Reproducibility Index

Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..

International Conference on Machine Learning (ICML) - 2024

Documentation Rate of Empirical Papers by Reproducibility Variable

Distribution of Empirical Papers by Number of Documented Variables

Website:

Venue	Year	Papers	Reproducibility Score Reproducibility Score based on Gundersen et al. (2025). See Methods for details.	Documentation Score Documentation Score is the average score over the seven reproducibility variables for empirical research papers. See Methods for details.	% Empirical Percentage of papers that are empirical research vs theoretical research.	% Industry Percentage of empirical research papers with at least one author from Industry.	Website
ICML	2024	2610	0.62	4.11	93.03%	39.99%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
$H$-Consistency Guarantees for Regression	❌	❌	✅	❌	❌	❌	✅	2
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting	❌	✅	✅	✅	✅	✅	✅	6
$\bfΦ_\textrmFlow$: Differentiable Simulations for PyTorch, TensorFlow and Jax	❌	✅	❌	❌	✅	❌	✅	3
$\mathttVITS$ : Variational Inference Thompson Sampling for contextual bandits	✅	❌	✅	❌	✅	❌	✅	4
$\rm E(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
$\textttMoE-RBench$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts	❌	✅	✅	❌	❌	❌	✅	3
$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy	❌	✅	✅	✅	❌	❌	✅	4
3D Geometric Shape Assembly via Efficient Point Cloud Matching	❌	❌	✅	❌	✅	❌	✅	3
3D-VLA: A 3D Vision-Language-Action Generative World Model	❌	❌	✅	❌	✅	✅	✅	4
A Bayesian Approach to Online Planning	✅	✅	✅	❌	❌	❌	✅	4
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models	✅	✅	✅	❌	✅	❌	✅	5
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design	❌	✅	✅	✅	✅	❌	✅	5
A Closer Look at the Limitations of Instruction Tuning	❌	❌	✅	❌	❌	❌	✅	2
A Computational Framework for Solving Wasserstein Lagrangian Flows	✅	✅	✅	✅	❌	❌	❌	4
A Contextual Combinatorial Bandit Approach to Negotiation	✅	❌	✅	❌	❌	❌	✅	3
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference	✅	✅	✅	❌	❌	❌	✅	4
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing	❌	✅	✅	❌	❌	❌	✅	3
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization	❌	✅	✅	✅	✅	❌	✅	5
A Distributional Analogue to the Successor Representation	✅	✅	✅	❌	❌	❌	✅	4
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization	✅	❌	✅	❌	✅	❌	✅	4
A Dual-module Framework for Counterfactual Estimation over Time	✅	✅	✅	✅	❌	❌	✅	5
A Dynamic Algorithm for Weighted Submodular Cover Problem	✅	❌	❌	❌	❌	❌	❌	1
A Dynamical Model of Neural Scaling Laws	❌	❌	✅	❌	❌	❌	✅	2
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization	✅	❌	✅	❌	✅	❌	✅	4
A Field Guide for Pacing Budget and ROS Constraints	✅	❌	❌	❌	❌	❌	✅	2
A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models	❌	❌	❌	❌	❌	❌	✅	1
A Fixed-Point Approach for Causal Generative Modeling	✅	❌	✅	✅	✅	❌	✅	5
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks	✅	❌	✅	✅	✅	❌	✅	5
A General Framework for Learning from Weak Supervision	✅	✅	✅	✅	❌	❌	✅	5
A General Framework for Sequential Decision-Making under Adaptivity Constraints	✅	❌	✅	❌	❌	❌	✅	3
A General Online Algorithm for Optimizing Complex Performance Metrics	✅	✅	✅	✅	❌	✅	✅	6
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts	❌	❌	❌	❌	❌	✅	✅	2
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective	✅	✅	✅	✅	✅	✅	❌	6
A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights	❌	❌	❌	❌	❌	❌	❌	0
A Geometric Explanation of the Likelihood OOD Detection Paradox	✅	✅	✅	❌	✅	❌	✅	5
A Global Geometric Analysis of Maximal Coding Rate Reduction	❌	❌	✅	❌	✅	❌	✅	3
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer	✅	✅	✅	✅	✅	❌	✅	6
A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design	❌	❌	❌	❌	✅	❌	✅	2
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts	❌	✅	✅	✅	❌	❌	✅	4
A Language Model’s Guide Through Latent Space	❌	❌	✅	❌	❌	❌	✅	2
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)	✅	✅	✅	❌	✅	❌	✅	5
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity	❌	✅	✅	✅	❌	❌	✅	4
A Minimaximalist Approach to Reinforcement Learning from Human Feedback	✅	❌	✅	❌	❌	❌	✅	3
A Multimodal Automated Interpretability Agent	❌	✅	✅	✅	❌	✅	✅	5
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering	✅	❌	❌	❌	❌	❌	❌	1
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness	✅	✅	✅	❌	✅	❌	✅	5
A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data	✅	✅	✅	✅	✅	❌	✅	6
A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions	✅	✅	❌	❌	✅	❌	✅	4
A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems	✅	✅	✅	❌	✅	❌	✅	5
A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces	✅	✅	✅	✅	✅	✅	✅	7
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization	✅	✅	✅	❌	✅	❌	✅	5
A New Robust Partial p-Wasserstein-Based Metric for Comparing Distributions	❌	❌	✅	❌	❌	❌	❌	1
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization	✅	❌	✅	❌	✅	❌	✅	4
A Persuasive Approach to Combating Misinformation	❌	❌	❌	❌	❌	❌	❌	0
A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs	✅	❌	❌	❌	❌	❌	❌	1
A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs	✅	✅	✅	✅	✅	❌	✅	6
A Provable Decision Rule for Out-of-Distribution Detection	✅	❌	✅	❌	❌	❌	❌	2
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts	✅	❌	✅	❌	✅	❌	✅	4
A Rate-Distortion View of Uncertainty Quantification	✅	✅	✅	❌	✅	❌	✅	5
A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes	✅	✅	❌	❌	❌	❌	✅	3
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?	✅	✅	✅	❌	✅	❌	✅	5
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction	❌	✅	✅	✅	✅	❌	✅	5
A Sparsity Principle for Partially Observable Causal Representation Learning	❌	✅	✅	❌	❌	❌	✅	3
A Statistical Framework for Data-dependent Retrieval-Augmented Models	❌	❌	✅	❌	❌	❌	✅	2
A Statistical Theory of Regularization-Based Continual Learning	✅	❌	❌	❌	❌	❌	✅	2
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle	✅	❌	❌	❌	❌	❌	❌	1
A Subquadratic Time Algorithm for Robust Sparse Mean Estimation	✅	❌	❌	❌	❌	❌	❌	1
A Tale of Tails: Model Collapse as a Change of Scaling Laws	❌	❌	✅	❌	❌	❌	✅	2
A Tensor Decomposition Perspective on Second-order RNNs	❌	✅	✅	✅	❌	❌	✅	4
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
A Theory of Fault-Tolerant Learning	❌	❌	❌	❌	❌	❌	❌	0
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
A Touch, Vision, and Language Dataset for Multimodal Alignment	❌	✅	✅	❌	✅	❌	✅	4
A Unified Adaptive Testing System Enabled by Hierarchical Structure Search	✅	✅	✅	✅	✅	❌	❌	5
A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples	❌	✅	❌	❌	❌	❌	✅	2
A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback	❌	❌	❌	❌	❌	❌	✅	1
A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation	❌	✅	✅	✅	❌	❌	✅	4
A Universal Class of Sharpness-Aware Minimization Algorithms	✅	✅	✅	❌	❌	❌	✅	4
A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles	✅	❌	❌	❌	❌	❌	❌	1
A connection between Tempering and Entropic Mirror Descent	✅	✅	❌	❌	❌	❌	✅	3
A decoder-only foundation model for time-series forecasting	❌	✅	✅	✅	✅	❌	✅	5
A fast algorithm to simulate nonlinear resistive networks	❌	✅	✅	❌	✅	✅	✅	5
A sampling theory perspective on activations for implicit neural representations	❌	❌	✅	❌	❌	❌	✅	2
A2Q+: Improving Accumulator-Aware Weight Quantization	❌	❌	✅	❌	❌	✅	✅	3
A3S: A General Active Clustering Method with Pairwise Constraints	✅	✅	✅	❌	✅	❌	✅	5
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization	✅	❌	✅	✅	✅	❌	✅	5
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation	✅	✅	✅	❌	✅	✅	✅	6
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints	✅	❌	✅	❌	❌	❌	✅	3
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors	✅	❌	✅	❌	❌	❌	✅	3
AI Alignment with Changing and Influenceable Reward Functions	✅	❌	❌	❌	❌	❌	❌	1
AI Control: Improving Safety Despite Intentional Subversion	❌	✅	✅	❌	❌	✅	✅	4
ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data	✅	❌	✅	✅	✅	✅	✅	6
AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training	✅	❌	✅	✅	✅	❌	✅	5
AND: Audio Network Dissection for Interpreting Deep Acoustic Models	✅	✅	✅	❌	✅	✅	✅	6
APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference	✅	✅	✅	✅	✅	❌	✅	6
AST-T5: Structure-Aware Pretraining for Code Generation and Understanding	✅	✅	✅	❌	✅	❌	✅	5
ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories	✅	✅	✅	✅	✅	❌	✅	6
Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence	✅	✅	✅	❌	✅	❌	✅	5
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion	✅	❌	❌	❌	❌	❌	❌	1
Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces	✅	✅	✅	❌	✅	❌	✅	5
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Accelerated Speculative Sampling Based on Tree Monte Carlo	✅	❌	✅	❌	❌	❌	✅	3
Accelerating Convergence in Bayesian Few-Shot Classification	✅	✅	✅	✅	✅	❌	✅	6
Accelerating Convergence of Score-Based Diffusion Models, Provably	❌	❌	✅	❌	❌	❌	❌	1
Accelerating Federated Learning with Quick Distributed Mean Estimation	✅	✅	✅	❌	✅	❌	✅	5
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers	✅	✅	✅	✅	✅	❌	✅	6
Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation	✅	✅	✅	❌	✅	❌	✅	5
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving	✅	✅	❌	✅	✅	❌	✅	5
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need	✅	✅	❌	❌	❌	❌	✅	3
Accelerating PDE Data Generation via Differential Operator Action in Solution Space	✅	✅	✅	❌	✅	✅	✅	6
Accelerating Parallel Sampling of Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Accelerating Transformer Pre-training with 2:4 Sparsity	✅	✅	✅	❌	✅	❌	✅	5
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention	✅	✅	✅	❌	✅	❌	✅	5
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling	✅	❌	✅	❌	❌	❌	✅	3
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts	✅	✅	❌	❌	❌	❌	✅	3
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition	✅	✅	✅	✅	✅	❌	✅	6
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations	✅	✅	✅	✅	✅	❌	✅	6
Activation-Descent Regularization for Input Optimization of ReLU Networks	✅	✅	✅	❌	❌	❌	✅	4
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice	✅	❌	✅	❌	✅	❌	✅	4
Active Label Correction for Semantic Segmentation with Foundation Models	✅	✅	✅	✅	❌	❌	✅	5
Active Preference Learning for Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
Active Ranking and Matchmaking, with Perfect Matchings	✅	❌	❌	❌	❌	❌	❌	1
Active Statistical Inference	✅	✅	✅	❌	❌	❌	✅	4
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control	❌	✅	✅	❌	✅	❌	✅	4
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate	✅	✅	❌	❌	✅	❌	✅	4
Adaptive Accompaniment with ReaLchords	❌	❌	✅	✅	❌	❌	✅	3
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning	✅	✅	✅	❌	✅	✅	✅	6
Adaptive Conformal Inference by Betting	✅	✅	✅	❌	❌	❌	✅	4
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity	❌	❌	✅	❌	❌	❌	✅	2
Adaptive Group Personalization for Federated Mutual Transfer Learning	✅	❌	✅	✅	✅	❌	✅	5
Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing	✅	✅	✅	✅	❌	❌	✅	5
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation	✅	✅	❌	❌	❌	❌	✅	3
Adaptive Observation Cost Control for Variational Quantum Eigensolvers	✅	✅	❌	❌	✅	❌	✅	4
Adaptive Online Experimental Design for Causal Discovery	✅	✅	✅	❌	❌	❌	❌	3
Adaptive Proximal Gradient Methods Are Universal Without Approximation	✅	✅	✅	❌	❌	❌	✅	4
Adaptive Robust Learning using Latent Bernoulli Variables	✅	✅	✅	✅	❌	❌	✅	5
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction	❌	✅	✅	✅	❌	❌	✅	4
Adaptive Stabilization Based on Machine Learning for Column Generation	✅	✅	✅	✅	✅	❌	✅	6
Adaptive Text Watermark for Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations	✅	❌	✅	❌	✅	✅	✅	5
Adaptively Learning to Select-Rank in Online Platforms	✅	✅	❌	❌	❌	❌	✅	3
Adaptively Perturbed Mirror Descent for Learning in Games	✅	✅	❌	❌	✅	❌	✅	4
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion	✅	✅	✅	✅	✅	❌	✅	6
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment	❌	❌	❌	❌	✅	❌	✅	2
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities	✅	✅	✅	❌	✅	❌	✅	5
Adversarial Attacks on Combinatorial Multi-Armed Bandits	✅	✅	✅	❌	❌	❌	✅	4
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies	❌	✅	✅	❌	❌	❌	✅	3
Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework	✅	✅	✅	❌	❌	❌	✅	4
Adversarially Robust Hypothesis Transfer Learning	❌	❌	❌	❌	❌	❌	❌	0
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning	✅	❌	✅	✅	✅	❌	✅	5
Agent Instructs Large Language Models to be General Zero-Shot Reasoners	❌	✅	✅	❌	✅	✅	✅	5
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast	✅	✅	✅	✅	✅	❌	✅	6
Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs	✅	✅	✅	❌	✅	✅	✅	6
Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms	✅	✅	✅	❌	✅	❌	✅	5
Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms	✅	❌	❌	❌	❌	❌	❌	1
Agnostic Sample Compression Schemes for Regression	✅	❌	❌	❌	❌	❌	❌	1
Ai-sampler: Adversarial Learning of Markov kernels with involutive maps	✅	✅	✅	❌	✅	❌	✅	5
Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models	✅	❌	❌	❌	❌	❌	❌	1
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses	❌	❌	❌	❌	❌	❌	❌	0
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning	✅	✅	✅	✅	❌	❌	✅	5
Aligning Transformers with Weisfeiler-Leman	❌	✅	✅	❌	✅	❌	✅	4
All-in-one simulation-based inference	✅	✅	✅	❌	❌	❌	✅	4
Allocation Requires Prediction Only if Inequality Is Low	❌	❌	✅	❌	❌	❌	✅	2
AlphaFold Meets Flow Matching for Generating Protein Ensembles	✅	✅	✅	✅	✅	❌	✅	6
AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training	✅	✅	✅	✅	✅	❌	✅	6
Ambiguity-Aware Abductive Learning	✅	❌	✅	❌	✅	❌	✅	4
Ameliorate Spurious Correlations in Dataset Condensation	❌	❌	✅	❌	✅	❌	✅	3
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models	❌	❌	✅	✅	✅	❌	✅	4
Amortized Equation Discovery in Hybrid Dynamical Systems	❌	✅	✅	✅	✅	❌	✅	5
Amortized Variational Deep Kernel Learning	❌	✅	✅	✅	✅	❌	✅	5
Amortizing Pragmatic Program Synthesis with Rankings	✅	✅	✅	❌	❌	❌	✅	4
An Analysis of Linear Time Series Forecasting Models	❌	✅	✅	✅	✅	❌	✅	5
An Effective Dynamic Gradient Calibration Method for Continual Learning	✅	❌	✅	✅	❌	❌	✅	4
An Efficient Maximal Ancestral Graph Listing Algorithm	✅	❌	❌	❌	❌	❌	✅	2
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems	✅	❌	✅	✅	✅	❌	✅	5
An Embodied Generalist Agent in 3D World	❌	✅	✅	✅	✅	❌	✅	5
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series	❌	❌	✅	❌	❌	❌	❌	1
An Empirical Study Into What Matters for Calibrating Vision-Language Models	❌	❌	✅	✅	✅	✅	✅	5
An Empirical Study of Realized GNN Expressiveness	❌	✅	✅	✅	✅	❌	✅	5
An Explicit Frame Construction for Normalizing 3D Point Clouds	❌	✅	✅	✅	✅	❌	✅	5
An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning	✅	✅	✅	❌	✅	❌	✅	5
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
An Independence-promoting Loss for Music Generation with Language Models	✅	✅	✅	✅	✅	❌	✅	6
An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network	❌	❌	✅	❌	✅	❌	✅	3
An Information Theoretic Approach to Interaction-Grounded Learning	✅	❌	✅	❌	❌	❌	✅	3
An Information-Theoretic Analysis of In-Context Learning	❌	❌	❌	❌	❌	❌	❌	0
An Interpretable Evaluation of Entropy-based Novelty of Generative Models	✅	✅	✅	❌	❌	❌	✅	4
An Intrinsic Vector Heat Network	❌	❌	✅	❌	✅	❌	✅	3
An Iterative Min-Min Optimization Method for Sparse Bayesian Learning	✅	✅	✅	❌	✅	✅	✅	6
An LLM Compiler for Parallel Function Calling	❌	✅	✅	❌	✅	✅	✅	5
An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization	✅	✅	✅	❌	❌	❌	✅	4
An Unsupervised Approach for Periodic Source Detection in Time Series	❌	✅	✅	✅	✅	❌	✅	5
An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation	✅	✅	✅	❌	✅	✅	✅	6
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts	❌	❌	✅	❌	✅	❌	✅	3
Analyzing $D^α$ seeding for $k$-means	❌	✅	✅	❌	❌	❌	✅	3
Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical and Geometric Constraints	✅	✅	✅	❌	❌	❌	✅	4
Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs	✅	✅	✅	✅	✅	❌	✅	6
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls	❌	✅	✅	❌	❌	❌	✅	3
Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu’s formula	❌	✅	❌	❌	❌	❌	✅	2
Approximate Nearest Neighbor Search with Window Filters	✅	✅	✅	❌	✅	❌	✅	5
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA	✅	✅	✅	✅	✅	❌	✅	6
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL	✅	✅	✅	❌	✅	❌	✅	5
Arrows of Time for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations	✅	✅	✅	❌	❌	❌	✅	4
Assessing Large Language Models on Climate Information	❌	❌	❌	❌	❌	❌	✅	1
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications	❌	✅	✅	✅	✅	❌	✅	5
Asymmetry in Low-Rank Adapters of Foundation Models	❌	✅	✅	✅	❌	❌	✅	4
Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing	❌	❌	❌	❌	❌	❌	✅	1
Asymptotics of Learning with Deep Structured (Random) Features	❌	✅	✅	✅	❌	❌	✅	4
Asymptotics of feature learning in two-layer networks after one gradient-step	❌	✅	❌	❌	❌	❌	✅	2
AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios	✅	❌	✅	✅	❌	❌	✅	4
Attack-free Evaluating and Enhancing Adversarial Robustness on Categorical Data	✅	✅	✅	❌	✅	❌	✅	5
Attention Meets Post-hoc Interpretability: A Mathematical Perspective	❌	✅	✅	✅	✅	❌	✅	5
AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers	❌	✅	✅	✅	✅	❌	✅	5
Attribute Based Interpretable Evaluation Metrics for Generative Models	❌	✅	✅	❌	✅	❌	✅	4
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games	❌	✅	❌	✅	✅	❌	✅	4
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities	❌	✅	✅	❌	✅	❌	✅	4
Auditing Private Prediction	✅	❌	✅	❌	❌	❌	✅	3
Augmenting Decision with Hypothesis in Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Auto-Encoding Morph-Tokens for Multimodal LLM	❌	✅	✅	✅	✅	❌	✅	5
Auto-Linear Phenomenon in Subsurface Imaging	❌	❌	✅	✅	✅	❌	✅	4
Auto-Regressive Next-Token Predictors are Universal Learners	❌	❌	✅	✅	✅	❌	✅	4
AutoOS: Make Your OS More Powerful by Exploiting Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
Autoencoding Conditional Neural Processes for Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
Autoformalizing Euclidean Geometry	✅	✅	✅	✅	❌	✅	✅	6
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation	✅	✅	✅	❌	❌	❌	✅	4
Automated Loss function Search for Class-imbalanced Node Classification	✅	❌	✅	✅	✅	❌	✅	5
Automated Statistical Model Discovery with Language Models	✅	❌	✅	❌	❌	✅	✅	4
Automating the Selection of Proxy Variables of Unmeasured Confounders	✅	✅	✅	❌	❌	❌	✅	4
Autonomous Sparse Mean-CVaR Portfolio Optimization	✅	✅	✅	❌	❌	❌	✅	4
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
BAGEL: Bootstrapping Agents by Guiding Exploration with Language	❌	❌	✅	❌	❌	❌	✅	2
BAT: Learning to Reason about Spatial Sounds with Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation	✅	✅	✅	❌	❌	❌	✅	4
BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation	✅	✅	✅	✅	✅	❌	✅	6
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks	✅	✅	✅	❌	✅	❌	✅	5
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback	✅	❌	✅	❌	❌	❌	✅	3
BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges	✅	✅	✅	❌	✅	❌	✅	5
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks	✅	✅	✅	✅	✅	❌	✅	6
Bagged Deep Image Prior for Recovering Images in the Presence of Speckle Noise	✅	✅	✅	❌	✅	❌	✅	5
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance	❌	✅	✅	✅	❌	❌	✅	4
Balanced Resonate-and-Fire Neurons	✅	✅	✅	✅	✅	✅	✅	7
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection	✅	❌	✅	❌	✅	❌	✅	4
Balancing Similarity and Complementarity for Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Barrier Algorithms for Constrained Non-Convex Optimization	✅	❌	❌	❌	❌	❌	❌	1
Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation	❌	❌	✅	❌	❌	❌	✅	2
Batch and match: black-box variational inference with a score-based divergence	✅	✅	✅	❌	❌	❌	✅	4
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition	✅	✅	✅	❌	❌	❌	✅	4
Bayesian Adaptation of Network Depth and Width for Continual Learning	❌	✅	✅	✅	✅	❌	✅	5
Bayesian Design Principles for Offline-to-Online Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
Bayesian Exploration Networks	✅	❌	❌	❌	❌	❌	✅	2
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification	✅	❌	✅	✅	❌	❌	✅	4
Bayesian Optimization of Function Networks with Partial Evaluations	✅	✅	✅	❌	✅	❌	✅	5
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
Bayesian Program Learning by Decompiling Amortized Knowledge	❌	❌	✅	❌	✅	❌	✅	3
Bayesian Regret Minimization in Offline Bandits	✅	❌	❌	❌	❌	❌	✅	2
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning	✅	✅	✅	✅	✅	❌	✅	6
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning	✅	✅	✅	✅	❌	❌	✅	5
Behavior Generation with Latent Actions	❌	✅	✅	✅	✅	❌	✅	5
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images	✅	❌	✅	❌	❌	❌	✅	3
Benchmarking Deletion Metrics with the Principled Explanations	✅	✅	✅	✅	✅	❌	✅	6
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT	❌	✅	✅	✅	✅	✅	✅	6
Benign Overfitting in Adversarial Training of Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data	❌	❌	❌	❌	❌	❌	✅	1
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models	✅	❌	✅	✅	✅	❌	✅	5
Best Arm Identification for Stochastic Rising Bandits	✅	✅	❌	❌	✅	❌	✅	4
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization	✅	❌	❌	❌	❌	❌	✅	2
Better & Faster Large Language Models via Multi-token Prediction	❌	❌	✅	✅	✅	❌	✅	4
Better Locally Private Sparse Estimation Given Multiple Samples Per User	✅	✅	✅	❌	✅	❌	✅	5
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks	✅	✅	✅	❌	❌	❌	✅	4
BetterV: Controlled Verilog Generation with Discriminative Guidance	❌	❌	✅	❌	✅	✅	✅	4
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws	❌	❌	❌	❌	✅	❌	✅	2
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling	❌	✅	✅	❌	❌	❌	✅	3
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning	❌	❌	✅	❌	❌	❌	✅	2
Beyond Individual Input for Deep Anomaly Detection on Tabular Data	✅	✅	✅	✅	✅	❌	✅	6
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process	✅	✅	✅	✅	✅	❌	✅	6
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains	❌	✅	✅	❌	✅	❌	❌	3
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models	❌	✅	✅	❌	❌	❌	✅	3
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy	✅	❌	✅	❌	❌	❌	✅	3
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients	✅	❌	✅	❌	✅	❌	✅	4
Beyond the Norms: Detecting Prediction Errors in Regression Models	✅	✅	✅	✅	✅	❌	✅	6
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets	✅	❌	✅	✅	❌	✅	✅	5
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization	❌	❌	✅	✅	✅	✅	✅	5
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs	✅	✅	✅	❌	✅	❌	✅	5
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model	❌	✅	✅	✅	✅	❌	✅	5
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Bifurcated Attention for Single-Context Large-Batch Sampling	✅	✅	✅	✅	✅	❌	✅	6
Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering	✅	✅	✅	❌	✅	❌	✅	5
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning	❌	✅	✅	❌	❌	❌	✅	3
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains	❌	✅	✅	✅	✅	❌	✅	5
Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS	✅	✅	❌	❌	✅	✅	✅	5
Bivariate Causal Discovery using Bayesian Model Selection	❌	❌	✅	❌	❌	❌	✅	2
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares	❌	✅	❌	❌	❌	❌	✅	2
Boosting Offline Optimizers with Surrogate Sensitivity	✅	✅	✅	❌	❌	❌	✅	4
Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays	✅	✅	✅	❌	❌	❌	✅	4
Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation	❌	❌	✅	✅	✅	❌	✅	4
Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium	❌	❌	✅	❌	❌	❌	✅	2
Borda Regret Minimization for Generalized Linear Dueling Bandits	✅	❌	✅	❌	❌	❌	✅	3
Bottleneck-Minimal Indexing for Generative Document Retrieval	❌	✅	✅	✅	❌	❌	✅	4
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints	❌	✅	✅	❌	✅	❌	✅	4
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs	❌	✅	✅	✅	✅	✅	✅	6
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data	✅	✅	✅	❌	❌	❌	✅	4
Box Facets and Cut Facets of Lifted Multicut Polytopes	❌	❌	❌	❌	❌	❌	❌	0
Boximator: Generating Rich and Controllable Motions for Video Synthesis	❌	❌	✅	❌	✅	❌	✅	3
Breadth-First Exploration on Adaptive Grid for Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Break the Sequential Dependency of LLM Inference Using Lookahead Decoding	✅	✅	✅	❌	✅	✅	✅	6
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents	✅	✅	✅	❌	❌	❌	✅	4
Breaking through the learning plateaus of in-context learning in Transformer	❌	❌	✅	❌	❌	❌	✅	2
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning	✅	✅	✅	❌	❌	❌	✅	4
Bridging Environments and Language with Rendering Functions and Vision-Language Models	✅	❌	✅	❌	✅	✅	✅	5
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses	❌	✅	✅	❌	❌	✅	✅	4
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning	✅	✅	✅	✅	✅	✅	✅	7
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models	✅	✅	✅	❌	❌	❌	✅	4
Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel	✅	✅	✅	❌	✅	❌	✅	5
Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds	✅	✅	✅	❌	✅	❌	✅	5
Building Socially-Equitable Public Models	✅	✅	✅	❌	❌	❌	✅	4
By Tying Embeddings You Are Assuming the Distributional Hypothesis	❌	✅	✅	❌	❌	❌	✅	3
ByMI: Byzantine Machine Identification with False Discovery Rate Control	✅	✅	✅	❌	✅	✅	✅	6
Byzantine Resilient and Fast Federated Few-Shot Learning	✅	❌	❌	❌	❌	❌	✅	2
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates	✅	❌	✅	❌	✅	❌	✅	4
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models	✅	✅	✅	✅	❌	❌	✅	5
CARTE: Pretraining and Transfer for Tabular Learning	❌	✅	✅	✅	✅	❌	✅	5
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables	❌	❌	✅	✅	✅	❌	✅	4
CCM: Real-Time Controllable Visual Content Creation Using Text-to-Image Consistency Models	❌	❌	✅	❌	✅	❌	✅	3
CF-OPT: Counterfactual Explanations for Structured Prediction	✅	✅	✅	❌	✅	❌	✅	5
CHAI: Clustered Head Attention for Efficient LLM Inference	❌	❌	✅	❌	✅	❌	✅	3
CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback	✅	✅	✅	❌	✅	✅	✅	6
CKGConv: General Graph Convolution with Continuous Kernels	❌	✅	✅	✅	✅	❌	✅	5
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes	❌	✅	✅	✅	✅	✅	✅	6
CLLMs: Consistency Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
COALA: A Practical and Vision-Centric Federated Learning Platform	❌	❌	✅	✅	✅	❌	✅	4
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability	✅	✅	✅	❌	✅	❌	✅	5
COPAL: Continual Pruning in Large Language Generative Models	✅	❌	✅	❌	✅	❌	✅	4
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution	❌	❌	✅	❌	❌	❌	✅	2
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection	✅	✅	✅	✅	❌	❌	✅	5
CW Complex Hypothesis for Image Data	❌	❌	✅	❌	❌	❌	✅	2
CaM: Cache Merging for Memory-efficient LLMs Inference	✅	✅	✅	❌	✅	❌	✅	5
CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources	✅	✅	✅	✅	✅	✅	✅	7
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process	❌	✅	✅	❌	❌	✅	✅	4
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling	❌	✅	✅	✅	✅	❌	✅	5
Calibration Bottleneck: Over-compressed Representations are Less Calibratable	❌	✅	✅	✅	❌	❌	✅	4
Can AI Assistants Know What They Don’t Know?	❌	✅	✅	✅	✅	❌	✅	5
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?	✅	❌	❌	❌	❌	❌	❌	1
Can Implicit Bias Imply Adversarial Robustness?	✅	✅	✅	❌	❌	❌	✅	4
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?	❌	❌	❌	❌	❌	❌	✅	1
Can Machines Learn the True Probabilities?	❌	❌	❌	❌	❌	❌	❌	0
Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks	❌	✅	✅	❌	✅	❌	✅	4
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective	✅	❌	✅	❌	❌	❌	✅	3
Can a Few Decide for Many? The Metric Distortion of Sortition	✅	❌	✅	❌	❌	❌	✅	3
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data	✅	✅	✅	❌	❌	❌	✅	4
CarbonNovo: Joint Design of Protein Structure and Sequence Using a Unified Energy-based Model	✅	✅	✅	✅	✅	❌	✅	6
Careful with that Scalpel: Improving Gradient Surgery with an EMA	✅	❌	✅	❌	❌	❌	✅	3
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling	❌	✅	✅	✅	✅	❌	✅	5
Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Case-Based or Rule-Based: How Do Transformers Do the Math?	✅	✅	✅	✅	❌	❌	✅	5
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning	❌	❌	✅	✅	✅	❌	✅	4
Category-Aware Active Domain Adaptation	✅	✅	✅	✅	✅	❌	✅	6
CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series	✅	❌	✅	✅	✅	✅	✅	6
Causal Action Influence Aware Counterfactual Data Augmentation	✅	✅	✅	✅	✅	❌	✅	6
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals	✅	❌	❌	❌	❌	❌	❌	1
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model	✅	✅	✅	✅	✅	❌	✅	6
Causal Discovery via Conditional Independence Testing with Proxy Variables	✅	✅	✅	❌	❌	❌	✅	4
Causal Discovery with Fewer Conditional Independence Tests	✅	✅	✅	❌	❌	❌	❌	3
Causal Effect Identification in LiNGAM Models with Latent Confounders	✅	✅	❌	❌	❌	❌	✅	3
Causal Inference from Competing Treatments	✅	❌	❌	❌	❌	❌	❌	1
Causal Inference out of Control: Estimating Performativity without Treatment Randomization	❌	❌	✅	❌	❌	✅	✅	3
Causal Representation Learning Made Identifiable by Grouping of Observational Variables	✅	✅	✅	❌	✅	❌	✅	5
Causal Representation Learning from Multiple Distributions: A General Setting	❌	❌	❌	❌	❌	❌	❌	0
Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference	✅	❌	✅	✅	✅	❌	✅	5
Causality Based Front-door Defense Against Backdoor Attack on Language Models	❌	✅	✅	✅	✅	❌	✅	5
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization	✅	❌	✅	❌	✅	❌	✅	4
Cell2Sentence: Teaching Large Language Models the Language of Biology	❌	❌	✅	✅	✅	❌	✅	4
Centralized Selection with Preferences in the Presence of Biases	✅	✅	✅	❌	❌	❌	✅	4
Certifiably Byzantine-Robust Federated Conformal Prediction	✅	✅	✅	✅	✅	❌	✅	6
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator	✅	❌	✅	❌	❌	❌	✅	3
Chain-of-Thought Predictive Control	❌	❌	✅	✅	❌	❌	✅	3
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery	❌	❌	✅	❌	❌	❌	✅	2
Challenges in Training PINNs: A Loss Landscape Perspective	✅	✅	❌	❌	✅	✅	✅	5
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale	✅	✅	✅	❌	✅	❌	✅	5
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation	✅	✅	✅	❌	❌	✅	✅	5
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum	❌	❌	❌	❌	❌	❌	✅	1
Characterizing ResNet’s Universal Approximation Capability	❌	❌	❌	❌	❌	❌	✅	1
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension	❌	✅	✅	✅	❌	❌	✅	4
Chasing Convex Functions with Long-term Constraints	✅	❌	❌	❌	❌	❌	✅	2
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference	❌	✅	✅	❌	❌	❌	✅	3
Class-Imbalanced Graph Learning without Class Rebalancing	✅	✅	✅	✅	✅	❌	✅	6
Classification Under Strategic Self-Selection	❌	✅	✅	✅	✅	❌	✅	5
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference	✅	✅	✅	✅	✅	❌	❌	5
Clifford-Steerable Convolutional Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization	✅	❌	❌	❌	❌	❌	❌	1
Cluster-Aware Similarity Diffusion for Instance Retrieval	✅	✅	✅	❌	✅	❌	✅	5
Clustered Federated Learning via Gradient-based Partitioning	✅	✅	✅	✅	❌	❌	✅	5
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations	❌	✅	✅	❌	✅	❌	✅	4
Coactive Learning for Large Language Models using Implicit User Feedback	✅	✅	✅	❌	❌	❌	✅	4
Coarse-To-Fine Tensor Trains for Compact Visual Representations	❌	✅	✅	❌	✅	❌	✅	4
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models	✅	❌	✅	✅	✅	✅	✅	6
Code as Reward: Empowering Reinforcement Learning with VLMs	❌	✅	✅	❌	❌	❌	✅	3
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay	✅	✅	✅	✅	✅	❌	✅	6
Codebook Features: Sparse and Discrete Interpretability for Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
CogBench: a large language model walks into a psychology lab	✅	✅	✅	❌	❌	❌	✅	4
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding	✅	❌	✅	✅	✅	❌	✅	5
Collaborative Heterogeneous Causal Inference Beyond Meta-analysis	✅	❌	✅	❌	❌	❌	❌	2
Collaborative Learning with Different Labeling Functions	✅	❌	❌	❌	❌	❌	❌	1
Collage: Light-Weight Low-Precision Strategy for LLM Training	✅	✅	✅	✅	✅	❌	✅	6
Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval	✅	✅	✅	❌	✅	❌	✅	5
Collective Certified Robustness against Graph Injection Attacks	✅	✅	✅	✅	❌	✅	✅	6
Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better	✅	✅	✅	❌	❌	❌	❌	3
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond	✅	❌	❌	❌	❌	❌	❌	1
Combining Experimental and Historical Data for Policy Evaluation	✅	✅	✅	❌	❌	❌	✅	4
Community-Invariant Graph Contrastive Learning	✅	✅	✅	✅	✅	✅	✅	7
Compact Optimality Verification for Optimization Proxies	✅	❌	✅	❌	✅	✅	✅	5
Comparing Graph Transformers via Positional Encodings	❌	✅	✅	❌	❌	✅	✅	4
CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents	❌	✅	❌	❌	❌	✅	✅	3
Completing Visual Objects via Bridging Generation and Segmentation	❌	✅	✅	❌	✅	❌	✅	4
Complexity Matters: Feature Learning in the Presence of Spurious Correlations	❌	✅	✅	✅	✅	❌	✅	5
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks	❌	✅	❌	❌	❌	❌	✅	2
Compositional Curvature Bounds for Deep Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Compositional Few-Shot Class-Incremental Learning	❌	✅	✅	✅	❌	❌	✅	4
Compositional Image Decomposition with Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Compositional Text-to-Image Generation with Dense Blob Representations	❌	❌	✅	❌	✅	❌	✅	3
Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach	❌	✅	✅	❌	✅	❌	✅	4
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation	❌	✅	✅	✅	✅	❌	✅	5
Compressing Large Language Models by Joint Sparsification and Quantization	✅	✅	✅	✅	❌	❌	✅	5
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth	❌	❌	✅	❌	❌	❌	✅	2
Compute Better Spent: Replacing Dense Layers with Structured Matrices	❌	✅	✅	✅	✅	❌	✅	5
ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models	❌	✅	✅	✅	❌	✅	✅	5
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables	❌	❌	❌	❌	❌	❌	❌	0
Conditional Common Entropy for Instrumental Variable Testing and Partial Identification	✅	✅	✅	❌	❌	❌	✅	4
Conditional Language Learning with Context	❌	✅	✅	❌	✅	❌	✅	4
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations	❌	✅	✅	✅	✅	✅	✅	6
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation	✅	✅	✅	✅	❌	✅	✅	6
Confidence Aware Inverse Constrained Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Confidence-aware Contrastive Learning for Selective Classification	✅	✅	✅	✅	❌	❌	✅	5
Configurable Mirror Descent: Towards a Unification of Decision Making	✅	✅	✅	❌	✅	❌	✅	5
Conformal Prediction Sets Improve Human Decision Making	❌	✅	✅	✅	✅	❌	✅	5
Conformal Prediction for Deep Classifier via Label Ranking	❌	✅	✅	✅	❌	❌	✅	4
Conformal Prediction with Learned Features	✅	❌	✅	✅	❌	❌	✅	4
Conformal Predictions under Markovian Data	❌	❌	✅	✅	❌	❌	✅	3
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)	❌	✅	✅	✅	❌	❌	✅	4
Conformal prediction for multi-dimensional time series by ellipsoidal sets	✅	✅	✅	✅	❌	❌	✅	5
Conformalized Adaptive Forecasting of Heterogeneous Trajectories	✅	✅	✅	✅	❌	❌	✅	5
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration	✅	✅	✅	✅	❌	❌	✅	5
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases	✅	✅	✅	❌	✅	❌	✅	5
Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations	❌	❌	✅	❌	❌	❌	✅	2
Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models	✅	✅	✅	❌	✅	❌	✅	5
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?	❌	✅	✅	✅	✅	❌	✅	5
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting	❌	❌	❌	❌	❌	❌	✅	1
Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data	❌	✅	✅	❌	❌	❌	✅	3
Consistent Long-Term Forecasting of Ergodic Dynamical Systems	✅	❌	✅	✅	✅	❌	❌	4
Consistent Submodular Maximization	✅	✅	✅	❌	❌	❌	✅	4
Constrained Ensemble Exploration for Unsupervised Skill Discovery	✅	✅	✅	❌	❌	❌	✅	4
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics	✅	✅	✅	✅	❌	❌	✅	5
Constrained Reinforcement Learning Under Model Mismatch	✅	❌	✅	❌	❌	❌	✅	3
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos	❌	✅	✅	✅	❌	❌	✅	4
Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data	❌	✅	✅	✅	❌	❌	✅	4
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design	✅	✅	✅	✅	✅	✅	✅	7
Contextual Feature Selection with Conditional Stochastic Gates	✅	✅	✅	✅	✅	❌	✅	6
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning	❌	✅	✅	✅	❌	❌	✅	4
Continuous Treatment Effects with Surrogate Outcomes	✅	❌	✅	❌	❌	❌	✅	3
Contrasting Multiple Representations with the Multi-Marginal Matching Gap	✅	❌	✅	✅	✅	❌	✅	5
Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources	❌	✅	✅	✅	❌	❌	✅	4
Contrastive Predict-and-Search for Mixed Integer Linear Programs	❌	❌	✅	✅	✅	✅	✅	5
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation	❌	✅	✅	❌	❌	❌	✅	3
Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Controllable Prompt Tuning For Balancing Group Distributional Robustness	❌	✅	✅	✅	✅	❌	✅	5
Controlled Decoding from Language Models	❌	❌	✅	❌	❌	❌	✅	2
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy	❌	✅	✅	✅	❌	❌	❌	3
Convergence Guarantees for the DeepWalk Embedding on Block Models	✅	❌	❌	❌	❌	❌	✅	2
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms	✅	❌	❌	❌	✅	❌	✅	3
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point	✅	❌	❌	❌	❌	❌	✅	2
Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions	✅	❌	❌	❌	❌	❌	✅	2
Convergence of Some Convex Message Passing Algorithms to a Fixed Point	✅	❌	❌	❌	❌	❌	❌	1
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption	❌	✅	✅	❌	✅	✅	✅	5
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time	❌	❌	✅	❌	❌	❌	❌	1
Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning	✅	✅	✅	✅	✅	❌	✅	6
Cooperative Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation	✅	✅	✅	❌	❌	❌	✅	4
Copula-Nested Spectral Kernel Network	❌	❌	✅	❌	❌	❌	✅	2
Copyright Traps for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Coresets for Multiple $\ell_p$ Regression	❌	❌	✅	❌	❌	✅	✅	3
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder	✅	✅	✅	❌	❌	❌	✅	4
Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning	✅	✅	✅	❌	✅	❌	✅	5
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks	✅	✅	✅	✅	✅	❌	✅	6
Counterfactual Image Editing	❌	❌	✅	❌	❌	❌	❌	1
Counterfactual Metarules for Local and Global Recourse	❌	❌	✅	✅	✅	❌	✅	4
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training	✅	✅	✅	✅	✅	❌	✅	6
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation	❌	❌	✅	❌	❌	❌	✅	2
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Creative Text-to-Audio Generation via Synthesizer Programming	✅	✅	✅	✅	✅	❌	✅	6
Criterion Collapse and Loss Distribution Control	❌	✅	✅	✅	❌	❌	✅	4
Critical feature learning in deep neural networks	✅	✅	✅	❌	❌	❌	✅	4
Critical windows: non-asymptotic theory for feature emergence in diffusion models	❌	❌	✅	❌	❌	❌	✅	2
Cross-Domain Policy Adaptation by Capturing Representation Mismatch	✅	✅	✅	❌	✅	❌	✅	5
Cross-domain Open-world Discovery	❌	✅	✅	❌	❌	❌	✅	3
Cross-view Masked Diffusion Transformers for Person Image Synthesis	❌	✅	✅	❌	✅	❌	✅	4
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers	✅	✅	✅	✅	❌	❌	✅	5
CuTS: Customizable Tabular Synthetic Data Generation	✅	✅	✅	✅	✅	❌	✅	6
CurBench: Curriculum Learning Benchmark	❌	✅	✅	✅	✅	❌	✅	5
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes	❌	✅	✅	✅	❌	❌	✅	4
D-Flow: Differentiating through Flows for Controlled Generation	✅	❌	✅	✅	✅	❌	✅	5
DAG-Based Column Generation for Adversarial Team Games	✅	❌	✅	❌	✅	✅	✅	5
DE-COP: Detecting Copyrighted Content in Language Models Training Data	✅	✅	✅	❌	✅	❌	✅	5
DFA-RAG: Conversational Semantic Router for Large Language Model with Definite Finite Automaton	✅	❌	✅	❌	❌	❌	✅	3
DFD: Distilling the Feature Disparity Differently for Detectors	❌	✅	✅	❌	✅	❌	✅	4
DFlow: A Generative Model Combining Denoising AutoEncoder and Normalizing Flow for High Fidelity Waveform Generation	❌	✅	✅	❌	✅	❌	✅	4
DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation	✅	✅	✅	❌	❌	❌	❌	3
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation	✅	✅	✅	❌	❌	❌	✅	4
DITTO: Diffusion Inference-Time T-Optimization for Music Generation	✅	❌	❌	❌	✅	❌	✅	3
DMTG: One-Shot Differentiable Multi-Task Grouping	❌	✅	✅	✅	✅	❌	✅	5
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation	✅	✅	✅	✅	❌	❌	✅	5
DNCs Require More Planning Steps	❌	❌	❌	❌	❌	❌	✅	1
DOGE: Domain Reweighting with Generalization Estimation	✅	✅	✅	❌	❌	❌	✅	4
DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems	❌	✅	✅	✅	✅	❌	✅	5
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training	❌	✅	✅	❌	✅	❌	✅	4
DPZero: Private Fine-Tuning of Language Models without Backpropagation	✅	✅	✅	✅	✅	❌	✅	6
DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images	❌	❌	✅	❌	❌	❌	✅	2
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design	✅	✅	✅	❌	❌	❌	✅	4
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning	✅	✅	✅	✅	❌	❌	✅	5
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection	❌	❌	✅	✅	✅	❌	✅	4
DUPLEX: Dual GAT for Complex Embedding of Directed Graphs	❌	✅	✅	✅	❌	❌	✅	4
Data Engineering for Scaling Language Models to 128K Context	❌	❌	✅	❌	✅	❌	✅	3
Data Poisoning Attacks against Conformal Prediction	❌	❌	✅	✅	❌	❌	✅	3
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond	✅	❌	✅	✅	❌	✅	✅	5
Data-Efficient Molecular Generation with Hierarchical Textual Inversion	✅	✅	✅	✅	✅	❌	✅	6
Data-efficient Large Vision Models through Sequential Autoregression	❌	✅	✅	✅	✅	❌	✅	5
Data-free Distillation of Diffusion Models with Bootstrapping	✅	❌	✅	✅	✅	❌	✅	5
Data-free Neural Representation Compression with Riemannian Neural Dynamics	❌	✅	✅	✅	✅	❌	✅	5
DataFreeShield: Defending Adversarial Attacks without Training Data	✅	✅	✅	❌	✅	✅	✅	6
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection	❌	✅	✅	✅	✅	❌	✅	5
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization	✅	❌	❌	❌	❌	❌	❌	1
Debating with More Persuasive LLMs Leads to More Truthful Answers	✅	✅	✅	✅	❌	❌	✅	5
Debiased Distribution Compression	✅	✅	✅	❌	✅	❌	✅	5
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics	✅	✅	✅	❌	❌	❌	✅	4
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers	✅	❌	✅	❌	❌	❌	✅	3
Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective	✅	✅	✅	✅	❌	❌	✅	5
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning	✅	✅	✅	❌	✅	❌	✅	5
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression	❌	✅	✅	❌	✅	❌	✅	4
Decoding-time Realignment of Language Models	✅	❌	✅	✅	❌	❌	✅	4
Decomposable Submodular Maximization in Federated Setting	✅	❌	❌	❌	❌	❌	❌	1
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling	❌	✅	✅	✅	✅	❌	✅	5
Decomposing and Editing Predictions by Modeling Model Computation	✅	✅	✅	✅	✅	❌	✅	6
Deconstructing the Goldilocks Zone of Neural Network Initialization	❌	✅	✅	❌	❌	❌	✅	3
Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information	✅	✅	✅	❌	✅	❌	✅	5
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Decoupling Learning and Decision-Making: Breaking the $\mathcalO(\sqrtT)$ Barrier in Online Resource Allocation with First-Order Methods	✅	❌	❌	❌	❌	❌	✅	2
Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration	✅	❌	✅	❌	❌	❌	✅	3
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures	❌	✅	✅	❌	✅	❌	✅	4
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization	✅	✅	✅	✅	❌	❌	✅	5
Deep Fusion: Efficient Network Training via Pre-trained Initializations	❌	❌	✅	❌	✅	❌	✅	3
Deep Networks Always Grok and Here is Why	❌	❌	✅	✅	✅	❌	✅	4
Deep Neural Room Acoustics Primitive	❌	✅	✅	❌	✅	❌	✅	4
Deep Regression Representation Learning with Topology	❌	✅	✅	✅	❌	❌	✅	4
Deep Stochastic Mechanics	✅	✅	❌	❌	✅	❌	✅	4
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning	✅	✅	❌	❌	❌	❌	✅	3
Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss	❌	❌	❌	❌	❌	❌	❌	0
Defense against Backdoor Attack on Pre-trained Language Models via Head Pruning and Attention Normalization	✅	✅	✅	✅	✅	❌	✅	6
Defense against Model Extraction Attack by Bayesian Active Watermarking	✅	❌	✅	❌	✅	❌	✅	4
Defining Neural Network Architecture through Polytope Structures of Datasets	✅	❌	✅	❌	❌	❌	✅	3
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration	✅	❌	✅	❌	❌	❌	✅	3
Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation	❌	✅	✅	✅	❌	❌	✅	4
Deletion-Anticipative Data Selection with a Limited Budget	✅	✅	✅	✅	✅	❌	✅	6
Delving into Differentially Private Transformer	✅	❌	✅	❌	✅	❌	✅	4
Delving into the Convergence of Generalized Smooth Minimax Optimization	✅	✅	✅	❌	❌	❌	✅	4
Demystifying SGD with Doubly Stochastic Gradients	✅	❌	❌	❌	❌	❌	✅	2
Denoising Autoregressive Representation Learning	❌	❌	✅	✅	❌	❌	✅	3
Dense Reward for Free in Reinforcement Learning from Human Feedback	❌	✅	✅	✅	✅	❌	✅	5
Density Ratio Estimation with Doubly Strong Robustness	❌	❌	✅	✅	❌	❌	✅	3
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts	✅	✅	✅	✅	✅	❌	✅	6
Designing Decision Support Systems using Counterfactual Prediction Sets	✅	✅	✅	✅	✅	✅	✅	7
DetKDS: Knowledge Distillation Search for Object Detectors	✅	✅	✅	✅	✅	❌	✅	6
Detecting Any instruction-to-answer interaction relationship:Universal Instruction-to-Answer Navigator for Med-VQA	✅	❌	✅	❌	✅	❌	✅	4
Detecting Influence Structures in Multi-Agent Reinforcement Learning	❌	❌	❌	❌	✅	❌	✅	2
Detecting and Identifying Selection Structure in Sequential Data	✅	❌	❌	❌	❌	❌	❌	1
DiJiang: Efficient Large Language Models through Compact Kernelization	✅	✅	✅	❌	✅	❌	❌	4
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models	❌	✅	✅	✅	❌	❌	❌	3
Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View	❌	❌	✅	❌	❌	❌	❌	1
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation	✅	✅	✅	❌	✅	❌	✅	5
DiffDA: a Diffusion model for weather-scale Data Assimilation	✅	✅	✅	✅	✅	❌	✅	6
DiffFPR: Diffusion Prior for Oversampled Fourier Phase Retrieval	✅	✅	✅	❌	❌	❌	✅	4
DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching	✅	✅	✅	❌	✅	❌	✅	5
Differentiability and Optimization of Multiparameter Persistent Homology	❌	✅	✅	❌	❌	❌	✅	3
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution	❌	✅	✅	❌	✅	❌	✅	4
Differentiable Combinatorial Scheduling at Scale	✅	✅	✅	❌	✅	✅	✅	6
Differentiable Distributionally Robust Optimization Layers	❌	✅	❌	✅	✅	❌	✅	4
Differentiable Mapper for Topological Optimization of Data Representation	✅	✅	✅	❌	❌	❌	✅	4
Differentiable Model Scaling using Differentiable Topk	❌	✅	✅	❌	✅	❌	✅	4
Differentiable Weightless Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Differentially Private Bias-Term Fine-tuning of Foundation Models	✅	✅	✅	❌	✅	❌	✅	5
Differentially Private Decentralized Learning with Random Walks	✅	✅	✅	✅	❌	❌	✅	5
Differentially Private Domain Adaptation with Theoretical Guarantees	✅	❌	✅	✅	❌	❌	✅	4
Differentially Private Post-Processing for Fair Regression	✅	✅	✅	❌	❌	❌	✅	4
Differentially Private Representation Learning via Image Captioning	❌	✅	✅	❌	✅	❌	✅	4
Differentially Private Sum-Product Networks	✅	✅	✅	❌	❌	❌	✅	4
Differentially Private Synthetic Data via Foundation Model APIs 2: Text	✅	✅	✅	✅	✅	❌	✅	6
Differentially Private Worst-group Risk Minimization	✅	❌	❌	❌	❌	❌	❌	1
Differentially private exact recovery for stochastic block models	✅	❌	❌	❌	❌	❌	❌	1
Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation	❌	✅	✅	❌	❌	❌	✅	3
Diffusion Language Models Are Versatile Protein Learners	✅	❌	✅	❌	❌	❌	✅	3
Diffusion Model-Augmented Behavioral Cloning	✅	❌	✅	❌	✅	❌	✅	4
Diffusion Models Demand Contrastive Guidance for Adversarial Purification to Advance	✅	✅	✅	✅	❌	❌	✅	5
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds	✅	✅	✅	❌	✅	❌	✅	5
Diffusion Posterior Sampling is Computationally Intractable	✅	❌	❌	❌	❌	❌	❌	1
Diffusion Rejection Sampling	✅	✅	✅	❌	✅	✅	✅	6
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations	✅	✅	❌	❌	✅	❌	✅	4
Diffusion-based Missing-view Generation With the Application on Incomplete Multi-view Clustering	✅	✅	✅	❌	❌	❌	✅	4
Diffusive Gibbs Sampling	✅	✅	✅	❌	❌	❌	✅	4
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency	✅	✅	✅	✅	✅	❌	✅	6
Directly Denoising Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Dirichlet Flow Matching with Applications to DNA Sequence Design	✅	✅	✅	✅	✅	❌	✅	6
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents	✅	✅	✅	✅	✅	❌	✅	6
Discounted Adaptive Online Learning: Towards Better Regularization	✅	✅	✅	❌	❌	❌	✅	4
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach	✅	❌	✅	✅	✅	❌	✅	5
Discovering Environments with XRM	✅	✅	✅	✅	✅	❌	✅	6
Discovering Features with Synergistic Interactions in Multiple Views	✅	✅	✅	✅	❌	❌	✅	5
Discovering Mixtures of Structural Causal Models from Time Series Data	❌	✅	✅	✅	❌	❌	✅	4
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution	❌	✅	✅	✅	❌	❌	✅	4
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution	✅	✅	✅	✅	✅	❌	✅	6
Discrete Latent Perspective Learning for Segmentation and Detection	❌	❌	✅	✅	❌	❌	✅	3
Disentangled 3D Scene Generation with Layout Learning	✅	❌	❌	❌	❌	❌	✅	2
Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet	✅	❌	✅	✅	✅	✅	✅	6
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization	❌	❌	✅	✅	❌	❌	✅	3
Disentanglement Learning via Topology	✅	✅	✅	❌	❌	❌	✅	4
Disguised Copyright Infringement of Latent Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Disparate Impact on Group Accuracy of Linearization for Private Inference	✅	✅	✅	❌	✅	❌	✅	5
Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion	✅	✅	✅	✅	✅	❌	✅	6
DistiLLM: Towards Streamlined Distillation for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control	❌	✅	✅	❌	❌	❌	✅	3
Distinguishing the Knowable from the Unknowable with Language Models	❌	✅	✅	✅	✅	✅	✅	6
Distributed Bilevel Optimization with Communication Compression	✅	❌	✅	❌	❌	❌	✅	3
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery	✅	✅	✅	✅	❌	❌	✅	5
Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification	✅	❌	✅	❌	✅	❌	✅	4
Distributional Bellman Operators over Mean Embeddings	✅	✅	✅	❌	✅	❌	✅	5
Distributionally Robust Data Valuation	❌	✅	✅	✅	✅	❌	✅	5
Ditto: Quantization-aware Secure Inference of Transformers upon MPC	✅	✅	✅	❌	✅	❌	✅	5
Diversified Batch Selection for Training Acceleration	✅	✅	✅	❌	❌	❌	✅	4
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset	❌	✅	✅	✅	✅	❌	✅	5
Do Efficient Transformers Really Save Computation?	❌	❌	❌	❌	✅	❌	✅	2
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?	❌	✅	❌	❌	❌	❌	✅	2
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates	❌	❌	✅	❌	❌	❌	✅	2
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function	❌	❌	✅	❌	❌	❌	✅	2
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations	❌	✅	✅	❌	❌	❌	✅	3
Do Topological Characteristics Help in Knowledge Distillation?	✅	✅	✅	✅	✅	❌	✅	6
Do Transformer World Models Give Better Policy Gradients?	✅	✅	✅	❌	❌	❌	✅	4
DoRA: Weight-Decomposed Low-Rank Adaptation	❌	✅	✅	❌	❌	❌	✅	3
Does Label Smoothing Help Deep Partial Label Learning?	✅	✅	✅	❌	❌	❌	✅	4
Domain Generalisation via Imprecise Learning	✅	✅	✅	✅	❌	❌	✅	5
Domain-wise Data Acquisition to Improve Performance under Distribution Shift	✅	✅	✅	❌	❌	❌	✅	4
Don’t Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget	❌	✅	✅	❌	❌	❌	❌	2
Don’t be so Negative! Score-based Generative Modeling with Oracle-assisted Guidance	✅	✅	✅	✅	✅	❌	✅	6
Don’t trust your eyes: on the (un)reliability of feature visualizations	❌	✅	✅	✅	❌	✅	✅	5
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)	❌	✅	✅	✅	✅	❌	✅	5
Double Momentum Method for Lower-Level Constrained Bilevel Optimization	✅	❌	✅	❌	✅	❌	✅	4
Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods	✅	❌	✅	❌	❌	❌	✅	3
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient	✅	❌	✅	❌	❌	❌	✅	3
Double-Step Alternating Extragradient with Increasing Timescale Separation for Finding Local Minimax Points: Provable Improvements	✅	❌	❌	❌	❌	❌	✅	2
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning	❌	✅	✅	❌	✅	❌	✅	4
Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming	✅	❌	✅	❌	✅	❌	✅	4
Drug Discovery with Dynamic Goal-aware Fragments	✅	✅	✅	✅	❌	❌	✅	5
DsDm: Model-Aware Dataset Selection with Datamodels	❌	❌	✅	✅	✅	❌	✅	4
Dual Operating Modes of In-Context Learning	❌	✅	✅	❌	✅	❌	✅	4
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems	❌	✅	✅	✅	✅	❌	✅	5
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems	✅	✅	✅	❌	❌	❌	✅	4
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization	✅	✅	❌	❌	❌	❌	✅	3
Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers	✅	❌	✅	❌	✅	❌	✅	4
Dynamic Correlation Clustering in Sublinear Update Time	✅	✅	✅	❌	❌	✅	✅	5
Dynamic Evaluation of Large Language Models by Meta Probing Agents	❌	✅	✅	❌	❌	❌	✅	3
Dynamic Facility Location in High Dimensional Euclidean Spaces	✅	❌	✅	❌	✅	❌	✅	4
Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Metric Embedding into lp Space	✅	❌	✅	❌	❌	❌	✅	3
Dynamic Spectral Clustering with Provable Approximation Guarantee	✅	✅	✅	❌	✅	❌	✅	5
Dynamic Survival Analysis with Controlled Latent States	❌	✅	✅	✅	❌	❌	✅	4
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving	❌	✅	✅	❌	✅	❌	✅	4
E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation	✅	❌	✅	✅	✅	❌	✅	5
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty	✅	✅	✅	❌	✅	❌	✅	5
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance	✅	✅	✅	✅	✅	❌	✅	6
EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization	✅	❌	✅	❌	✅	✅	✅	5
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism	❌	✅	✅	❌	✅	❌	✅	4
ELF: Encoding Speaker-Specific Latent Speech Feature for Speech Synthesis	❌	❌	✅	❌	✅	❌	✅	3
ELTA: An Enhancer against Long-Tail for Aesthetics-oriented Models	❌	✅	✅	✅	❌	❌	✅	4
EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence	✅	✅	✅	❌	✅	❌	✅	5
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers	✅	❌	✅	✅	✅	❌	✅	5
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling	❌	✅	✅	✅	✅	❌	✅	5
ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection	❌	✅	✅	❌	✅	❌	✅	4
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections	❌	✅	✅	✅	✅	❌	✅	5
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens	❌	❌	✅	✅	✅	❌	✅	4
Early Time Classification with Accumulated Accuracy Gap Control	✅	✅	✅	✅	❌	❌	✅	5
Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring	✅	❌	❌	❌	❌	✅	✅	3
Editing Partially Observable Networks via Graph Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Effective Federated Graph Matching	❌	❌	✅	❌	✅	✅	✅	4
Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing	✅	✅	✅	❌	✅	❌	✅	5
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning	✅	❌	❌	❌	❌	❌	✅	2
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond	✅	❌	✅	❌	❌	❌	✅	3
Efficient Algorithms for Sum-Of-Minimum Optimization	✅	✅	❌	❌	❌	❌	✅	3
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior	✅	✅	✅	❌	✅	❌	✅	5
Efficient Contextual Bandits with Uninformed Feedback Graphs	✅	❌	✅	❌	❌	❌	✅	3
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs	❌	✅	✅	✅	✅	❌	✅	5
Efficient Denoising Diffusion via Probabilistic Masking	✅	❌	✅	❌	✅	❌	✅	4
Efficient Error Certification for Physics-Informed Neural Networks	✅	❌	❌	❌	✅	❌	❌	2
Efficient Exploration for LLMs	✅	❌	✅	❌	❌	❌	✅	3
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling	✅	✅	✅	❌	❌	❌	✅	4
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits	✅	✅	✅	❌	✅	❌	✅	5
Efficient Mixture Learning in Black-Box Variational Inference	❌	✅	✅	❌	✅	❌	✅	4
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation	✅	❌	✅	✅	✅	❌	✅	5
Efficient Online Set-valued Classification with Bandit Feedback	✅	❌	✅	✅	❌	❌	✅	4
Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks	❌	✅	✅	❌	✅	❌	✅	4
Efficient Pareto Manifold Learning with Low-Rank Structure	✅	❌	✅	✅	❌	❌	✅	4
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design	✅	✅	❌	❌	❌	❌	✅	3
Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling	❌	✅	✅	❌	✅	❌	✅	4
Efficient Stochastic Approximation of Minimax Excess Risk Optimization	✅	❌	✅	❌	❌	❌	❌	2
Efficient Value Iteration for s-rectangular Robust Markov Decision Processes	✅	❌	❌	❌	✅	❌	✅	3
Efficient World Models with Context-Aware Tokenization	❌	✅	✅	❌	✅	❌	✅	4
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data	❌	❌	✅	❌	✅	❌	✅	3
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time	✅	✅	✅	✅	✅	❌	✅	6
Eluder-based Regret for Stochastic Contextual MDPs	✅	❌	❌	❌	❌	❌	❌	1
Embarrassingly Parallel GFlowNets	✅	✅	❌	❌	✅	❌	✅	4
Embodied CoT Distillation From LLM To Off-the-shelf Agents	✅	❌	✅	❌	✅	✅	✅	5
Emergence of In-Context Reinforcement Learning from Noise Distillation	✅	✅	❌	✅	❌	❌	✅	4
Emergent Equivariance in Deep Ensembles	❌	❌	✅	✅	❌	❌	✅	3
Emergent Representations of Program Semantics in Language Models Trained on Programs	❌	✅	❌	❌	✅	❌	✅	3
Empowering Graph Invariance Learning with Deep Spurious Infomax	✅	✅	✅	✅	✅	✅	✅	7
Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer	✅	✅	✅	✅	❌	❌	✅	5
Enabling Uncertainty Estimation in Iterative Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Encodings for Prediction-based Neural Architecture Search	❌	✅	✅	❌	❌	❌	✅	3
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations	✅	❌	❌	✅	✅	❌	✅	4
Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic	✅	✅	✅	✅	✅	❌	✅	6
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining	❌	✅	✅	❌	❌	❌	✅	3
Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem	✅	✅	✅	✅	✅	❌	✅	6
Enhancing Adversarial Robustness in SNNs with Sparse Gradients	✅	✅	✅	❌	❌	❌	✅	4
Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation	✅	✅	✅	✅	❌	❌	✅	5
Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation	✅	❌	✅	❌	✅	❌	✅	4
Enhancing Implicit Shape Generators Using Topological Regularizations	❌	❌	✅	❌	❌	❌	❌	1
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning	❌	✅	✅	✅	❌	❌	✅	4
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models	✅	✅	✅	❌	✅	❌	✅	5
Enhancing Sufficient Dimension Reduction via Hellinger Correlation	❌	✅	✅	❌	❌	❌	✅	3
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction	❌	❌	✅	❌	✅	❌	✅	3
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning	✅	❌	✅	✅	❌	❌	✅	4
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module	❌	❌	✅	✅	❌	❌	❌	2
Ensemble Pruning for Out-of-distribution Generalization	❌	✅	✅	✅	❌	❌	✅	4
Entropy-Reinforced Planning with Large Language Models for Drug Discovery	✅	✅	✅	❌	✅	❌	✅	5
Environment Design for Inverse Reinforcement Learning	✅	✅	❌	❌	✅	❌	✅	4
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection	✅	✅	✅	✅	✅	✅	✅	7
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction	✅	✅	✅	✅	✅	❌	✅	6
Equilibrium of Data Markets with Externality	✅	❌	❌	❌	❌	❌	✅	2
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency	✅	✅	✅	✅	✅	❌	✅	6
Equivariant Deep Weight Space Alignment	❌	✅	✅	✅	✅	❌	✅	5
Equivariant Diffusion for Crystal Structure Prediction	✅	✅	✅	✅	✅	❌	✅	6
Equivariant Frames and the Impossibility of Continuous Canonicalization	❌	✅	✅	❌	❌	❌	✅	3
Equivariant Graph Neural Operator for Modeling 3D Dynamics	❌	✅	✅	✅	❌	❌	✅	4
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
Error Feedback Can Accurately Compress Preconditioners	✅	✅	✅	❌	✅	❌	✅	5
Estimating Barycenters of Distributions with Neural Optimal Transport	✅	✅	✅	❌	❌	❌	✅	4
Estimating Canopy Height at Scale	❌	✅	✅	✅	✅	❌	✅	5
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction	✅	✅	✅	❌	✅	✅	❌	5
Estimating Unknown Population Sizes Using the Hypergeometric Distribution	✅	❌	✅	❌	❌	❌	✅	3
Estimating the Permanent by Nesting Importance Sampling	✅	✅	✅	❌	❌	❌	✅	4
Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples	✅	✅	✅	❌	✅	❌	✅	5
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems	❌	✅	✅	❌	✅	❌	✅	4
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting	❌	✅	✅	❌	✅	❌	✅	4
EvIL: Evolution Strategies for Generalisable Imitation Learning	✅	❌	✅	❌	❌	❌	✅	3
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution	❌	✅	✅	✅	✅	❌	✅	5
Evaluating Model Bias Requires Characterizing its Mistakes	✅	❌	✅	❌	❌	❌	❌	2
Evaluating Quantized Large Language Models	❌	✅	✅	✅	❌	❌	✅	4
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models	❌	❌	✅	❌	✅	❌	✅	3
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks	❌	✅	✅	❌	❌	❌	✅	3
Evaluation of Test-Time Adaptation Under Computational Time Constraints	❌	✅	✅	✅	❌	❌	✅	4
Evaluation of Trajectory Distribution Predictions with Energy Score	❌	✅	✅	❌	❌	❌	✅	3
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search	❌	✅	✅	❌	❌	❌	✅	3
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs	✅	✅	✅	❌	✅	❌	✅	5
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model	❌	✅	✅	✅	✅	✅	✅	6
Evolution-Inspired Loss Functions for Protein Representation Learning	❌	❌	✅	❌	✅	❌	✅	3
Evolving Subnetwork Training for Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking	✅	✅	✅	❌	❌	❌	✅	4
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers	✅	❌	❌	❌	❌	❌	❌	1
Exact Soft Analytical Side-Channel Attacks using Tractable Circuits	✅	✅	❌	✅	✅	❌	✅	5
Executable Code Actions Elicit Better LLM Agents	❌	✅	✅	❌	✅	❌	✅	4
Expand-and-Cluster: Parameter Recovery of Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning	✅	✅	✅	❌	✅	❌	✅	5
Experts Don’t Cheat: Learning What You Don’t Know By Predicting Pairs	✅	❌	✅	✅	❌	❌	✅	4
Explain Temporal Black-Box Models via Functional Decomposition	❌	❌	✅	✅	❌	❌	✅	3
Explaining Graph Neural Networks via Structure-aware Interaction Index	✅	✅	✅	✅	❌	✅	✅	6
Explaining Probabilistic Models with Distributional Values	❌	✅	✅	❌	✅	❌	✅	4
Exploiting Code Symmetries for Learning Program Semantics	❌	❌	✅	❌	✅	❌	✅	3
Exploiting Human-AI Dependence for Learning to Defer	❌	❌	✅	✅	✅	❌	✅	4
Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics	✅	❌	✅	❌	✅	✅	✅	5
Exploration and Anti-Exploration with Distributional Random Network Distillation	✅	✅	✅	❌	✅	✅	✅	6
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring	✅	❌	❌	❌	❌	❌	❌	1
Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization	✅	❌	❌	❌	❌	❌	✅	2
Explorations of Self-Repair in Language Models	❌	✅	✅	❌	❌	❌	❌	2
Exploring Correlations of Self-Supervised Tasks for Graphs	❌	✅	✅	✅	❌	❌	✅	4
Exploring Intrinsic Dimension for Vision-Language Model Pruning	✅	✅	✅	✅	✅	❌	✅	6
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters	❌	✅	✅	❌	❌	❌	✅	3
Exploring the Benefit of Activation Sparsity in Pre-training	❌	✅	✅	✅	✅	❌	✅	5
Exploring the Complexity of Deep Neural Networks through Functional Equivalence	❌	❌	❌	❌	❌	❌	❌	0
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold	❌	❌	✅	✅	✅	❌	✅	4
Exploring the LLM Journey from Cognition to Expression with Linear Representations	✅	❌	✅	✅	❌	❌	✅	4
Exploring the Low-Pass Filtering Behavior in Image Super-Resolution	❌	✅	✅	✅	❌	❌	✅	4
Exponential Spectral Pursuit: An Effective Initialization Method for Sparse Phase Retrieval	✅	❌	❌	❌	❌	❌	✅	2
Expressivity and Generalization: Fragment-Biases for Molecular GNNs	❌	✅	✅	❌	❌	❌	✅	3
Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems	❌	✅	✅	✅	✅	❌	✅	5
Extracting Training Data From Document-Based VQA Models	❌	❌	✅	✅	✅	❌	✅	4
Extreme Compression of Large Language Models via Additive Quantization	✅	✅	✅	✅	✅	❌	✅	6
FADAS: Towards Federated Adaptive Asynchronous Optimization	✅	✅	✅	✅	❌	❌	✅	5
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames	✅	✅	✅	❌	❌	✅	✅	5
FESSNC: Fast Exponentially Stable and Safe Neural Controller	✅	✅	❌	❌	✅	❌	✅	4
FRAG: Frequency Adapting Group for Diffusion Video Editing	✅	❌	✅	❌	✅	❌	✅	4
FRAPPÉ: A Group Fairness Framework for Post-Processing Everything	❌	✅	✅	✅	✅	❌	✅	5
Factored-Reward Bandits with Intermediate Observations	✅	✅	❌	❌	❌	❌	✅	3
Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models	✅	✅	✅	❌	✅	❌	✅	5
Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach	✅	✅	✅	❌	❌	❌	✅	4
Fair Federated Learning via the Proportional Veto Core	✅	❌	✅	❌	❌	❌	✅	3
Fair Off-Policy Learning from Observational Data	✅	✅	✅	✅	❌	❌	✅	5
Fair Resource Allocation in Multi-Task Learning	✅	✅	✅	✅	❌	❌	✅	5
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks	✅	✅	✅	✅	✅	✅	✅	7
FairProof : Confidential and Certifiable Fairness for Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
Faithfulness Measurable Masked Language Models	✅	✅	✅	✅	✅	❌	✅	6
Fast Adversarial Attacks on Language Models In One GPU Minute	✅	✅	✅	✅	✅	❌	✅	6
Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
Fast Co-Training under Weak Dependence via Stream-Based Active Learning	✅	❌	❌	❌	❌	❌	❌	1
Fast Decision Boundary based Out-of-Distribution Detector	❌	✅	✅	✅	✅	❌	✅	5
Fast Peer Adaptation with Context-aware Exploration	✅	✅	❌	❌	✅	❌	✅	4
Fast Sampling-Based Sketches for Tensors	❌	✅	❌	❌	❌	❌	✅	2
Fast Text-to-3D-Aware Face Generation and Manipulation via Direct Cross-modal Mapping and Geometric Regularization	❌	✅	✅	❌	✅	❌	✅	4
Fast Timing-Conditioned Latent Audio Diffusion	❌	✅	✅	❌	✅	❌	✅	4
Fast White-Box Adversarial Streaming Without a Random Oracle	✅	❌	❌	❌	❌	❌	❌	1
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits	✅	❌	✅	❌	❌	❌	✅	3
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching	✅	✅	✅	✅	✅	❌	✅	6
Fast-Slow Test-Time Adaptation for Online Vision-and-Language Navigation	❌	✅	✅	✅	✅	✅	✅	6
Faster Adaptive Decentralized Learning Algorithms	✅	❌	✅	❌	❌	❌	✅	3
Faster Maximum Inner Product Search in High Dimensions	✅	✅	✅	❌	✅	❌	✅	5
Faster Sampling via Stochastic Gradient Proximal Sampler	✅	❌	✅	❌	❌	❌	✅	3
Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs	✅	❌	✅	❌	✅	❌	✅	4
Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training	✅	✅	✅	❌	✅	❌	✅	5
Feasibility Consistent Representation Learning for Safe Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Feasible Reachable Policy Iteration	✅	❌	✅	❌	✅	❌	✅	4
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation	❌	✅	✅	❌	❌	❌	✅	3
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize	❌	✅	✅	✅	❌	❌	✅	4
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective	❌	❌	✅	✅	❌	❌	✅	3
Feature Importance Disparities for Data Bias Investigations	✅	✅	✅	❌	✅	❌	✅	5
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models	❌	✅	✅	✅	❌	❌	✅	4
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization	✅	❌	✅	❌	✅	❌	✅	4
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler	✅	❌	✅	✅	✅	❌	✅	5
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees	✅	✅	✅	✅	✅	✅	✅	7
FedMBridge: Bridgeable Multimodal Federated Learning	✅	❌	✅	❌	✅	✅	✅	5
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering	✅	✅	✅	✅	✅	❌	✅	6
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error	✅	✅	✅	❌	❌	❌	✅	4
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data	✅	❌	✅	✅	❌	❌	✅	4
Federated Combinatorial Multi-Agent Multi-Armed Bandits	✅	❌	✅	❌	❌	❌	✅	3
Federated Continual Learning via Prompt-based Dual Knowledge Transfer	✅	✅	✅	✅	✅	❌	✅	6
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes	✅	✅	✅	✅	✅	✅	✅	7
Federated Neuro-Symbolic Learning	✅	❌	✅	❌	❌	❌	✅	3
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices	✅	❌	❌	❌	❌	❌	❌	1
Federated Optimization with Doubly Regularized Drift Correction	✅	❌	✅	❌	❌	❌	✅	3
Federated Representation Learning in the Under-Parameterized Regime	✅	✅	✅	❌	❌	❌	✅	4
Federated Self-Explaining GNNs with Anti-shortcut Augmentations	✅	✅	✅	✅	✅	❌	✅	6
Feedback Efficient Online Fine-Tuning of Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
Feedback Loops With Language Models Drive In-Context Reward Hacking	❌	❌	❌	❌	❌	✅	✅	2
Feel-Good Thompson Sampling for Contextual Dueling Bandits	✅	❌	❌	❌	❌	❌	✅	2
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind	❌	✅	✅	✅	✅	❌	✅	5
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries	✅	❌	✅	✅	✅	❌	✅	5
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings	❌	❌	✅	✅	❌	❌	✅	3
Fewer Truncations Improve Language Modeling	✅	❌	✅	✅	✅	✅	✅	6
FiT: Flexible Vision Transformer for Diffusion Model	❌	✅	✅	❌	❌	❌	✅	3
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning	✅	✅	❌	❌	✅	❌	✅	4
Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks	❌	❌	✅	✅	✅	❌	✅	4
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Fine-grained Classes and How to Find Them	✅	✅	✅	✅	✅	✅	✅	7
Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention	❌	✅	✅	❌	❌	❌	✅	3
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem	✅	✅	✅	❌	✅	❌	✅	5
Finite Smoothing Algorithm for High-Dimensional Support Vector Machines and Quantile Regression	✅	✅	✅	❌	❌	❌	✅	4
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation	✅	❌	✅	❌	❌	❌	✅	3
Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation	✅	✅	✅	✅	✅	❌	✅	6
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
First-Order Manifold Data Augmentation for Regression Learning	✅	✅	✅	✅	✅	❌	✅	6
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction	❌	✅	✅	✅	❌	❌	✅	4
Flexible Residual Binarization for Image Super-Resolution	✅	❌	✅	❌	✅	❌	✅	4
Flextron: Many-in-One Flexible Large Language Model	❌	❌	✅	❌	✅	❌	✅	3
Floating Anchor Diffusion Model for Multi-motif Scaffolding	❌	✅	✅	❌	✅	❌	✅	4
Flora: Low-Rank Adapters Are Secretly Gradient Compressors	✅	✅	✅	✅	❌	❌	✅	5
FlowMM: Generating Materials with Riemannian Flow Matching	❌	✅	✅	✅	❌	❌	✅	4
Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations	❌	✅	✅	✅	✅	❌	✅	5
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics	✅	✅	✅	✅	❌	❌	✅	5
Foundation Policies with Hilbert Representations	✅	✅	✅	❌	✅	❌	✅	5
Foundations of Testing for Finite-Sample Causal Discovery	✅	❌	❌	❌	❌	❌	✅	2
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning	✅	✅	✅	✅	✅	✅	✅	7
FrameQuant: Flexible Low-Bit Quantization for Transformers	✅	✅	✅	✅	✅	❌	✅	6
FreeBind: Free Lunch in Unified Multimodal Space via Knowledge Fusion	❌	✅	✅	❌	✅	❌	✅	4
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions	✅	✅	✅	✅	✅	✅	✅	7
From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble	❌	✅	✅	✅	✅	❌	✅	5
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems	✅	❌	✅	✅	✅	❌	✅	5
From Generalization Analysis to Optimization Designs for State Space Models	✅	❌	✅	✅	✅	❌	✅	5
From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks	✅	❌	✅	✅	✅	✅	✅	6
From Inverse Optimization to Feasibility to ERM	✅	✅	✅	✅	❌	❌	✅	5
From Neurons to Neutrons: A Case Study in Interpretability	❌	✅	✅	✅	✅	❌	✅	5
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers	❌	❌	❌	❌	❌	❌	✅	1
From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation	❌	❌	✅	❌	✅	❌	✅	3
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems	✅	❌	❌	❌	❌	❌	❌	1
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning	✅	❌	✅	❌	❌	❌	✅	3
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning	✅	✅	✅	✅	✅	✅	✅	7
Full-Atom Peptide Design based on Multi-modal Flow Matching	✅	✅	✅	❌	✅	❌	✅	5
Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees	✅	❌	❌	❌	❌	❌	❌	1
Fundamental Benefit of Alternating Updates in Minimax Optimization	✅	✅	✅	❌	❌	❌	✅	4
Fundamental Limitations of Alignment in Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints	❌	❌	❌	❌	❌	❌	❌	0
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting	❌	✅	❌	❌	✅	❌	✅	3
GATE: How to Keep Out Intrusive Neighbors	❌	✅	✅	✅	❌	❌	✅	4
GFlowNet Training by Policy Gradients	✅	✅	✅	❌	❌	❌	✅	4
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements	❌	❌	✅	❌	✅	❌	✅	3
GNNs Also Deserve Editing, and They Need It More Than Once	✅	✅	✅	✅	❌	❌	✅	5
GPT-4V(ision) is a Generalist Web Agent, if Grounded	❌	✅	✅	❌	❌	❌	✅	3
GPTSwarm: Language Agents as Optimizable Graphs	✅	✅	✅	✅	❌	❌	✅	5
GRATH: Gradual Self-Truthifying for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection	✅	❌	✅	✅	✅	❌	✅	5
Gambling-Based Confidence Sequences for Bounded Random Vectors	❌	✅	❌	❌	❌	❌	✅	2
Gated Linear Attention Transformers with Hardware-Efficient Training	✅	✅	✅	❌	✅	❌	✅	5
Gaussian Plane-Wave Neural Operator for Electron Density Estimation	❌	✅	✅	✅	❌	❌	✅	4
Gaussian Processes on Cellular Complexes	❌	❌	✅	❌	✅	❌	✅	3
GaussianPro: 3D Gaussian Splatting with Progressive Propagation	❌	✅	✅	❌	✅	❌	✅	4
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer	❌	✅	✅	✅	✅	❌	✅	5
GenCO: Generating Diverse Designs with Combinatorial Constraints	✅	❌	✅	❌	❌	❌	✅	3
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning	❌	✅	✅	✅	✅	❌	✅	5
Generalization Analysis for Multi-Label Learning	❌	❌	❌	❌	❌	❌	❌	0
Generalization Analysis of Deep Non-linear Matrix Completion	❌	❌	✅	✅	✅	✅	✅	5
Generalization Analysis of Stochastic Weight Averaging with General Sampling	❌	❌	✅	❌	❌	❌	✅	2
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack	✅	✅	✅	❌	✅	❌	✅	5
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis	❌	✅	✅	❌	✅	❌	❌	3
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation	❌	✅	✅	❌	❌	❌	✅	3
Generalization Error of Graph Neural Networks in the Mean-field Regime	❌	✅	✅	✅	✅	❌	✅	5
Generalization in Kernel Regression Under Realistic Assumptions	❌	❌	❌	❌	❌	❌	❌	0
Generalization to New Sequential Decision Making Tasks with In-Context Learning	❌	❌	✅	✅	✅	❌	✅	4
Generalized Neural Collapse for a Large Number of Classes	❌	❌	✅	❌	✅	❌	✅	3
Generalized Preference Optimization: A Unified Approach to Offline Alignment	❌	❌	✅	❌	❌	❌	✅	2
Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes	✅	❌	❌	❌	❌	❌	✅	2
Generalized Sobolev Transport for Probability Measures on a Graph	❌	✅	✅	✅	❌	❌	✅	4
Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization	❌	✅	✅	✅	❌	❌	✅	4
Generalizing Orthogonalization for Models with Non-Linearities	❌	✅	✅	✅	❌	❌	✅	4
Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought	✅	❌	✅	❌	❌	❌	✅	3
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
Generative Active Learning for Long-tailed Instance Segmentation	✅	❌	✅	✅	✅	✅	✅	6
Generative Conditional Distributions by Neural (Entropic) Optimal Transport	✅	✅	✅	✅	❌	❌	✅	5
Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates	❌	✅	✅	✅	✅	❌	✅	5
Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design	✅	✅	✅	❌	✅	❌	✅	5
Generative Marginalization Models	✅	✅	✅	✅	✅	❌	✅	6
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes	✅	✅	✅	✅	✅	❌	✅	6
Genie: Generative Interactive Environments	❌	❌	✅	❌	✅	❌	✅	3
GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation	❌	✅	✅	✅	❌	❌	✅	4
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model	❌	✅	✅	❌	✅	✅	✅	5
Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction	✅	❌	❌	❌	❌	❌	✅	2
Geometry-Aware Instrumental Variable Regression	✅	✅	❌	❌	❌	❌	✅	3
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications	❌	❌	✅	✅	❌	❌	✅	3
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference	✅	✅	✅	❌	✅	❌	✅	5
Getting the most out of your tokenizer for pre-training and domain adaptation	❌	❌	✅	❌	❌	❌	✅	2
GiLOT: Interpreting Generative Language Models via Optimal Transport	❌	✅	✅	❌	❌	❌	✅	3
Gibbs Sampling of Continuous Potentials on a Quantum Computer	✅	❌	❌	❌	❌	❌	❌	1
GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks	❌	✅	✅	✅	✅	✅	✅	6
GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding	✅	✅	✅	❌	✅	❌	✅	5
Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods	✅	❌	❌	❌	❌	❌	✅	2
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations	❌	✅	✅	❌	✅	❌	✅	4
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization	✅	✅	✅	❌	❌	❌	✅	4
Gradient-based Visual Explanation for Transformer-based CLIP	❌	✅	✅	✅	❌	❌	✅	4
Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method	✅	✅	✅	✅	❌	❌	✅	5
Graph Adversarial Diffusion Convolution	✅	✅	✅	✅	✅	✅	✅	7
Graph As Point Set	❌	✅	✅	✅	✅	❌	✅	5
Graph Automorphism Group Equivariant Neural Networks	✅	❌	❌	❌	❌	❌	❌	1
Graph Distillation with Eigenbasis Matching	✅	✅	✅	✅	✅	❌	✅	6
Graph External Attention Enhanced Transformer	❌	✅	✅	✅	❌	❌	✅	4
Graph Generation with Diffusion Mixture	✅	✅	✅	✅	✅	❌	✅	6
Graph Geometry-Preserving Autoencoders	✅	✅	✅	❌	✅	❌	❌	4
Graph Mixup on Approximate Gromov–Wasserstein Geodesics	✅	✅	✅	✅	✅	❌	✅	6
Graph Neural Network Explanations are Fragile	✅	✅	✅	❌	✅	❌	✅	5
Graph Neural Networks Use Graphs When They Shouldn’t	❌	✅	✅	✅	❌	❌	✅	4
Graph Neural Networks with a Distribution of Parametrized Graphs	✅	✅	✅	✅	✅	❌	✅	6
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance	❌	✅	❌	✅	✅	✅	✅	5
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification	✅	❌	✅	✅	✅	✅	✅	6
Graph Out-of-Distribution Detection Goes Neighborhood Shaping	❌	❌	✅	✅	✅	✅	✅	5
Graph Positional and Structural Encoder	❌	✅	✅	✅	✅	❌	✅	5
Graph Structure Extrapolation for Out-of-Distribution Generalization	❌	❌	✅	✅	✅	❌	✅	4
Graph-Triggered Rising Bandits	✅	❌	❌	❌	❌	❌	✅	2
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling	❌	✅	✅	✅	✅	❌	✅	5
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting	❌	✅	✅	✅	✅	❌	✅	5
Graph-enhanced Large Language Models in Asynchronous Plan Reasoning	❌	✅	✅	❌	✅	❌	✅	4
Graph2Tac: Online Representation Learning of Formal Math Concepts	❌	✅	✅	❌	✅	❌	✅	4
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm	✅	❌	❌	❌	✅	❌	❌	2
Grokking Group Multiplication with Cosets	❌	✅	❌	✅	✅	✅	✅	5
GroupCover: A Secure, Efficient and Scalable Inference Framework for On-device Model Protection based on TEEs	✅	✅	✅	❌	✅	❌	✅	5
Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples	❌	❌	❌	❌	❌	❌	✅	1
Guidance with Spherical Gaussian Constraint for Conditional Diffusion	✅	✅	✅	❌	❌	❌	✅	4
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation	✅	✅	✅	✅	✅	❌	✅	6
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding	✅	✅	✅	✅	❌	❌	✅	5
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations	❌	❌	✅	❌	✅	❌	✅	3
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network	❌	❌	✅	❌	❌	❌	✅	2
HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming	❌	✅	❌	❌	✅	✅	✅	4
Handling Heterogeneous Curvatures in Bandit LQR Control	✅	❌	❌	❌	❌	❌	❌	1
Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling	✅	❌	✅	❌	❌	❌	✅	3
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal	✅	✅	✅	✅	✅	❌	✅	6
HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design	✅	✅	✅	✅	✅	❌	✅	6
Harmonizing Generalization and Personalization in Federated Prompt Learning	✅	❌	✅	✅	✅	❌	✅	5
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis	❌	✅	✅	❌	❌	❌	✅	3
HarmonyDream: Task Harmonization Inside World Models	❌	✅	✅	✅	❌	❌	✅	4
Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition	✅	✅	✅	✅	❌	❌	✅	5
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning	✅	❌	✅	✅	✅	❌	✅	5
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws	❌	✅	✅	✅	✅	❌	✅	5
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction	❌	✅	✅	✅	✅	❌	✅	5
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions	✅	✅	✅	✅	✅	❌	✅	6
HexGen: Generative Inference of Large Language Model over Heterogeneous Environment	✅	✅	✅	❌	✅	❌	✅	5
Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks	✅	✅	❌	❌	❌	❌	✅	3
Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity	✅	✅	❌	❌	✅	❌	❌	3
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution	❌	❌	✅	✅	✅	❌	✅	4
Hierarchical Novelty Detection via Fine-Grained Evidence Allocation	✅	✅	✅	✅	✅	✅	✅	7
Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling	❌	✅	✅	✅	❌	❌	✅	4
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models	❌	✅	✅	❌	✅	❌	✅	4
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling	✅	✅	✅	✅	❌	❌	✅	5
High-Dimensional Geometric Streaming for Nearly Low Rank Data	✅	❌	✅	❌	❌	❌	✅	3
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization	❌	❌	❌	❌	❌	❌	✅	1
High-Order Contrastive Learning with Fine-grained Comparative Levels for Sparse Ordinal Tensor Completion	✅	✅	✅	✅	❌	❌	✅	5
High-Performance Temporal Reversible Spiking Neural Networks with $\mathcalO(L)$ Training Memory and $\mathcalO(1)$ Inference Cost	❌	✅	✅	❌	✅	❌	✅	4
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails	✅	❌	✅	✅	❌	❌	✅	4
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise	✅	❌	❌	❌	❌	❌	✅	2
High-dimensional Linear Bandits with Knapsacks	✅	❌	❌	❌	❌	❌	✅	2
Highway Value Iteration Networks	❌	✅	✅	✅	✅	❌	✅	5
Homomorphism Counts for Graph Neural Networks: All About That Basis	❌	✅	✅	✅	✅	❌	✅	5
How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective	✅	✅	✅	❌	✅	❌	✅	5
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model	❌	✅	✅	❌	❌	❌	✅	3
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?	✅	❌	❌	❌	❌	❌	✅	2
How Does Goal Relabeling Improve Sample Efficiency?	✅	❌	❌	❌	❌	❌	❌	1
How Far Can Fairness Constraints Help Recover From Biased Data?	❌	❌	❌	❌	❌	❌	❌	0
How Flawed Is ECE? An Analysis via Logit Smoothing	✅	✅	✅	❌	❌	❌	✅	4
How Free is Parameter-Free Stochastic Optimization?	✅	❌	❌	❌	❌	❌	❌	1
How Graph Neural Networks Learn: Lessons from Training Dynamics	✅	✅	✅	✅	✅	❌	✅	6
How Interpretable Are Interpretable Graph Neural Networks?	✅	✅	✅	✅	✅	✅	✅	7
How Language Model Hallucinations Can Snowball	❌	✅	✅	❌	❌	❌	✅	3
How Learning by Reconstruction Produces Uninformative Features For Perception	❌	✅	✅	❌	❌	❌	❌	2
How Private are DP-SGD Implementations?	✅	✅	❌	❌	❌	❌	✅	3
How Smooth Is Attention?	❌	❌	✅	❌	❌	❌	✅	2
How Spurious Features are Memorized: Precise Analysis for Random and NTK Features	❌	✅	✅	❌	❌	❌	❌	2
How Transformers Learn Causal Structure with Gradient Descent	✅	✅	❌	❌	✅	❌	✅	4
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers	✅	❌	✅	❌	❌	❌	❌	2
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing	✅	✅	✅	✅	✅	❌	✅	6
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis	❌	✅	❌	❌	❌	❌	✅	2
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?	❌	❌	❌	❌	❌	❌	✅	1
How do Transformers Perform In-Context Autoregressive Learning ?	❌	✅	✅	❌	❌	❌	✅	3
How to Escape Sharp Minima with Random Perturbations	✅	❌	✅	❌	❌	❌	✅	3
How to Explore with Belief: State Entropy Maximization in POMDPs	✅	✅	❌	❌	❌	❌	✅	3
How to Leverage Diverse Demonstrations in Offline Imitation Learning	✅	✅	✅	❌	✅	✅	✅	6
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization	✅	✅	❌	❌	❌	❌	✅	3
How to Trace Latent Generative Model Generated Images without Artificial Watermark?	✅	✅	✅	❌	✅	✅	✅	6
Human Alignment of Large Language Models through Online Preference Optimisation	✅	❌	✅	✅	✅	❌	✅	5
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?	✅	❌	❌	❌	❌	❌	✅	2
Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
HumanTOMATO: Text-aligned Whole-body Motion Generation	✅	❌	✅	✅	✅	✅	✅	6
Hybrid Inverse Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Hybrid Neural Representations for Spherical Data	❌	❌	✅	✅	✅	❌	✅	4
Hybrid Reinforcement Learning from Offline Observation Alone	✅	❌	✅	❌	❌	❌	✅	3
Hybrid$^2$ Neural ODE Causal Modeling and an Application to Glycemic Response	✅	✅	✅	✅	❌	❌	✅	5
HyperFields: Towards Zero-Shot Generation of NeRFs from Text	✅	❌	❌	❌	❌	❌	✅	2
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift	❌	✅	✅	✅	✅	❌	✅	5
Hyperbolic Geometric Latent Diffusion Model for Graph Generation	✅	✅	✅	❌	✅	❌	✅	5
Hyperbolic Optimizer as a Dynamical System	❌	❌	❌	❌	❌	❌	❌	0
Hypergraph-enhanced Dual Semi-supervised Graph Classification	✅	❌	✅	✅	❌	❌	✅	4
I/O Complexity of Attention, or How Optimal is FlashAttention?	✅	❌	❌	❌	❌	❌	❌	1
IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency	✅	✅	✅	✅	✅	❌	✅	6
IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation	❌	✅	✅	✅	✅	❌	✅	5
ILILT: Implicit Learning of Inverse Lithography Technologies	❌	❌	✅	❌	❌	❌	✅	2
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation	❌	❌	✅	❌	✅	❌	✅	3
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers	✅	✅	✅	❌	✅	❌	✅	5
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer	❌	✅	✅	❌	✅	✅	✅	5
IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics	✅	✅	✅	❌	✅	❌	✅	5
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation	✅	❌	✅	✅	❌	❌	✅	4
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank	✅	✅	✅	✅	❌	❌	✅	5
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach	❌	❌	❌	❌	❌	❌	✅	1
Image Clustering with External Guidance	❌	✅	✅	❌	✅	❌	✅	4
Image Fusion via Vision-Language Model	❌	✅	✅	✅	✅	❌	✅	5
Image Hijacks: Adversarial Images can Control Generative Models at Runtime	❌	❌	✅	✅	✅	❌	✅	4
Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge	❌	✅	✅	✅	✅	❌	✅	5
Imitation Learning from Purified Demonstrations	✅	✅	✅	❌	❌	❌	✅	4
Imitation Learning in Discounted Linear MDPs without exploration assumptions	✅	❌	❌	❌	❌	❌	✅	2
Impact of Decentralized Learning on Player Utilities in Stackelberg Games	✅	❌	❌	❌	❌	❌	❌	1
Implicit Bias of AdamW: $\ell_∞$-Norm Constrained Optimization	✅	❌	✅	❌	✅	❌	✅	4
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States	❌	✅	❌	❌	✅	❌	✅	3
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD	❌	✅	✅	✅	✅	❌	✅	5
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks	❌	❌	✅	❌	✅	❌	✅	3
Implicit Representations for Constrained Image Segmentation	❌	✅	✅	❌	❌	✅	✅	4
Implicit Representations via Operator Learning	❌	✅	✅	❌	❌	❌	✅	3
Implicit meta-learning may lead language models to trust more reliable sources	❌	✅	✅	✅	✅	❌	✅	5
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy	✅	❌	❌	❌	❌	❌	❌	1
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy	✅	❌	✅	❌	❌	❌	✅	3
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements	✅	❌	❌	❌	❌	❌	❌	1
Improved Dimensionality Dependence for Zeroth-Order Optimisation over Cross-Polytopes	✅	❌	❌	❌	❌	❌	❌	1
Improved Generalization of Weight Space Networks via Augmentations	❌	✅	✅	✅	❌	❌	✅	4
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials	✅	✅	✅	✅	❌	❌	✅	5
Improved Operator Learning by Orthogonal Attention	❌	❌	✅	❌	✅	❌	✅	3
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm	✅	❌	❌	❌	❌	❌	✅	2
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training	✅	✅	✅	✅	✅	❌	✅	6
Improving Adversarial Energy-Based Model via Diffusion Process	❌	❌	✅	❌	❌	✅	✅	3
Improving Antibody Humanness Prediction using Patent Data	❌	✅	✅	✅	✅	✅	✅	6
Improving Computational Complexity in Statistical Models with Local Curvature Information	❌	❌	❌	❌	❌	❌	✅	1
Improving Context Understanding in Multimodal Large Language Models via Multimodal Composition Learning	❌	✅	✅	✅	✅	❌	✅	5
Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance	❌	✅	✅	❌	❌	❌	✅	3
Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning	❌	✅	✅	✅	❌	❌	✅	4
Improving Factuality and Reasoning in Language Models through Multiagent Debate	❌	✅	✅	❌	❌	❌	✅	3
Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting	✅	✅	✅	✅	❌	❌	❌	4
Improving Gradient-Guided Nested Sampling for Posterior Inference	✅	✅	❌	❌	❌	❌	✅	3
Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference	✅	✅	✅	✅	✅	❌	✅	6
Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation	❌	✅	✅	❌	❌	❌	✅	3
Improving Interpretation Faithfulness for Vision Transformers	✅	❌	✅	❌	❌	❌	✅	3
Improving Neural Additive Models with Bayesian Principles	❌	✅	✅	✅	✅	❌	✅	5
Improving Neural Logic Machines via Failure Reflection	✅	✅	✅	✅	✅	❌	✅	6
Improving Open-Ended Text Generation via Adaptive Decoding	✅	✅	✅	✅	✅	❌	✅	6
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining	✅	✅	✅	❌	❌	❌	✅	4
Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization	✅	❌	✅	❌	✅	❌	✅	4
Improving SAM Requires Rethinking its Optimization Formulation	✅	✅	✅	✅	✅	❌	✅	6
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Improving Sharpness-Aware Minimization by Lookahead	✅	❌	✅	✅	❌	❌	✅	4
Improving Token-Based World Models with Parallel Observation Prediction	✅	✅	✅	❌	✅	❌	✅	5
Improving Transformers with Dynamically Composable Multi-Head Attention	✅	✅	✅	❌	✅	❌	✅	5
Improving fine-grained understanding in image-text pre-training	✅	❌	✅	✅	✅	❌	✅	5
In value-based deep reinforcement learning, a pruned network is a good network	❌	✅	✅	❌	✅	❌	✅	4
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought	✅	✅	✅	❌	✅	❌	✅	5
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization	✅	✅	✅	✅	✅	❌	✅	6
In-Context Language Learning: Architectures and Algorithms	✅	✅	✅	❌	❌	❌	✅	4
In-Context Learning Agents Are Asymmetric Belief Updaters	❌	✅	❌	❌	❌	❌	✅	2
In-Context Principle Learning from Mistakes	✅	❌	✅	❌	❌	✅	✅	4
In-Context Reinforcement Learning for Variable Action Spaces	✅	✅	❌	❌	✅	✅	✅	5
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation	✅	✅	✅	✅	✅	❌	✅	6
In-Context Unlearning: Language Models as Few-Shot Unlearners	❌	✅	✅	✅	✅	❌	✅	5
In-context Convergence of Transformers	❌	❌	❌	❌	❌	❌	✅	1
In-context Learning on Function Classes Unveiled for Transformers	❌	❌	❌	❌	❌	❌	✅	1
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering	❌	✅	✅	❌	✅	❌	✅	4
Incentivized Learning in Principal-Agent Bandit Games	✅	❌	❌	❌	❌	❌	✅	2
Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach	✅	❌	❌	❌	❌	❌	❌	1
Incorporating probabilistic domain knowledge into deep multiple instance learning	❌	❌	✅	✅	❌	❌	✅	3
Incremental Topological Ordering and Cycle Detection with Predictions	❌	✅	✅	❌	✅	❌	✅	4
Indirectly Parameterized Concrete Autoencoders	❌	✅	✅	✅	✅	❌	✅	5
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Individual Fairness in Graph Decomposition	✅	❌	✅	❌	❌	❌	✅	3
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization	✅	❌	❌	❌	❌	❌	❌	1
Inexact Newton-type Methods for Optimisation with Nonnegativity Constraints	✅	✅	✅	❌	❌	❌	✅	4
InferCept: Efficient Intercept Support for Augmented Large Language Model Inference	❌	✅	✅	❌	✅	❌	❌	3
Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing	❌	✅	❌	✅	✅	✅	✅	5
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting	✅	✅	✅	❌	❌	❌	✅	4
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments	❌	✅	❌	❌	❌	❌	✅	2
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks	❌	✅	✅	✅	❌	❌	✅	4
Infinite-Horizon Distributionally Robust Regret-Optimal Control	✅	❌	✅	❌	✅	❌	✅	4
InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization	✅	✅	✅	❌	✅	❌	✅	5
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing	✅	❌	❌	❌	❌	❌	❌	1
Information Flow in Self-Supervised Learning	❌	❌	✅	✅	❌	❌	✅	3
Information-Directed Pessimism for Offline Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks	✅	✅	✅	❌	❌	❌	✅	4
Initial Guessing Bias: How Untrained Networks Favor Some Classes	❌	✅	✅	❌	❌	❌	❌	2
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining	❌	✅	✅	✅	✅	✅	✅	6
InstructSpeech: Following Speech Editing Instructions via Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Instruction Tuning for Secure Code Generation	✅	✅	✅	✅	✅	❌	✅	6
Integrated Hardware Architecture and Device Placement Search	✅	✅	✅	❌	✅	✅	✅	6
Integrating Global Context Contrast and Local Sensitivity for Blind Image Quality Assessment	❌	❌	✅	✅	❌	❌	✅	3
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics	❌	✅	✅	❌	❌	❌	✅	3
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning	✅	✅	✅	✅	✅	❌	✅	6
Interacting Diffusion Processes for Event Sequence Forecasting	❌	✅	✅	✅	✅	✅	✅	6
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation	✅	✅	✅	❌	✅	❌	✅	5
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification	❌	❌	❌	❌	❌	❌	❌	0
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation	✅	✅	✅	✅	❌	✅	✅	6
Interpretability Illusions in the Generalization of Simplified Models	❌	❌	✅	✅	❌	❌	✅	3
Interpretable Deep Clustering for Tabular Data	❌	✅	✅	❌	✅	❌	✅	4
Interpreting Equivariant Representations	❌	❌	✅	✅	❌	❌	✅	3
Interpreting and Improving Diffusion Models from an Optimization Perspective	✅	✅	✅	❌	✅	✅	✅	6
Interpreting and Improving Large Language Models in Arithmetic Calculation	✅	❌	✅	❌	✅	❌	✅	4
Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models	❌	✅	✅	❌	✅	❌	❌	3
Intersectional Unfairness Discovery	✅	✅	✅	✅	❌	❌	✅	5
Invariant Risk Minimization Is A Total Variation Model	❌	✅	✅	✅	❌	❌	✅	4
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects	❌	✅	✅	✅	❌	❌	✅	4
Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach	❌	✅	✅	✅	✅	❌	✅	5
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study	❌	❌	✅	✅	❌	❌	✅	3
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?	❌	✅	❌	❌	❌	❌	✅	2
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective	❌	✅	❌	❌	✅	❌	✅	3
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective	✅	❌	❌	❌	❌	❌	❌	1
Is Kernel Prediction More Powerful than Gating in Convolutional Neural Networks?	❌	✅	✅	✅	❌	❌	✅	4
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?	❌	❌	❌	❌	❌	❌	✅	1
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities	✅	✅	✅	✅	✅	❌	✅	6
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF	✅	❌	✅	❌	❌	❌	✅	3
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint	✅	✅	✅	✅	✅	❌	✅	6
Iterative Regularized Policy Optimization with Imperfect Demonstrations	✅	✅	✅	❌	❌	❌	✅	4
Iterative Search Attribution for Deep Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Jacobian Regularizer-based Neural Granger Causality	❌	✅	✅	❌	❌	❌	✅	3
Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization	✅	❌	✅	❌	✅	❌	✅	4
Joint Composite Latent Space Bayesian Optimization	✅	✅	✅	❌	✅	❌	✅	5
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textitIrreversibly$ and $\textitMonotonically$ Impairs “Difficult" Downstream Tasks in LLMs	❌	✅	✅	✅	❌	❌	✅	4
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations	✅	✅	✅	❌	❌	❌	✅	4
KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations	✅	❌	✅	❌	✅	❌	✅	4
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache	✅	✅	✅	❌	✅	❌	✅	5
KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation	✅	❌	❌	❌	✅	✅	✅	4
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows	❌	✅	✅	❌	❌	❌	✅	3
Kepler codebook	❌	✅	✅	✅	✅	❌	✅	5
Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters	✅	✅	❌	❌	✅	❌	✅	4
Kernel Semi-Implicit Variational Inference	✅	✅	✅	✅	✅	❌	✅	6
Kernel-Based Evaluation of Conditional Biological Sequence Models	✅	❌	✅	❌	❌	❌	✅	3
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions	✅	✅	✅	❌	✅	❌	❌	4
KernelWarehouse: Rethinking the Design of Dynamic Convolution	✅	✅	✅	✅	✅	❌	✅	6
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs	✅	❌	✅	✅	✅	❌	✅	5
KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning	✅	✅	✅	✅	✅	✅	✅	7
Knowledge Distillation with Auxiliary Variable	✅	❌	✅	❌	❌	❌	✅	3
Knowledge Graphs Can be Learned with Just Intersection Features	❌	✅	✅	✅	✅	❌	✅	5
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models	❌	❌	✅	✅	✅	❌	✅	4
Knowledge-aware Reinforced Language Models for Protein Directed Evolution	✅	✅	✅	✅	✅	❌	✅	6
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
LASER: Linear Compression in Wireless Distributed Optimization	✅	✅	✅	❌	❌	❌	✅	4
LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies	❌	✅	✅	❌	✅	❌	✅	4
LESS: Selecting Influential Data for Targeted Instruction Tuning	✅	✅	✅	✅	✅	❌	✅	6
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views	❌	❌	✅	✅	✅	❌	✅	4
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models	✅	❌	✅	❌	❌	❌	✅	3
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning	✅	✅	✅	❌	❌	❌	✅	4
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery	✅	❌	✅	❌	❌	❌	✅	3
LLM-Empowered State Representation for Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
LLaGA: Large Language and Graph Assistant	❌	✅	✅	✅	❌	✅	✅	5
LLark: A Multimodal Instruction-Following Language Model for Music	❌	✅	✅	✅	✅	❌	✅	5
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers	✅	✅	✅	❌	❌	❌	✅	4
LQER: Low-Rank Quantization Error Reconstruction for LLMs	❌	✅	✅	❌	✅	❌	✅	4
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering	✅	✅	✅	❌	❌	✅	✅	5
LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits	❌	❌	❌	❌	✅	❌	✅	2
LangCell: Language-Cell Pre-training for Cell Identity Understanding	❌	✅	✅	❌	✅	❌	✅	4
Langevin Policy for Safe Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models	✅	✅	✅	❌	❌	❌	✅	4
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game	❌	✅	❌	❌	❌	✅	✅	3
Language Generation with Strictly Proper Scoring Rules	❌	✅	✅	✅	❌	❌	✅	4
Language Models Represent Beliefs of Self and Others	❌	✅	✅	❌	❌	❌	✅	3
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch	❌	✅	✅	✅	✅	❌	✅	5
Language Models as Science Tutors	❌	✅	✅	✅	✅	❌	✅	5
Language Models as Semantic Indexers	✅	✅	✅	✅	✅	❌	✅	6
Language Models with Conformal Factuality Guarantees	✅	✅	✅	✅	❌	❌	✅	5
Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition	✅	❌	✅	❌	❌	❌	✅	3
Language-guided Skill Learning with Temporal Variational Inference	❌	✅	✅	✅	❌	❌	✅	4
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning	❌	✅	✅	✅	✅	❌	✅	5
Large Language Models are Geographically Biased	❌	✅	✅	❌	❌	❌	✅	3
Large Scale Dataset Distillation with Domain Shift	✅	✅	✅	✅	✅	❌	✅	6
Larimar: Large Language Models with Episodic Memory Control	✅	✅	✅	✅	✅	❌	✅	6
Latent Logic Tree Extraction for Event Sequence Explanation from LLMs	✅	❌	✅	✅	✅	❌	✅	5
Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping	✅	✅	✅	✅	✅	❌	✅	6
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming	✅	✅	✅	✅	✅	❌	✅	6
Latent Space Symmetry Discovery	❌	✅	✅	❌	❌	❌	✅	3
Latent variable model for high-dimensional point process with structured missingness	❌	✅	✅	✅	❌	❌	✅	4
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency	✅	✅	✅	❌	✅	❌	✅	5
LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging	✅	✅	✅	✅	✅	❌	✅	6
Layerwise Change of Knowledge in Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning	✅	✅	✅	❌	❌	❌	✅	4
LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions	❌	✅	✅	✅	✅	❌	✅	5
Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement	❌	❌	✅	✅	✅	❌	✅	4
Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking	❌	✅	✅	❌	✅	❌	✅	4
Learning Associative Memories with Gradient Descent	❌	❌	❌	❌	❌	❌	✅	1
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition	❌	❌	✅	✅	✅	❌	✅	4
Learning Causal Dynamics Models in Object-Oriented Environments	✅	✅	✅	❌	✅	❌	✅	5
Learning Causal Relations from Subsampled Time Series with Two Time-Slices	✅	✅	✅	❌	✅	✅	✅	6
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments	❌	❌	✅	❌	✅	❌	✅	3
Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation	✅	✅	✅	❌	✅	❌	✅	5
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Learning Decision Policies with Instrumental Variables through Double Machine Learning	✅	✅	✅	✅	❌	❌	✅	5
Learning Decision Trees and Forests with Algorithmic Recourse	✅	✅	✅	✅	✅	✅	✅	7
Learning Divergence Fields for Shift-Robust Graph Representations	❌	✅	✅	✅	✅	✅	✅	6
Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence	✅	✅	✅	❌	❌	❌	✅	4
Learning Graph Representation via Graph Entropy Maximization	✅	✅	✅	✅	✅	❌	✅	6
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding	❌	✅	✅	❌	❌	❌	✅	3
Learning High-Order Relationships of Brain Regions	❌	✅	✅	✅	✅	✅	✅	6
Learning Iterative Reasoning through Energy Diffusion	✅	✅	✅	❌	✅	❌	✅	5
Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition	✅	✅	✅	❌	❌	❌	✅	4
Learning Latent Dynamic Robust Representations for World Models	✅	✅	✅	❌	✅	❌	✅	5
Learning Latent Space Hierarchical EBM Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders	❌	✅	✅	❌	❌	❌	✅	3
Learning Linear Block Error Correction Codes	❌	✅	✅	❌	✅	❌	✅	4
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds	✅	❌	❌	✅	❌	❌	✅	3
Learning Mixtures of Gaussian Processes through Random Projection	✅	✅	✅	❌	✅	❌	✅	5
Learning Modality Knowledge Alignment for Cross-Modality Transfer	✅	❌	✅	❌	❌	❌	✅	3
Learning Multiple Secrets in Mastermind	✅	❌	❌	❌	❌	❌	❌	1
Learning Optimal Deterministic Policies with Stochastic Policy Gradients	✅	✅	✅	❌	❌	❌	✅	4
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series	❌	❌	✅	✅	❌	❌	✅	3
Learning Pseudo-Contractive Denoisers for Inverse Problems	✅	✅	✅	❌	❌	✅	✅	5
Learning Reward for Robot Skills Using Large Language Models via Self-Alignment	✅	❌	✅	❌	❌	❌	✅	3
Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring	❌	✅	✅	✅	✅	❌	✅	5
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias	✅	✅	✅	✅	✅	❌	✅	6
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem	✅	✅	✅	✅	✅	❌	✅	6
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching	✅	✅	✅	❌	✅	❌	✅	5
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making	✅	✅	✅	❌	❌	❌	✅	4
Learning Universal Predictors	✅	✅	❌	❌	❌	❌	✅	3
Learning Useful Representations of Recurrent Neural Network Weight Matrices	❌	✅	✅	✅	✅	❌	✅	5
Learning a Diffusion Model Policy from Rewards via Q-Score Matching	✅	✅	✅	❌	❌	❌	✅	4
Learning and Forgetting Unsafe Examples in Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
Learning from Integral Losses in Physics Informed Neural Networks	✅	✅	❌	❌	❌	❌	✅	3
Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features	✅	✅	✅	❌	✅	❌	✅	5
Learning from Streaming Data when Users Choose	✅	✅	✅	❌	❌	❌	✅	4
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs	✅	✅	✅	❌	❌	❌	✅	4
Learning in Deep Factor Graphs with Gaussian Belief Propagation	❌	✅	✅	✅	✅	❌	✅	5
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method	✅	❌	✅	✅	✅	✅	✅	6
Learning the Target Network in Function Space	✅	❌	✅	❌	❌	❌	✅	3
Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis	❌	✅	❌	❌	❌	❌	✅	2
Learning to Compile Programs to Neural Networks	❌	❌	✅	✅	✅	❌	✅	4
Learning to Continually Learn with the Bayesian Principle	❌	✅	✅	❌	✅	❌	✅	4
Learning to Explore for Stochastic Gradient MCMC	✅	✅	✅	❌	✅	❌	✅	5
Learning to Explore in POMDPs with Informational Rewards	✅	✅	✅	❌	❌	❌	✅	4
Learning to Infer Generative Template Programs for Visual Concepts	❌	✅	✅	✅	✅	❌	✅	5
Learning to Intervene on Concept Bottlenecks	✅	✅	✅	✅	❌	❌	✅	5
Learning to Model the World With Language	✅	❌	✅	❌	✅	❌	✅	4
Learning to Play Atari in a World of Tokens	✅	✅	✅	❌	❌	❌	✅	4
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning	✅	✅	✅	✅	❌	❌	✅	5
Learning to Reach Goals via Diffusion	✅	✅	✅	❌	❌	❌	✅	4
Learning to Remove Cuts in Integer Linear Programming	✅	❌	❌	✅	❌	✅	✅	4
Learning to Route Among Specialized Experts for Zero-Shot Generalization	❌	✅	✅	❌	❌	❌	✅	3
Learning to Scale Logits for Temperature-Conditional GFlowNets	✅	✅	✅	❌	❌	❌	✅	4
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces	✅	✅	✅	❌	✅	❌	✅	5
Learning with 3D rotations, a hitchhiker’s guide to SO(3)	❌	✅	✅	✅	✅	✅	✅	6
Learning with Adaptive Resource Allocation	✅	❌	✅	❌	❌	❌	✅	3
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical	✅	✅	✅	✅	❌	❌	✅	5
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency	✅	❌	✅	❌	✅	❌	✅	4
Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation	✅	✅	✅	✅	✅	❌	✅	6
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds	✅	✅	✅	❌	✅	❌	✅	5
Less is More: on the Over-Globalizing Problem in Graph Transformers	❌	✅	✅	✅	❌	❌	✅	4
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!	✅	✅	✅	❌	✅	❌	✅	5
Let Go of Your Labels with Unsupervised Transfer	✅	✅	✅	✅	✅	❌	✅	6
Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification	✅	❌	✅	✅	✅	❌	✅	5
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data	✅	❌	❌	❌	❌	❌	✅	2
Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing	❌	❌	✅	✅	❌	✅	✅	4
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference	✅	✅	✅	❌	❌	❌	✅	4
Leveraging VLM-Based Pipelines to Annotate 3D Objects	❌	✅	✅	❌	❌	✅	✅	4
Libra: Building Decoupled Vision System on Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras	❌	✅	✅	❌	❌	❌	✅	3
Light and Optimal Schrödinger Bridge Matching	✅	✅	✅	✅	✅	❌	✅	6
Lightweight Image Super-Resolution via Flexible Meta Pruning	❌	❌	✅	✅	✅	❌	✅	4
Limited Preference Aided Imitation Learning from Imperfect Demonstrations	✅	❌	✅	❌	❌	❌	✅	3
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback	✅	✅	✅	❌	✅	❌	✅	5
Linear Explanations for Individual Neurons	✅	✅	✅	✅	✅	❌	✅	6
Linguistic Calibration of Long-Form Generations	✅	✅	✅	✅	✅	✅	✅	7
Liouville Flow Importance Sampler	✅	✅	✅	❌	✅	❌	✅	5
Listenable Maps for Audio Classifiers	❌	✅	✅	❌	❌	❌	✅	3
Listening to the noise: Blind Denoising with Gibbs Diffusion	✅	✅	✅	✅	✅	❌	✅	6
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
LoCoCo: Dropping In Convolutions for Long Context Compression	✅	✅	✅	❌	✅	✅	✅	6
LoRA Training in the NTK Regime has No Spurious Local Minima	❌	✅	✅	❌	❌	❌	✅	3
LoRA+: Efficient Low Rank Adaptation of Large Models	❌	✅	✅	❌	✅	❌	✅	4
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models	✅	❌	✅	✅	✅	❌	✅	5
Local Causal Structure Learning in the Presence of Latent Variables	✅	✅	✅	❌	✅	❌	❌	4
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions	✅	✅	✅	❌	❌	❌	✅	4
Local vs. Global Interpretability: A Computational Complexity Perspective	✅	❌	❌	❌	❌	❌	❌	1
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics	❌	✅	✅	✅	✅	❌	✅	5
Localizing Task Information for Improved Model Merging and Compression	❌	✅	✅	✅	✅	❌	✅	5
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy	✅	❌	✅	✅	❌	❌	✅	4
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization	✅	✅	✅	❌	✅	❌	✅	5
Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies	❌	❌	❌	❌	❌	❌	❌	0
Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference	❌	✅	✅	✅	✅	❌	✅	5
Logistic Variational Bayes Revisited	❌	✅	✅	✅	✅	✅	✅	6
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning	❌	✅	✅	❌	✅	❌	✅	4
Long Range Propagation on Continuous-Time Dynamic Graphs	❌	✅	✅	✅	✅	❌	✅	5
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts	✅	✅	✅	❌	✅	❌	✅	5
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens	✅	✅	✅	✅	✅	❌	✅	6
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer	✅	✅	✅	✅	✅	❌	✅	6
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining	❌	✅	✅	✅	❌	❌	✅	4
Lookbehind-SAM: k steps back, 1 step forward	✅	✅	✅	✅	✅	❌	✅	6
Loss Shaping Constraints for Long-Term Time Series Forecasting	✅	❌	✅	✅	❌	❌	✅	4
Low-Cost High-Power Membership Inference Attacks	✅	✅	✅	❌	❌	❌	✅	4
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery	✅	✅	❌	❌	❌	❌	✅	3
Low-Rank Similarity Mining for Multimodal Dataset Distillation	✅	✅	✅	✅	✅	❌	✅	6
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation	✅	✅	❌	❌	❌	❌	✅	3
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent	✅	✅	✅	❌	✅	❌	✅	5
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models	❌	✅	✅	❌	✅	❌	✅	4
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation	✅	✅	✅	✅	✅	❌	✅	6
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization	✅	✅	✅	✅	✅	❌	✅	6
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations	✅	✅	✅	❌	❌	❌	✅	4
MD tree: a model-diagnostic tree grown on loss landscape	❌	✅	✅	❌	✅	❌	✅	4
MEMORYLLM: Towards Self-Updatable Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series	✅	✅	✅	✅	❌	❌	✅	5
MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution	❌	❌	✅	❌	✅	✅	✅	4
MGit: A Model Versioning and Management System	✅	✅	✅	❌	✅	❌	✅	5
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis	❌	❌	✅	❌	❌	❌	✅	2
MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness	✅	❌	✅	✅	❌	✅	✅	5
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation	❌	✅	✅	❌	❌	❌	✅	3
MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation	✅	❌	✅	❌	❌	❌	✅	3
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization	✅	❌	✅	❌	✅	❌	✅	4
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark	❌	✅	✅	❌	✅	❌	✅	4
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities	❌	✅	✅	❌	❌	❌	✅	3
MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance	✅	✅	✅	✅	✅	❌	✅	6
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI	❌	✅	✅	❌	✅	❌	✅	4
MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence	✅	✅	✅	✅	✅	❌	✅	6
MOMENT: A Family of Open Time-series Foundation Models	❌	✅	✅	✅	✅	❌	✅	5
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data	✅	❌	✅	❌	✅	❌	✅	4
MS-TIP: Imputation Aware Pedestrian Trajectory Prediction	❌	✅	✅	❌	❌	✅	✅	4
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts	❌	✅	✅	❌	✅	❌	✅	4
MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective	❌	✅	✅	✅	❌	❌	✅	4
Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning	✅	✅	✅	✅	✅	❌	✅	6
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition	✅	✅	✅	❌	✅	✅	✅	6
MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions	❌	✅	✅	✅	✅	❌	✅	5
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion	❌	✅	✅	✅	✅	❌	✅	5
Magicoder: Empowering Code Generation with OSS-Instruct	❌	✅	✅	❌	✅	❌	✅	4
Major-Minor Mean Field Multi-Agent Reinforcement Learning	✅	✅	❌	❌	✅	✅	✅	5
Make-A-Shape: a Ten-Million-scale 3D Shape Model	❌	❌	✅	✅	✅	❌	✅	4
Making Old Things New: A Unified Algorithm for Differentially Private Clustering	✅	❌	❌	❌	❌	❌	❌	1
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution	✅	✅	✅	❌	❌	❌	✅	4
Mapping the Multiverse of Latent Representations	❌	✅	✅	✅	❌	❌	✅	4
Masked Face Recognition with Generative-to-Discriminative Representations	❌	❌	✅	✅	✅	❌	✅	4
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning	✅	❌	✅	✅	✅	❌	✅	5
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs	❌	✅	✅	❌	❌	❌	✅	3
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games	✅	✅	✅	❌	✅	❌	✅	5
MathScale: Scaling Instruction Tuning for Mathematical Reasoning	✅	✅	✅	✅	❌	❌	✅	5
Matrix Information Theory for Self-Supervised Learning	✅	✅	✅	✅	❌	❌	✅	5
Matroid Semi-Bandits in Sublinear Time	✅	❌	❌	❌	❌	❌	❌	1
MaxMin-RLHF: Alignment with Diverse Human Preferences	✅	❌	✅	❌	❌	❌	✅	3
Mean Estimation in the Add-Remove Model of Differential Privacy	✅	❌	❌	❌	❌	❌	✅	2
Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning	✅	❌	✅	❌	❌	❌	✅	3
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective	❌	❌	❌	❌	❌	❌	✅	1
Mean-field Chaos Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization	✅	✅	❌	❌	❌	❌	✅	3
Measures of diversity and space-filling designs for categorical data	✅	❌	✅	❌	✅	❌	✅	4
Measuring Stochastic Data Complexity with Boltzmann Influence Functions	❌	❌	✅	✅	✅	❌	✅	4
Mechanistic Design and Scaling of Hybrid Architectures	❌	❌	✅	❌	❌	❌	✅	2
Mechanistic Neural Networks for Scientific Machine Learning	❌	✅	✅	✅	❌	❌	✅	4
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads	❌	❌	✅	❌	✅	❌	✅	3
Membership Inference Attacks on Diffusion Models via Quantile Regression	✅	❌	✅	❌	✅	❌	✅	4
Memoria: Resolving Fateful Forgetting Problem through Human-Inspired Memory Architecture	✅	✅	✅	✅	✅	❌	✅	6
Memorization Through the Lens of Curvature of Loss Function Around Samples	✅	✅	✅	✅	✅	❌	✅	6
Memory Consolidation Enables Long-Context Video Understanding	✅	❌	✅	❌	❌	❌	✅	3
Memory Efficient Neural Processes via Constant Memory Attention Block	❌	✅	✅	❌	✅	❌	✅	4
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning	❌	✅	✅	❌	✅	❌	✅	4
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts	❌	✅	✅	❌	❌	❌	✅	3
Meta Evidential Transformer for Few-Shot Open-Set Recognition	✅	✅	✅	✅	❌	❌	✅	5
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments	✅	✅	✅	✅	❌	❌	✅	5
Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning	✅	✅	❌	❌	❌	❌	✅	3
Mimicking Better by Matching the Approximate Action Distribution	✅	✅	✅	❌	❌	❌	✅	4
Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary	✅	❌	✅	✅	❌	❌	✅	4
MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data	✅	✅	✅	❌	✅	❌	✅	5
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value	✅	✅	❌	❌	❌	❌	✅	3
Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions	✅	❌	✅	❌	❌	❌	❌	2
Minimizing $f$-Divergences by Interpolating Velocity Fields	✅	✅	✅	❌	❌	❌	✅	4
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces	❌	❌	❌	❌	❌	❌	❌	0
Minimum-Norm Interpolation Under Covariate Shift	❌	❌	✅	❌	✅	❌	✅	3
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization	✅	❌	✅	✅	❌	❌	✅	4
Mitigating Label Noise on Graphs via Topological Sample Selection	✅	❌	✅	✅	❌	❌	✅	4
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs	✅	✅	✅	✅	❌	❌	✅	5
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss	❌	✅	✅	✅	❌	❌	✅	4
Mixtures of Experts Unlock Parameter Scaling for Deep RL	❌	✅	✅	❌	✅	❌	✅	4
MoMo: Momentum Models for Adaptive Learning Rates	✅	❌	✅	❌	✅	❌	✅	4
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers	❌	✅	✅	✅	✅	✅	✅	6
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases	❌	❌	✅	❌	✅	❌	✅	3
Model Alignment as Prospect Theoretic Optimization	❌	✅	✅	❌	❌	❌	✅	3
Model Assessment and Selection under Temporal Distribution Shift	✅	✅	✅	✅	❌	❌	✅	5
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models	❌	❌	✅	❌	✅	❌	✅	3
Model-Based Minimum Bayes Risk Decoding for Text Generation	❌	✅	✅	❌	❌	❌	✅	3
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL	✅	✅	❌	❌	❌	❌	✅	3
Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data	✅	❌	❌	❌	❌	❌	❌	1
Model-based Reinforcement Learning for Confounded POMDPs	✅	❌	❌	❌	❌	❌	❌	1
Model-based Reinforcement Learning for Parameterized Action Spaces	✅	✅	✅	❌	❌	❌	✅	4
Modeling Caption Diversity in Contrastive Vision-Language Pretraining	❌	❌	✅	✅	✅	❌	✅	4
Modeling Language Tokens as Functionals of Semantic Fields	❌	✅	✅	❌	✅	❌	✅	4
Modelling Microbial Communities with Graph Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference	✅	✅	✅	❌	✅	❌	✅	5
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective	❌	✅	✅	✅	✅	❌	✅	5
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space	✅	✅	✅	✅	✅	❌	✅	6
Mollification Effects of Policy Gradient Methods	❌	❌	✅	❌	❌	❌	✅	2
Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning	❌	✅	✅	❌	✅	❌	✅	4
Momentum Particle Maximum Likelihood	✅	✅	✅	❌	❌	❌	✅	4
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments	✅	✅	✅	❌	✅	❌	✅	5
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews	❌	✅	✅	✅	❌	❌	✅	4
Monotone Individual Fairness	✅	❌	❌	❌	❌	❌	❌	1
Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks	✅	✅	✅	❌	✅	❌	✅	5
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms	❌	✅	✅	✅	❌	❌	✅	4
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy	✅	✅	✅	✅	✅	❌	✅	6
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation	❌	✅	✅	✅	✅	✅	✅	6
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy	✅	❌	✅	✅	✅	✅	✅	6
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing	✅	✅	✅	✅	✅	❌	✅	6
Multi-Factor Adaptive Vision Selection for Egocentric Video Question Answering	✅	✅	✅	❌	✅	❌	✅	5
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling	✅	✅	✅	✅	✅	❌	✅	6
Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions	❌	✅	✅	✅	❌	❌	✅	4
Multi-Sender Persuasion: A Computational Perspective	❌	❌	❌	❌	❌	❌	✅	1
Multi-Source Conformal Inference Under Distribution Shift	✅	✅	✅	✅	❌	❌	✅	5
Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing	✅	✅	✅	✅	✅	✅	✅	7
Multi-View Clustering by Inter-cluster Connectivity Guided Reward	❌	❌	✅	❌	❌	❌	✅	2
Multi-View Stochastic Block Models	✅	❌	❌	❌	❌	❌	✅	2
Multi-group Learning for Hierarchical Groups	✅	❌	✅	❌	❌	❌	✅	3
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning	✅	✅	✅	✅	❌	❌	✅	5
MultiMax: Sparse and Multi-Modal Attention Learning	❌	✅	✅	❌	❌	❌	✅	3
Multicalibration for Confidence Scoring in LLMs	✅	❌	✅	✅	❌	❌	❌	3
Multigroup Robustness	✅	✅	✅	❌	❌	❌	❌	3
Multimodal Prototyping for cancer survival prediction	❌	✅	✅	✅	❌	❌	✅	4
Multiplicative Weights Update, Area Convexity and Random Coordinate Descent for Densest Subgraph Problems	✅	❌	✅	❌	❌	❌	❌	2
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains	✅	✅	✅	✅	✅	❌	✅	6
Multiply-Robust Causal Change Attribution	❌	✅	✅	✅	❌	❌	✅	4
MusicFlow: Cascaded Flow Matching for Text Guided Music Generation	❌	❌	✅	❌	❌	❌	✅	2
MusicRL: Aligning Music Generation to Human Preferences	❌	❌	✅	✅	✅	❌	✅	4
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving	✅	✅	✅	❌	✅	❌	✅	5
NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
NExT-Chat: An LMM for Chat, Detection and Segmentation	❌	❌	✅	✅	✅	❌	✅	4
NExT-GPT: Any-to-Any Multimodal LLM	❌	✅	✅	❌	❌	❌	✅	3
NExT: Teaching Large Language Models to Reason about Code Execution	✅	❌	✅	✅	❌	❌	✅	4
Naive Bayes Classifiers over Missing Data: Decision and Poisoning	✅	✅	✅	❌	✅	❌	✅	5
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning	✅	❌	❌	❌	❌	❌	❌	1
Nash Learning from Human Feedback	❌	❌	✅	✅	❌	❌	✅	3
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching	✅	✅	✅	✅	✅	❌	✅	6
Navigating Scaling Laws: Compute Optimality in Adaptive Model Training	❌	❌	✅	❌	❌	❌	✅	2
NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction	❌	✅	✅	❌	✅	❌	✅	4
Near-Linear Time Approximation Algorithms for k-means with Outliers	✅	❌	✅	❌	✅	❌	✅	4
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints	✅	❌	❌	❌	❌	❌	❌	1
Nearest Neighbour Score Estimators for Diffusion Generative Models	✅	✅	✅	❌	✅	❌	✅	5
Neighboring Perturbations of Knowledge Editing on Large Language Models	❌	✅	✅	✅	❌	❌	✅	4
Nesting Particle Filters for Experimental Design in Dynamical Systems	✅	✅	❌	❌	✅	❌	✅	4
Network Tight Community Detection	✅	❌	✅	❌	✅	❌	✅	4
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction	❌	✅	✅	✅	✅	❌	✅	5
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model	❌	❌	✅	❌	❌	❌	✅	2
Neural Collapse in Multi-label Learning with Pick-all-label Loss	❌	✅	✅	❌	❌	❌	✅	3
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning	❌	❌	✅	❌	❌	❌	✅	2
Neural Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity	❌	✅	✅	✅	✅	❌	✅	5
Neural Jump-Diffusion Temporal Point Processes	✅	✅	✅	✅	✅	❌	✅	6
Neural NeRF Compression	✅	❌	✅	❌	✅	❌	✅	4
Neural Networks Learn Statistics of Increasing Complexity	✅	✅	✅	✅	✅	❌	✅	6
Neural Operators with Localized Integral and Differential Kernels	❌	✅	❌	✅	✅	❌	✅	4
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics	❌	✅	✅	✅	❌	❌	✅	4
Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
Neural Tangent Kernels for Axis-Aligned Tree Ensembles	❌	✅	✅	✅	❌	❌	✅	4
Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving	✅	✅	✅	❌	❌	❌	✅	4
Neural-Kernel Conditional Mean Embeddings	❌	✅	✅	✅	✅	❌	✅	5
NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors	❌	❌	✅	❌	✅	❌	✅	3
Neuro-Symbolic Temporal Point Processes	❌	❌	✅	❌	✅	✅	❌	3
Neuro-Visualizer: A Novel Auto-Encoder-Based Loss Landscape Visualization Method With an Application in Knowledge-Guided Machine Learning	❌	✅	✅	❌	✅	❌	✅	4
Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization	❌	❌	✅	✅	✅	❌	✅	4
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields	❌	❌	✅	❌	✅	❌	✅	3
New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering	✅	❌	❌	❌	❌	❌	❌	1
New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming	❌	❌	❌	❌	❌	❌	❌	0
No Dimensional Sampling Coresets for Classification	❌	❌	❌	❌	❌	❌	❌	0
No Double Descent in Principal Component Regression: A High-Dimensional Analysis	❌	✅	✅	❌	❌	❌	✅	3
No Free Prune: Information-Theoretic Barriers to Pruning at Initialization	❌	❌	✅	❌	❌	❌	✅	2
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths	✅	✅	✅	✅	✅	✅	✅	7
No-Regret Reinforcement Learning in Smooth MDPs	❌	❌	❌	❌	✅	❌	✅	2
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization	✅	✅	✅	❌	❌	❌	✅	4
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation	✅	❌	✅	❌	❌	❌	✅	3
Non-Vacuous Generalization Bounds for Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
Non-clairvoyant Scheduling with Partial Predictions	✅	❌	❌	❌	❌	❌	✅	2
Non-confusing Generation of Customized Concepts in Diffusion Models	❌	❌	❌	❌	✅	❌	✅	2
Non-convex Stochastic Composite Optimization with Polyak Momentum	✅	❌	✅	❌	❌	❌	✅	3
Non-parametric Online Change Point Detection on Riemannian Manifolds	✅	✅	✅	❌	❌	❌	✅	4
Non-stationary Online Convex Optimization with Arbitrary Delays	✅	❌	❌	❌	❌	❌	❌	1
Nonlinear Filtering with Brenier Optimal Transport Maps	✅	✅	✅	❌	✅	❌	✅	5
Nonparametric Teaching of Implicit Neural Representations	✅	✅	✅	❌	✅	❌	✅	5
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates	✅	✅	✅	✅	❌	❌	✅	5
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators	✅	✅	✅	❌	✅	❌	✅	5
Not all distributional shifts are equal: Fine-grained robust conformal inference	✅	✅	✅	✅	❌	❌	✅	5
Novel Spectral Algorithms for the Partial Credit Model	✅	✅	✅	✅	❌	❌	✅	5
O$n$ Learning Deep O($n$)-Equivariant Hyperspheres	❌	✅	✅	✅	✅	❌	❌	4
OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification	✅	❌	✅	❌	✅	❌	✅	4
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models	✅	✅	✅	❌	✅	❌	✅	5
ODIN: Disentangled Reward Mitigates Hacking in RLHF	✅	❌	✅	✅	✅	❌	✅	5
OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning	✅	✅	✅	❌	✅	✅	✅	6
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts	✅	✅	✅	❌	✅	❌	✅	5
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift	❌	✅	✅	❌	❌	❌	✅	3
OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos	❌	✅	✅	❌	❌	❌	✅	3
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization	✅	✅	✅	✅	✅	❌	✅	6
OT-CLIP: Understanding and Generalizing CLIP via Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
OTMatch: Improving Semi-Supervised Learning with Optimal Transport	✅	❌	✅	❌	❌	❌	✅	3
Observable Propagation: Uncovering Feature Vectors in Transformers	✅	✅	✅	❌	❌	❌	❌	3
Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness	❌	✅	✅	❌	❌	❌	❌	2
Offline Actor-Critic Reinforcement Learning Scales to Large Models	✅	❌	✅	❌	✅	❌	✅	4
Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching	✅	✅	✅	❌	✅	❌	✅	5
Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms	✅	❌	✅	❌	❌	❌	❌	2
Offline Multi-Objective Optimization	❌	✅	✅	✅	❌	✅	✅	5
Offline Training of Language Model Agents with Functions as Learnable Weights	✅	✅	✅	❌	❌	❌	✅	4
Offline Transition Modeling via Contrastive Energy Learning	✅	✅	✅	❌	❌	❌	✅	4
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL	✅	✅	✅	❌	✅	❌	✅	5
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis	✅	❌	❌	❌	❌	❌	❌	1
On Convergence of Incremental Gradient for Non-convex Smooth Functions	❌	❌	✅	❌	❌	❌	✅	2
On Discrete Prompt Optimization for Diffusion Models	✅	❌	✅	❌	❌	❌	✅	3
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box	❌	✅	✅	✅	✅	✅	✅	6
On Hypothesis Transfer Learning of Functional Linear Models	✅	✅	✅	✅	❌	❌	✅	5
On Interpolating Experts and Multi-Armed Bandits	✅	❌	❌	❌	❌	❌	❌	1
On Least Square Estimation in Softmax Gating Mixture of Experts	❌	❌	❌	❌	❌	❌	✅	1
On Mechanistic Knowledge Localization in Text-to-Image Generative Models	✅	✅	✅	❌	❌	❌	✅	4
On Multi-Armed Bandit with Impatient Arms	✅	❌	❌	❌	❌	❌	✅	2
On Online Experimentation without Device Identifiers	✅	❌	✅	❌	❌	❌	❌	2
On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization	✅	✅	✅	✅	❌	✅	✅	6
On Positivity Condition for Causal Inference	✅	❌	❌	❌	❌	❌	❌	1
On Prompt-Driven Safeguarding for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
On Statistical Learning Theory for Distributional Inputs	❌	❌	❌	❌	❌	❌	❌	0
On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning	✅	❌	❌	❌	❌	❌	❌	1
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization	✅	❌	❌	❌	❌	❌	❌	1
On The Fairness Impacts of Hardware Selection in Machine Learning	❌	❌	✅	❌	✅	✅	✅	4
On The Statistical Complexity of Offline Decision-Making	✅	❌	❌	❌	❌	❌	❌	1
On Universally Optimal Algorithms for A/B Testing	✅	❌	❌	❌	❌	❌	✅	2
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective	❌	❌	✅	✅	✅	❌	✅	4
On a Combinatorial Problem Arising in Machine Teaching	❌	❌	❌	❌	❌	❌	❌	0
On a Neural Implementation of Brenier’s Polar Factorization	✅	❌	✅	✅	❌	❌	✅	4
On dimensionality of feature vectors in MPNNs	❌	✅	✅	❌	❌	❌	✅	3
On the Asymptotic Distribution of the Minimum Empirical Risk	❌	❌	❌	❌	❌	❌	✅	1
On the Calibration of Human Pose Estimation	✅	❌	✅	✅	❌	❌	✅	4
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition	✅	❌	✅	❌	✅	✅	✅	5
On the Consistency of Kernel Methods with Dependent Observations	❌	❌	❌	❌	❌	❌	❌	0
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity	✅	✅	❌	❌	❌	❌	✅	3
On the Diminishing Returns of Width for Continual Learning	❌	✅	✅	❌	✅	❌	✅	4
On the Duality Between Sharpness-Aware Minimization and Adversarial Training	❌	✅	✅	❌	❌	❌	✅	3
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning	❌	✅	✅	✅	❌	❌	✅	4
On the Embedding Collapse when Scaling up Recommendation Models	❌	✅	✅	✅	✅	❌	✅	5
On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm	❌	✅	✅	✅	❌	❌	✅	4
On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis	✅	❌	✅	❌	❌	❌	✅	3
On the Expressive Power of Spectral Invariant Graph Neural Networks	❌	✅	✅	❌	❌	❌	❌	2
On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors	✅	✅	❌	❌	✅	✅	✅	5
On the Generalization of Equivariant Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
On the Hardness of Probabilistic Neurosymbolic Learning	❌	✅	✅	❌	✅	❌	✅	4
On the Identifiability of Switching Dynamical Systems	❌	✅	✅	✅	✅	❌	✅	5
On the Implicit Bias of Adam	❌	✅	✅	❌	❌	❌	✅	3
On the Independence Assumption in Neurosymbolic Learning	❌	❌	✅	❌	❌	❌	✅	2
On the Last-Iterate Convergence of Shuffling Gradient Methods	✅	❌	❌	❌	❌	❌	❌	1
On the Maximal Local Disparity of Fairness-Aware Classifiers	✅	✅	✅	✅	✅	❌	✅	6
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions	✅	✅	❌	❌	❌	❌	✅	3
On the Nonlinearity of Layer Normalization	✅	❌	✅	❌	❌	❌	✅	3
On the Origins of Linear Representations in Large Language Models	❌	❌	✅	❌	❌	❌	✅	2
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data	❌	❌	❌	❌	❌	❌	✅	1
On the Role of Edge Dependency in Graph Generative Models	✅	❌	✅	❌	❌	❌	✅	3
On the Second-Order Convergence of Biased Policy Gradient Algorithms	✅	❌	❌	❌	❌	❌	❌	1
On the Tractability of SHAP Explanations under Markovian Distributions	❌	❌	❌	❌	❌	❌	❌	0
On the Trajectory Regularity of ODE-based Diffusion Sampling	✅	❌	✅	❌	✅	❌	✅	4
On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation	❌	❌	✅	✅	❌	❌	✅	3
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows	❌	❌	❌	❌	❌	❌	✅	1
On the Weight Dynamics of Deep Normalized Networks	✅	❌	✅	❌	✅	✅	✅	5
On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery	❌	❌	❌	❌	❌	❌	✅	1
One Meta-tuned Transformer is What You Need for Few-shot Learning	❌	❌	✅	✅	✅	❌	✅	4
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts	✅	❌	✅	✅	✅	❌	✅	5
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning	✅	✅	✅	❌	✅	✅	✅	6
One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment	❌	❌	✅	❌	✅	❌	✅	3
One-Shot Strategic Classification Under Unknown Costs	✅	❌	❌	❌	❌	❌	❌	1
Online Adaptive Anomaly Thresholding with Confidence Sequences	✅	❌	✅	❌	❌	❌	✅	3
Online Algorithms with Uncertainty-Quantified Predictions	✅	❌	❌	❌	❌	❌	✅	2
Online Cascade Learning for Efficient Inference over Streams	✅	✅	✅	✅	✅	✅	✅	7
Online Isolation Forest	✅	✅	✅	❌	❌	❌	✅	4
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs	❌	✅	❌	❌	❌	❌	✅	2
Online Learning in Betting Markets: Profit versus Prediction	✅	✅	❌	❌	❌	❌	✅	3
Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints	✅	❌	❌	❌	❌	❌	❌	1
Online Learning under Budget and ROI Constraints via Weak Adaptivity	✅	❌	❌	❌	❌	❌	❌	1
Online Learning with Bounded Recall	✅	❌	❌	❌	❌	❌	✅	2
Online Linear Regression in Dynamic Environments via Discounting	✅	❌	❌	❌	❌	❌	❌	1
Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning	❌	✅	❌	❌	❌	❌	✅	2
Online Matrix Completion: A Collaborative Approach with Hott Items	✅	❌	❌	❌	❌	❌	✅	2
Online Resource Allocation with Non-Stationary Customers	✅	❌	❌	❌	❌	❌	✅	2
Online Speculative Decoding	✅	✅	✅	❌	✅	❌	✅	5
Online Variational Sequential Monte Carlo	✅	✅	❌	❌	✅	❌	✅	4
Online bipartite matching with imperfect advice	✅	✅	✅	❌	❌	❌	✅	4
Online conformal prediction with decaying step sizes	❌	✅	✅	✅	❌	❌	✅	4
Open Ad Hoc Teamwork with Cooperative Game Theory	✅	✅	✅	❌	✅	❌	✅	5
Open-Domain Text Evaluation via Contrastive Distribution Methods	✅	✅	✅	✅	❌	❌	❌	4
Open-Vocabulary Calibration for Fine-tuned CLIP	❌	✅	✅	✅	❌	❌	✅	4
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models	❌	❌	✅	❌	✅	❌	✅	3
Operator SVD with Neural Networks via Nested Low-Rank Approximation	✅	✅	✅	❌	✅	❌	✅	5
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models	✅	✅	✅	❌	❌	❌	❌	3
Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique	❌	❌	✅	❌	❌	❌	✅	2
Optimal Batched Linear Bandits	✅	✅	❌	❌	❌	❌	✅	3
Optimal Coresets for Low-Dimensional Geometric Median	❌	❌	❌	❌	❌	❌	❌	0
Optimal Differentially Private Model Training with Public Data	✅	✅	✅	✅	❌	❌	✅	5
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks	✅	❌	❌	❌	❌	❌	✅	2
Optimal Eye Surgeon: Finding image priors through sparse generators at initialization	✅	✅	✅	❌	❌	❌	✅	4
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization	✅	❌	❌	✅	❌	❌	✅	3
Optimal Kernel Choice for Score Function-based Causal Discovery	❌	❌	✅	❌	❌	✅	✅	3
Optimal Kernel Quantile Learning with Random Features	❌	❌	✅	✅	❌	❌	✅	3
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction	✅	✅	✅	❌	❌	❌	✅	4
Optimal Ridge Regularization for Out-of-Distribution Prediction	❌	✅	✅	❌	❌	❌	✅	3
Optimal Transport for Structure Learning Under Missing Data	✅	✅	✅	❌	❌	❌	✅	4
Optimal bounds for $\ell_p$ sensitivity sampling via $\ell_2$ augmentation	❌	❌	❌	❌	❌	❌	❌	0
Optimally Improving Cooperative Learning in a Social Setting	✅	✅	✅	❌	❌	❌	✅	4
Optimistic Multi-Agent Policy Gradient	✅	✅	✅	❌	❌	❌	✅	4
Optimization without Retraction on the Random Generalized Stiefel Manifold	❌	✅	✅	❌	❌	❌	✅	3
Optimizing Watermarks for Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty	✅	❌	✅	✅	❌	❌	✅	4
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift	✅	✅	✅	✅	✅	❌	✅	6
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble	❌	❌	✅	❌	✅	❌	✅	3
Out-of-Domain Generalization in Dynamical Systems Reconstruction	❌	✅	❌	❌	❌	❌	✅	2
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity	❌	✅	✅	✅	✅	❌	✅	5
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models	❌	✅	✅	✅	✅	❌	✅	5
Outlier-aware Slicing for Post-Training Quantization in Vision Transformer	✅	❌	✅	❌	❌	❌	✅	3
Outlier-robust Kalman Filtering through Generalised Bayes	✅	✅	✅	✅	❌	❌	✅	5
Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors	✅	✅	✅	✅	❌	❌	✅	5
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization	❌	✅	✅	✅	❌	✅	✅	5
Overcoming the Optimizer’s Curse: Obtaining Realistic Prescriptions from Neural Networks	✅	❌	✅	❌	✅	✅	✅	5
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning	❌	❌	✅	✅	❌	❌	✅	3
OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning	✅	❌	✅	✅	❌	❌	✅	4
PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models	❌	✅	✅	❌	❌	❌	✅	3
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning	❌	✅	✅	❌	✅	✅	✅	5
PAGER: Accurate Failure Characterization in Deep Regression Models	✅	❌	✅	✅	❌	❌	✅	4
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring	❌	✅	✅	✅	✅	✅	✅	6
PAPM: A Physics-aware Proxy Model for Process Systems	✅	✅	✅	✅	✅	❌	✅	6
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling	❌	✅	✅	❌	✅	❌	✅	4
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition	❌	✅	✅	❌	❌	❌	✅	3
PASOA- PArticle baSed Bayesian Optimal Adaptive design	✅	✅	✅	❌	✅	❌	✅	5
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming	❌	✅	✅	✅	✅	✅	✅	6
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation	✅	✅	✅	❌	✅	❌	✅	5
PGODE: Towards High-quality System Dynamics Modeling	✅	❌	✅	✅	✅	✅	✅	6
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning	✅	✅	✅	❌	✅	❌	✅	5
PID: Prompt-Independent Data Protection Against Latent Diffusion Models	❌	✅	✅	❌	❌	❌	✅	3
PIDformer: Transformer Meets Control Theory	❌	✅	✅	✅	❌	❌	✅	4
PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling	✅	✅	✅	❌	❌	❌	✅	4
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs	✅	❌	✅	❌	❌	❌	✅	3
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching	❌	✅	✅	✅	❌	❌	✅	4
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control	✅	✅	✅	❌	✅	❌	✅	5
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect	✅	✅	✅	✅	✅	❌	✅	6
Pairwise Alignment Improves Graph Domain Adaptation	✅	✅	✅	✅	✅	❌	✅	6
Parallel Affine Transformation Tuning of Markov Chain Monte Carlo	✅	✅	✅	❌	❌	❌	✅	4
Parallelized Spatiotemporal Slot Binding for Videos	✅	✅	✅	❌	❌	❌	✅	4
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation	✅	✅	✅	✅	✅	❌	✅	6
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations	✅	❌	❌	❌	❌	❌	❌	1
Parameter-Efficient Fine-Tuning with Controls	❌	❌	✅	❌	✅	❌	✅	3
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform	✅	✅	✅	✅	❌	❌	✅	5
Parameterized Physics-informed Neural Networks for Parameterized PDEs	❌	✅	✅	❌	✅	✅	✅	5
Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcalNP$-hard Problems	✅	❌	❌	❌	❌	❌	❌	1
Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling	✅	❌	✅	❌	✅	✅	✅	5
Partial Optimality in the Linear Ordering Problem	✅	✅	✅	❌	✅	✅	✅	6
Partially Stochastic Infinitely Deep Bayesian Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Particle Denoising Diffusion Sampler	✅	✅	✅	❌	✅	❌	✅	5
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models	❌	✅	✅	✅	✅	❌	✅	5
Path-Guided Particle-based Sampling	✅	✅	✅	❌	✅	❌	✅	5
Pausing Policy Learning in Non-stationary Reinforcement Learning	✅	❌	❌	❌	✅	❌	✅	3
PcLast: Discovering Plannable Continuous Latent States	✅	✅	✅	❌	❌	❌	✅	4
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning	✅	✅	✅	✅	❌	❌	✅	5
Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams	❌	✅	✅	❌	✅	❌	✅	4
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR	❌	✅	✅	✅	✅	❌	✅	5
Perfect Alignment May be Poisonous to Graph Contrastive Learning	❌	✅	✅	❌	❌	❌	✅	3
Performance Bounds for Active Binary Testing with Information Maximization	❌	❌	✅	❌	❌	❌	✅	2
Performative Prediction with Bandit Feedback: Learning through Reparameterization	✅	✅	❌	❌	❌	❌	❌	2
Perturb-and-Project: Differentially Private Similarities and Marginals	✅	❌	❌	❌	❌	❌	❌	1
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Physics and Lie symmetry informed Gaussian processes	❌	✅	❌	❌	❌	❌	✅	2
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction	❌	❌	❌	✅	❌	❌	✅	2
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification	✅	✅	❌	❌	✅	❌	✅	4
Pi-DUAL: Using privileged information to distinguish clean from noisy labels	❌	❌	✅	✅	✅	❌	✅	4
Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach	✅	✅	✅	✅	✅	✅	✅	7
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation	❌	❌	✅	✅	✅	❌	✅	4
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer	✅	❌	✅	❌	❌	❌	✅	3
Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners	✅	✅	✅	❌	❌	❌	✅	4
Plug-and-Play image restoration with Stochastic deNOising REgularization	✅	✅	✅	❌	✅	❌	✅	5
Plug-in Performative Optimization	✅	❌	✅	❌	❌	❌	✅	3
Pluvial Flood Emulation with Hydraulics-informed Message Passing	❌	✅	✅	✅	✅	❌	✅	5
PointMC: Multi-instance Point Cloud Registration based on Maximal Cliques	❌	❌	✅	✅	❌	❌	✅	3
Policy Evaluation for Variance in Average Reward Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Policy Learning for Balancing Short-Term and Long-Term Rewards	❌	✅	✅	❌	❌	❌	✅	3
Policy-conditioned Environment Models are More Generalizable	✅	✅	✅	❌	❌	❌	✅	4
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels	✅	✅	✅	✅	✅	❌	✅	6
Polynomial-based Self-Attention for Table Representation Learning	❌	✅	✅	✅	✅	✅	✅	6
Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction	❌	❌	❌	❌	❌	❌	❌	0
Position: A Call for Embodied AI	❌	❌	❌	❌	❌	❌	❌	0
Position: A Call to Action for a Human-Centered AutoML Paradigm	❌	❌	❌	❌	❌	❌	❌	0
Position: A Roadmap to Pluralistic Alignment	❌	❌	✅	❌	❌	❌	✅	2
Position: A Safe Harbor for AI Evaluation and Red Teaming	❌	❌	❌	❌	❌	❌	❌	0
Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research	❌	❌	❌	❌	❌	❌	❌	0
Position: AI/ML Influencers Have a Place in the Academic Process	❌	❌	❌	❌	❌	❌	❌	0
Position: Amazing Things Come From Having Many Good Models	❌	❌	✅	✅	❌	❌	❌	2
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience	✅	❌	❌	❌	❌	❌	❌	1
Position: Application-Driven Innovation in Machine Learning	❌	❌	❌	❌	❌	❌	❌	0
Position: Automatic Environment Shaping is the Next Frontier in RL	✅	✅	✅	❌	❌	❌	❌	3
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI	❌	❌	❌	❌	❌	❌	❌	0
Position: Benchmarking is Limited in Reinforcement Learning Research	❌	❌	✅	❌	❌	❌	✅	2
Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis	❌	❌	❌	❌	❌	❌	❌	0
Position: Building Guardrails for Large Language Models Requires Systematic Design	❌	❌	❌	❌	❌	❌	❌	0
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures	❌	❌	❌	❌	❌	❌	❌	0
Position: Compositional Generative Modeling: A Single Model is Not All You Need	❌	❌	✅	❌	❌	❌	❌	1
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining	❌	❌	✅	❌	❌	❌	❌	1
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities	❌	❌	❌	❌	❌	❌	❌	0
Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?	❌	❌	❌	❌	❌	❌	❌	0
Position: Data-driven Discovery with Large Generative Models	❌	❌	✅	❌	❌	❌	❌	1
Position: Do Not Explain Vision Models Without Context	❌	❌	✅	❌	❌	❌	❌	1
Position: Do pretrained Transformers Learn In-Context by Gradient Descent?	❌	❌	✅	❌	❌	❌	✅	2
Position: Embracing Negative Results in Machine Learning	❌	❌	❌	❌	❌	❌	❌	0
Position: Enforced Amnesia as a Way to Mitigate the Potential Risk of Silent Suffering in the Conscious AI	❌	❌	❌	❌	❌	❌	❌	0
Position: Evolving AI Collectives Enhance Human Diversity and Enable Self-Regulation	❌	❌	❌	❌	❌	❌	✅	1
Position: Explain to Question not to Justify	❌	❌	❌	❌	❌	❌	❌	0
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training	❌	✅	✅	❌	✅	❌	✅	4
Position: Foundation Agents as the Paradigm Shift for Decision Making	❌	❌	✅	❌	✅	❌	✅	3
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches	❌	❌	❌	❌	❌	❌	❌	0
Position: Future Directions in the Theory of Graph Machine Learning	❌	❌	❌	❌	❌	❌	❌	0
Position: Graph Foundation Models Are Already Here	❌	❌	✅	❌	❌	❌	❌	1
Position: Insights from Survey Methodology can Improve Training Data	❌	❌	❌	❌	❌	❌	❌	0
Position: Intent-aligned AI Systems Must Optimize for Agency Preservation	❌	❌	❌	❌	❌	❌	✅	1
Position: Is machine learning good or bad for the natural sciences?	❌	✅	✅	✅	❌	❌	✅	4
Position: Key Claims in LLM Research Have a Long Tail of Footnotes	❌	❌	❌	❌	❌	❌	❌	0
Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks	❌	❌	✅	❌	❌	❌	❌	1
Position: Levels of AGI for Operationalizing Progress on the Path to AGI	❌	❌	❌	❌	❌	❌	❌	0
Position: Leverage Foundational Models for Black-Box Optimization	✅	❌	❌	❌	❌	❌	❌	1
Position: Machine Learning-powered Assessments of the EU Digital Services Act Aid Quantify Policy Impacts on Online Harms	❌	❌	❌	❌	❌	❌	❌	0
Position: Measure Dataset Diversity, Don’t Just Claim It	❌	❌	✅	❌	❌	❌	❌	1
Position: Mission Critical – Satellite Data is a Distinct Modality in Machine Learning	❌	❌	✅	❌	❌	❌	❌	1
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI	❌	❌	❌	❌	❌	❌	❌	0
Position: On the Possibilities of AI-Generated Text Detection	❌	❌	✅	❌	❌	❌	❌	1
Position: On the Societal Impact of Open Foundation Models	❌	❌	❌	❌	❌	❌	❌	0
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence	❌	❌	❌	❌	❌	❌	❌	0
Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy	❌	❌	✅	❌	❌	❌	❌	1
Position: Optimization in SciML Should Employ the Function Space Geometry	❌	❌	❌	❌	❌	❌	❌	0
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?	❌	✅	✅	✅	❌	❌	✅	4
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination	❌	✅	✅	✅	❌	❌	✅	4
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases	✅	✅	✅	✅	❌	❌	❌	4
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems	❌	✅	✅	❌	✅	❌	✅	4
Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation	❌	❌	❌	❌	❌	❌	❌	0
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized	✅	✅	✅	❌	❌	❌	✅	4
Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback	❌	❌	❌	❌	❌	❌	❌	0
Position: Social Environment Design Should be Further Developed for AI-based Policy-Making	❌	✅	❌	❌	❌	❌	✅	2
Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI	❌	✅	✅	❌	❌	❌	❌	2
Position: Stop Making Unscientific AGI Performance Claims	❌	✅	✅	✅	✅	❌	✅	5
Position: Technical Research and Talent is Needed for Effective AI Governance	❌	❌	❌	❌	❌	❌	❌	0
Position: Tensor Networks are a Valuable Asset for Green AI	❌	❌	✅	❌	❌	❌	❌	1
Position: The Causal Revolution Needs Scientific Pragmatism	❌	❌	❌	❌	❌	❌	❌	0
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning	❌	❌	✅	✅	✅	❌	✅	4
Position: The Platonic Representation Hypothesis	❌	✅	✅	✅	❌	❌	❌	3
Position: The Reasonable Person Standard for AI	❌	❌	❌	❌	❌	❌	❌	0
Position: Topological Deep Learning is the New Frontier for Relational Learning	❌	❌	❌	❌	❌	❌	❌	0
Position: Towards Implicit Prompt For Text-To-Image Models	❌	✅	✅	❌	❌	❌	✅	3
Position: Towards Unified Alignment Between Agents, Humans, and Environment	✅	✅	✅	✅	❌	✅	✅	6
Position: TrustLLM: Trustworthiness in Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Position: Understanding LLMs Requires More Than Statistical Generalization	❌	✅	❌	❌	❌	✅	✅	3
Position: Video as the New Language for Real-World Decision Making	❌	❌	✅	❌	❌	❌	✅	2
Position: What Can Large Language Models Tell Us about Time Series Analysis	✅	❌	✅	❌	❌	❌	❌	2
Position: What makes an image realistic?	❌	❌	❌	❌	❌	❌	❌	0
Position: Why Tabular Foundation Models Should Be a Research Priority	❌	❌	❌	❌	❌	❌	❌	0
Position: Why We Must Rethink Empirical Research in Machine Learning	❌	❌	❌	❌	❌	❌	❌	0
Position: Will we run out of data? Limits of LLM scaling based on human-generated data	❌	✅	✅	❌	❌	❌	✅	3
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning	❌	✅	✅	✅	✅	❌	✅	5
Positive Concave Deep Equilibrium Models	❌	✅	✅	❌	✅	❌	✅	4
Positive and Unlabeled Learning with Controlled Probability Boundary Fence	❌	❌	✅	✅	✅	❌	✅	4
Post-hoc Part-Prototype Networks	❌	❌	✅	❌	❌	❌	✅	2
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds	✅	❌	✅	❌	❌	❌	✅	3
Potential Based Diffusion Motion Planning	✅	✅	✅	❌	✅	✅	✅	6
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs	✅	✅	✅	✅	✅	❌	✅	6
Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory	✅	✅	✅	❌	❌	❌	✅	4
Practical Performance Guarantees for Pipelined DNN Inference	✅	❌	✅	❌	✅	✅	✅	5
Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input	✅	✅	✅	❌	❌	❌	✅	4
Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains	❌	❌	✅	✅	✅	❌	✅	4
Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms	❌	✅	✅	❌	❌	❌	✅	3
Predicting Dose-Response Curves with Deep Neural Networks	❌	✅	✅	✅	✅	✅	✅	6
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs	❌	✅	✅	✅	✅	❌	✅	5
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg	❌	❌	❌	❌	❌	❌	❌	0
Prediction-powered Generalization of Causal Inferences	✅	✅	❌	✅	❌	❌	✅	4
Predictive Coding beyond Correlations	✅	❌	✅	❌	❌	❌	✅	3
Predictive Dynamic Fusion	❌	✅	✅	❌	✅	❌	✅	4
Predictive Linear Online Tracking for Unknown Targets	✅	✅	❌	❌	✅	❌	✅	4
Predictive Performance Comparison of Decision Policies Under Confounding	✅	✅	✅	✅	❌	❌	✅	5
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data	✅	✅	✅	❌	✅	❌	✅	5
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models	✅	✅	✅	✅	✅	✅	✅	7
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss	❌	✅	✅	❌	✅	❌	✅	4
Premise Order Matters in Reasoning with Large Language Models	❌	❌	✅	❌	❌	❌	✅	2
Preventing Model Collapse in Gaussian Process Latent Variable Models	✅	✅	✅	✅	❌	❌	✅	5
Pricing with Contextual Elasticity and Heteroscedastic Valuation	✅	❌	❌	❌	❌	❌	✅	2
Principled Gradient-Based MCMC for Conditional Sampling of Text	❌	❌	✅	❌	❌	❌	✅	2
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF	✅	❌	❌	❌	❌	❌	✅	2
Principled Preferential Bayesian Optimization	✅	✅	✅	❌	✅	❌	✅	5
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis	✅	✅	✅	❌	❌	❌	✅	4
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses	✅	❌	❌	❌	❌	❌	✅	2
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models	❌	✅	✅	✅	✅	❌	✅	5
Privacy Attacks in Decentralized Learning	✅	✅	✅	❌	❌	❌	✅	4
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models	❌	✅	✅	❌	❌	✅	✅	4
Privacy Preserving Adaptive Experiment Design	✅	❌	❌	❌	❌	❌	✅	2
Privacy Profiles for Private Selection	❌	❌	✅	❌	❌	❌	✅	2
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent	✅	✅	✅	❌	✅	❌	✅	5
Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption	✅	❌	✅	✅	✅	✅	✅	6
Privacy-Preserving Instructions for Aligning Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation	✅	❌	❌	❌	❌	❌	✅	2
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses	✅	❌	✅	❌	❌	❌	✅	3
Private Truly-Everlasting Robust-Prediction	✅	❌	❌	❌	❌	❌	❌	1
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages	✅	❌	❌	❌	❌	❌	❌	1
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems	✅	❌	✅	❌	❌	❌	✅	3
Privately Learning Smooth Distributions on the Hypercube by Projections	❌	❌	❌	❌	❌	❌	❌	0
Proactive DP: A Multiple Target Optimization Framework for DP-SGD	✅	❌	✅	❌	❌	❌	✅	3
Proactive Detection of Voice Cloning with Localized Watermarking	❌	✅	✅	✅	✅	❌	✅	5
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models	✅	❌	✅	❌	✅	❌	✅	4
Probabilistic Constrained Reinforcement Learning with Formal Interpretability	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Generating Circuits - Demystified	❌	❌	❌	❌	❌	❌	❌	0
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Modeling of Interpersonal Coordination Processes	❌	✅	✅	✅	✅	✅	✅	6
Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model	✅	❌	✅	❌	❌	❌	✅	3
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization	❌	✅	✅	❌	❌	❌	✅	3
Prodigy: An Expeditiously Adaptive Parameter-Free Learner	✅	✅	✅	❌	❌	❌	✅	4
Profile Reconstruction from Private Sketches	✅	❌	❌	❌	❌	❌	❌	1
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions	✅	✅	✅	❌	❌	❌	✅	4
Projecting Molecules into Synthesizable Chemical Spaces	✅	✅	✅	✅	❌	❌	✅	5
Projection-Free Online Convex Optimization with Time-Varying Constraints	✅	❌	❌	❌	❌	❌	❌	1
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization	✅	❌	✅	❌	✅	❌	✅	4
Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE	✅	❌	✅	✅	✅	❌	✅	5
Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines	❌	✅	✅	❌	✅	❌	✅	4
Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation	✅	❌	❌	❌	❌	❌	❌	1
Prompt Sketching for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Prompt-based Visual Alignment for Zero-shot Policy Transfer	❌	❌	✅	✅	✅	❌	✅	4
Prompt-guided Precise Audio Editing with Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Prompt-tuning Latent Diffusion Models for Inverse Problems	✅	❌	✅	❌	✅	❌	✅	4
Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution	❌	❌	✅	✅	❌	❌	✅	3
Prompting a Pretrained Transformer Can Be a Universal Approximator	❌	❌	❌	❌	❌	❌	❌	0
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models	✅	✅	✅	❌	❌	❌	❌	3
Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts	❌	✅	✅	❌	✅	❌	✅	4
Prospective Side Information for Latent MDPs	✅	❌	❌	❌	❌	❌	❌	1
Prospector Heads: Generalized Feature Attribution for Large Models & Data	✅	✅	✅	✅	✅	❌	✅	6
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models	✅	❌	✅	✅	✅	❌	✅	5
Proteus: Exploring Protein Structure Generation for Enhanced Designability and Efficiency	✅	✅	✅	❌	✅	❌	✅	5
ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data	✅	✅	✅	✅	✅	❌	✅	6
Prototypical Transformer As Unified Motion Learners	✅	✅	✅	✅	✅	❌	✅	6
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective	❌	✅	✅	✅	✅	❌	✅	5
Provable Contrastive Continual Learning	✅	❌	✅	❌	❌	❌	✅	3
Provable Interactive Learning with Hindsight Instruction Feedback	✅	✅	❌	❌	✅	❌	✅	4
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks	❌	❌	❌	❌	❌	❌	✅	1
Provable Privacy with Non-Private Pre-Processing	✅	✅	❌	❌	❌	❌	✅	3
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation	✅	❌	❌	❌	❌	❌	✅	2
Provably Better Explanations with Optimized Aggregation of Feature Attributions	❌	✅	✅	✅	✅	❌	✅	5
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret	✅	❌	❌	❌	❌	❌	❌	1
Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization	✅	❌	❌	❌	✅	❌	✅	3
Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation	✅	❌	❌	❌	❌	❌	✅	2
Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback	✅	❌	✅	❌	❌	❌	✅	3
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples	✅	❌	❌	❌	❌	❌	✅	2
Provably Robust DPO: Aligning Language Models with Noisy Feedback	✅	✅	✅	❌	❌	❌	✅	4
Provably Scalable Black-Box Variational Inference with Structured Variational Families	❌	❌	✅	❌	✅	❌	✅	3
PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency	❌	❌	✅	✅	❌	❌	✅	3
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models	✅	❌	❌	❌	❌	❌	✅	2
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation	✅	✅	✅	❌	✅	❌	✅	5
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders	✅	✅	✅	❌	✅	❌	✅	5
Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation	❌	✅	✅	❌	✅	✅	✅	5
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making	✅	✅	✅	✅	✅	❌	✅	6
Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels	❌	❌	✅	❌	✅	❌	✅	3
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models	❌	✅	✅	❌	❌	❌	✅	3
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent	✅	✅	✅	❌	❌	❌	✅	4
Q-value Regularized Transformer for Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
QBMK: Quantum-based Matching Kernels for Un-attributed Graphs	❌	❌	✅	✅	❌	❌	✅	3
QORA: Zero-Shot Transfer via Interpretable Object-Relational Model Learning	✅	✅	❌	❌	❌	❌	✅	3
QUEST: Query-Aware Sparsity for Efficient Long-Context LLM Inference	✅	✅	✅	❌	✅	✅	✅	6
QuIP$#$: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks	✅	✅	✅	✅	✅	❌	✅	6
QuRating: Selecting High-Quality Data for Training Language Models	❌	✅	✅	✅	✅	❌	✅	5
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization	✅	✅	✅	❌	❌	✅	✅	5
Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics	✅	✅	❌	❌	❌	✅	✅	4
Quality-Diversity with Limited Resources	✅	✅	✅	❌	✅	❌	✅	5
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design	✅	✅	✅	❌	❌	❌	✅	4
Quantum Algorithm for Online Exp-concave Optimization	✅	❌	❌	❌	❌	❌	❌	1
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization	✅	❌	❌	❌	❌	❌	❌	1
Quantum Implicit Neural Representations	❌	✅	✅	❌	❌	❌	✅	3
Quantum Positional Encodings for Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Quantum Theory and Application of Contextual Optimal Transport	❌	❌	✅	✅	✅	✅	✅	5
Quasi-Monte Carlo Features for Kernel Approximation	❌	❌	✅	❌	❌	✅	✅	3
R2E: Turning any Github Repository into a Programming Agent Environment	❌	✅	✅	❌	❌	❌	✅	3
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation	❌	✅	❌	✅	✅	❌	✅	4
REMEDI: Corrective Transformations for Improved Neural Entropy Estimation	✅	✅	✅	✅	✅	❌	✅	6
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates	❌	✅	✅	✅	✅	❌	✅	5
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation	✅	✅	✅	❌	✅	✅	✅	6
RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences	✅	✅	✅	❌	❌	❌	✅	4
RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning	✅	✅	❌	❌	✅	❌	✅	4
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback	✅	❌	✅	❌	❌	❌	✅	3
RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback	❌	❌	✅	✅	❌	❌	✅	3
RLVF: Learning from Verbal Feedback without Overgeneralization	❌	❌	✅	✅	❌	❌	✅	3
RMIB: Representation Matching Information Bottleneck for Matching Text Representations	❌	✅	✅	✅	❌	❌	✅	4
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching	✅	✅	✅	✅	✅	❌	✅	6
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples	✅	✅	✅	✅	✅	❌	✅	6
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency	✅	❌	❌	❌	❌	❌	✅	2
Random Latent Exploration for Deep Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning	❌	✅	✅	✅	❌	❌	✅	4
Random Scaling and Momentum for Non-smooth Non-convex Optimization	✅	❌	✅	❌	❌	❌	✅	3
Random features models: a way to study the success of naive imputation	❌	❌	❌	❌	❌	❌	❌	0
Random matrix theory improved Fréchet mean of symmetric positive definite matrices	✅	✅	✅	❌	❌	❌	✅	4
Randomized Confidence Bounds for Stochastic Partial Monitoring	✅	✅	✅	❌	✅	❌	✅	5
Ranking-based Client Imitation Selection for Efficient Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze	✅	✅	❌	❌	✅	❌	✅	4
Rate-Optimal Policy Optimization for Linear Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge	✅	❌	✅	✅	✅	❌	✅	5
ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation	❌	✅	✅	❌	❌	❌	✅	3
ReGAL: Refactoring Programs to Discover Generalizable Abstractions	✅	✅	✅	✅	❌	✅	✅	6
ReLU Network with Width $d+\mathcalO(1)$ Can Achieve Optimal Approximation Rate	❌	❌	❌	❌	❌	❌	❌	0
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages	✅	✅	✅	❌	✅	❌	✅	5
ReLUs Are Sufficient for Learning Implicit Neural Representations	❌	✅	✅	❌	❌	❌	✅	3
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization	✅	✅	✅	✅	❌	❌	✅	5
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents	✅	✅	✅	❌	❌	❌	✅	4
Receptive Fields As Experts in Convolutional Neural Architectures	❌	❌	✅	✅	✅	❌	✅	4
ReconBoost: Boosting Can Achieve Modality Reconcilement	✅	✅	✅	✅	✅	❌	✅	6
Recovering Labels from Local Updates in Federated Learning	✅	❌	✅	❌	❌	✅	✅	4
Recovering the Pre-Fine-Tuning Weights of Generative Models	✅	✅	✅	✅	✅	❌	✅	6
Recurrent Distance Filtering for Graph Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Recurrent Early Exits for Federated Learning with Heterogeneous Clients	❌	✅	✅	✅	❌	❌	✅	4
Reducing Balancing Error for Causal Inference via Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation	✅	✅	✅	❌	✅	❌	✅	5
Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation	✅	❌	✅	❌	❌	❌	✅	3
Reducing sequential change detection to sequential estimation	✅	❌	❌	❌	❌	❌	✅	2
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion	✅	✅	✅	❌	✅	❌	✅	5
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations	✅	❌	✅	❌	✅	❌	✅	4
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints	✅	✅	✅	❌	✅	❌	✅	5
Refining Minimax Regret for Unsupervised Environment Design	✅	✅	✅	❌	❌	❌	✅	4
Reflected Flow Matching	✅	✅	✅	✅	✅	❌	✅	6
Reflective Policy Optimization	✅	✅	✅	❌	❌	❌	✅	4
Regression Learning with Limited Observations of Multivariate Outcomes and Features	✅	❌	✅	✅	❌	❌	✅	4
Regression with Multi-Expert Deferral	❌	❌	✅	✅	❌	❌	✅	3
Regularized Q-learning through Robust Averaging	❌	✅	✅	❌	❌	❌	✅	3
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning	❌	❌	✅	✅	✅	❌	✅	4
Reinforcement Learning and Regret Bounds for Admission Control	✅	✅	❌	❌	✅	❌	✅	4
Reinforcement Learning from Reachability Specifications: PAC Guarantees with Expected Conditional Distance	✅	❌	❌	❌	❌	❌	❌	1
Reinforcement Learning within Tree Search for Fast Macro Placement	✅	✅	✅	❌	✅	❌	✅	5
Reinformer: Max-Return Sequence Modeling for Offline RL	✅	✅	✅	❌	❌	❌	✅	4
Rejuvenating image-GPT as Strong Visual Representation Learners	❌	✅	✅	✅	❌	❌	✅	4
Relational DNN Verification With Cross Executional Bound Refinement	✅	✅	✅	❌	✅	✅	✅	6
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective	✅	❌	✅	✅	✅	❌	✅	5
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise	❌	✅	✅	✅	❌	❌	✅	4
Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering	✅	❌	✅	❌	✅	❌	✅	4
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making	✅	✅	❌	❌	✅	❌	✅	4
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation	✅	✅	✅	✅	❌	❌	✅	5
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Repeat After Me: Transformers are Better than State Space Models at Copying	✅	❌	✅	❌	✅	❌	✅	4
Replicable Learning of Large-Margin Halfspaces	✅	❌	❌	❌	❌	❌	❌	1
Repoformer: Selective Retrieval for Repository-Level Code Completion	✅	❌	✅	✅	✅	❌	✅	5
Representation Surgery for Multi-Task Model Merging	❌	✅	✅	✅	❌	❌	✅	4
Representation Surgery: Theory and Practice of Affine Steering	❌	✅	✅	❌	❌	✅	✅	4
Representing Molecules as Random Walks Over Interpretable Grammars	✅	✅	✅	❌	❌	❌	✅	4
Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling	✅	❌	✅	❌	❌	❌	✅	3
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast	✅	✅	✅	✅	✅	❌	✅	6
Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems	✅	❌	✅	✅	✅	❌	✅	5
Residual Quantization with Implicit Neural Codebooks	❌	✅	✅	✅	✅	✅	✅	6
Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration	✅	❌	✅	✅	✅	❌	✅	5
Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree	✅	✅	✅	❌	✅	❌	✅	5
Restoring balance: principled under/oversampling of data for optimal classification	❌	✅	✅	❌	❌	❌	✅	3
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten	❌	❌	✅	❌	❌	❌	✅	2
Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD	✅	✅	✅	✅	✅	✅	✅	7
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits	❌	❌	✅	✅	❌	❌	✅	3
Rethinking Decision Transformer via Hierarchical Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
Rethinking Generative Large Language Model Evaluation for Semantic Comprehension	❌	❌	❌	❌	✅	✅	✅	3
Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective	❌	✅	✅	❌	✅	❌	✅	4
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data	✅	✅	✅	✅	❌	❌	✅	5
Rethinking Momentum Knowledge Distillation in Online Continual Learning	✅	✅	✅	❌	✅	❌	✅	5
Rethinking Optimization and Architecture for Tiny Language Models	❌	✅	✅	✅	✅	❌	✅	5
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion	✅	❌	✅	✅	❌	❌	✅	4
Rethinking Transformers in Solving POMDPs	❌	✅	✅	❌	❌	❌	✅	3
Rethinking the Flat Minima Searching in Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Retrieval Across Any Domains via Large-scale Pre-trained Model	❌	❌	✅	❌	✅	❌	✅	3
Retrieval-Augmented Score Distillation for Text-to-3D Generation	❌	✅	✅	❌	✅	✅	✅	5
Revealing Vision-Language Integration in the Brain with Multimodal Networks	❌	✅	✅	✅	❌	❌	✅	4
Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness	❌	✅	✅	✅	❌	❌	✅	4
Revisit the Essence of Distilling Knowledge through Calibration	❌	❌	✅	❌	❌	❌	✅	2
Revisiting Character-level Adversarial Attacks for Language Models	✅	✅	✅	✅	✅	❌	✅	6
Revisiting Context Aggregation for Image Matting	❌	✅	✅	✅	✅	✅	✅	6
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity	✅	❌	❌	❌	❌	❌	❌	1
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark	✅	✅	✅	❌	✅	❌	✅	5
Revisiting the Power of Prompt for Visual Tuning	❌	✅	✅	✅	❌	❌	✅	4
Revisiting the Role of Language Priors in Vision-Language Models	❌	❌	✅	✅	✅	❌	✅	4
Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling	❌	✅	✅	✅	✅	❌	✅	5
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences	❌	❌	❌	❌	❌	❌	❌	0
Reward Shaping for Reinforcement Learning with An Assistant Reward Agent	✅	✅	✅	❌	❌	❌	✅	4
Reward-Free Kernel-Based Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment	❌	✅	✅	❌	✅	❌	✅	4
Reweighted Solutions for Weighted Low Rank Approximation	✅	✅	✅	❌	✅	❌	✅	5
Rich-Observation Reinforcement Learning with Continuous Latent Dynamics	✅	❌	✅	❌	❌	❌	✅	3
Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity	✅	❌	✅	❌	✅	❌	✅	4
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models	✅	✅	✅	❌	✅	❌	✅	5
Riemannian coordinate descent algorithms on matrix manifolds	✅	✅	✅	❌	✅	❌	✅	5
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content	✅	✅	✅	✅	✅	❌	✅	6
Risk Aware Benchmarking of Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds	❌	❌	❌	❌	❌	❌	❌	0
Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient	✅	❌	✅	❌	❌	❌	✅	3
Risk-Sensitive Reward-Free Reinforcement Learning with CVaR	✅	❌	❌	❌	❌	❌	✅	2
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation	✅	✅	✅	❌	✅	❌	✅	5
RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis	✅	❌	✅	❌	❌	❌	✅	3
RoboDreamer: Learning Compositional World Models for Robot Imagination	✅	❌	✅	❌	✅	❌	✅	4
RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation	❌	❌	✅	❌	✅	❌	✅	3
RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models	❌	❌	✅	❌	✅	❌	✅	3
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models	❌	✅	✅	✅	❌	❌	✅	4
Robust Classification via a Single Diffusion Model	✅	✅	✅	❌	✅	❌	✅	5
Robust Data-driven Prescriptiveness Optimization	✅	✅	❌	✅	✅	✅	❌	5
Robust Graph Matching when Nodes are Corrupt	✅	❌	❌	❌	❌	❌	❌	1
Robust Inverse Constrained Reinforcement Learning under Model Misspecification	✅	✅	✅	❌	❌	❌	✅	4
Robust Inverse Graphics via Probabilistic Inference	✅	✅	✅	✅	✅	❌	✅	6
Robust Learning-Augmented Dictionaries	❌	❌	✅	❌	❌	❌	✅	2
Robust Multi-Task Learning with Excess Risks	✅	✅	✅	✅	✅	❌	✅	6
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space	✅	✅	✅	❌	❌	❌	✅	4
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination	✅	❌	❌	❌	❌	❌	❌	1
Robust Stable Spiking Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Robust Universal Adversarial Perturbations	✅	❌	✅	❌	✅	❌	✅	4
Robust Yet Efficient Conformal Prediction Sets	✅	✅	✅	✅	✅	❌	✅	6
Robust and Conjugate Gaussian Process Regression	❌	✅	✅	✅	✅	❌	✅	5
Robustly Learning Single-Index Models via Alignment Sharpness	✅	❌	❌	❌	❌	❌	❌	1
Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data	❌	✅	✅	❌	✅	❌	✅	4
Robustness of Nonlinear Representation Learning	❌	❌	❌	❌	❌	❌	❌	0
Rolling Diffusion Models	✅	❌	✅	❌	❌	❌	✅	3
Roping in Uncertainty: Robustness and Regularization in Markov Games	❌	❌	❌	❌	❌	❌	❌	0
Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Run-Time Task Composition with Safety Semantics	❌	❌	✅	❌	✅	❌	✅	3
Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas	❌	❌	✅	❌	❌	❌	❌	1
S$Ω$I: Score-based O-INFORMATION Estimation	✅	✅	✅	❌	❌	❌	✅	4
S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning	❌	✅	✅	✅	✅	✅	✅	6
S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video	✅	✅	✅	❌	✅	❌	✅	5
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation	✅	✅	✅	✅	✅	❌	✅	6
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation	❌	❌	✅	❌	❌	❌	✅	2
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention	✅	✅	✅	✅	❌	❌	✅	5
SAPG: Split and Aggregate Policy Gradients	✅	✅	✅	❌	❌	❌	✅	4
SCoRe: Submodular Combinatorial Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic	❌	❌	✅	✅	✅	❌	✅	4
SHINE: Shielding Backdoors in Deep Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
SILVER: Single-loop variance reduction and application to federated learning	✅	❌	✅	❌	✅	✅	✅	5
SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting	❌	❌	✅	✅	✅	❌	✅	4
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization	❌	✅	✅	✅	✅	❌	✅	5
SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks	✅	✅	✅	✅	✅	❌	✅	6
SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter	✅	✅	✅	✅	✅	❌	✅	6
SMaRt: Improving GANs with Score Matching Regularity	❌	✅	✅	❌	✅	❌	✅	4
SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity	✅	✅	✅	✅	✅	✅	✅	7
SPADE: Sparsity-Guided Debugging for Deep Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models	❌	❌	✅	❌	✅	❌	✅	3
SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification	❌	❌	❌	❌	❌	❌	✅	1
STEER: Assessing the Economic Rationality of Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment	✅	✅	✅	❌	✅	❌	✅	5
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP	✅	❌	✅	❌	❌	❌	✅	3
Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants	✅	❌	❌	❌	❌	❌	✅	2
Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation	✅	❌	❌	❌	❌	❌	✅	2
Safe and Robust Subgame Exploitation in Imperfect Information Games	❌	❌	✅	❌	❌	❌	✅	2
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Saliency strikes back: How filtering out high frequencies improves white-box explanations	❌	❌	✅	❌	✅	❌	❌	2
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data	❌	❌	✅	❌	❌	❌	✅	2
Sample Complexity Bounds for Estimating Probability Divergences under Invariances	❌	❌	❌	❌	❌	❌	❌	0
Sample as you Infer: Predictive Coding with Langevin Dynamics	✅	❌	✅	❌	✅	❌	✅	4
Sample-Efficient Multiagent Reinforcement Learning with Reset Replay	✅	✅	✅	❌	❌	✅	✅	5
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty	✅	❌	❌	❌	❌	❌	❌	1
Sample-specific Masks for Visual Reprogramming-based Prompting	✅	✅	✅	✅	✅	❌	✅	6
Sampling in Unit Time with Kernel Fisher-Rao Flow	❌	✅	❌	❌	✅	❌	✅	3
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models	❌	❌	❌	❌	❌	❌	❌	0
Sampling-based Multi-dimensional Recalibration	✅	✅	✅	✅	✅	❌	✅	6
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features	✅	❌	✅	❌	❌	❌	✅	3
Scalable AI Safety via Doubly-Efficient Debate	✅	✅	❌	❌	❌	✅	❌	3
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers	❌	✅	✅	❌	✅	❌	✅	4
Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation	✅	❌	✅	❌	✅	❌	✅	4
Scalable Online Exploration via Coverability	✅	✅	✅	❌	❌	❌	✅	4
Scalable Pre-training of Large Autoregressive Image Models	❌	✅	✅	✅	❌	❌	✅	4
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs	✅	✅	✅	❌	❌	❌	✅	4
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport	✅	❌	✅	❌	✅	❌	✅	4
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency	❌	✅	✅	✅	✅	❌	✅	5
Scale-Free Image Keypoints Using Differentiable Persistent Homology	❌	✅	✅	✅	✅	❌	✅	5
Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training	❌	✅	✅	❌	✅	❌	✅	4
Scaling Down Deep Learning with MNIST-1D	❌	✅	✅	✅	❌	❌	✅	4
Scaling Exponents Across Parameterizations and Optimizers	❌	❌	✅	❌	❌	❌	✅	2
Scaling Laws for Fine-Grained Mixture of Experts	❌	✅	✅	❌	✅	❌	✅	4
Scaling Laws for the Value of Individual Data Points in Machine Learning	❌	✅	✅	❌	❌	❌	✅	3
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis	✅	✅	✅	✅	❌	❌	✅	5
Scaling Tractable Probabilistic Circuits: A Systems Perspective	✅	✅	✅	✅	✅	❌	✅	6
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency	✅	❌	✅	✅	✅	❌	✅	5
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code	✅	❌	✅	❌	❌	❌	✅	3
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models	❌	✅	✅	✅	❌	❌	✅	4
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation	✅	✅	✅	❌	✅	❌	✅	5
Score-Based Causal Discovery of Latent Variable Causal Models	✅	❌	❌	❌	❌	❌	✅	2
Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation	❌	✅	✅	✅	✅	❌	✅	5
SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets	✅	✅	✅	❌	✅	✅	✅	6
Second-Order Uncertainty Quantification: A Distance-Based Approach	❌	✅	❌	❌	❌	❌	❌	1
See More Details: Efficient Image Super-Resolution by Experts Mining	✅	✅	✅	❌	✅	❌	✅	5
Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference	✅	✅	✅	❌	✅	❌	✅	5
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic	✅	❌	✅	❌	✅	❌	✅	4
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching	✅	✅	✅	❌	❌	❌	✅	4
Selecting Large Language Model to Fine-tune via Rectified Scaling Law	✅	✅	✅	✅	✅	❌	✅	6
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup	❌	❌	✅	✅	✅	❌	✅	4
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation	❌	✅	✅	❌	✅	❌	✅	4
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes	❌	✅	✅	✅	✅	❌	✅	5
Self-Composing Policies for Scalable Continual Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction	✅	❌	✅	✅	✅	❌	✅	5
Self-Correcting Self-Consuming Loops for Generative Model Training	✅	✅	✅	❌	❌	❌	✅	4
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning	✅	❌	✅	✅	✅	❌	✅	5
Self-Infilling Code Generation	✅	❌	✅	❌	❌	❌	✅	3
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models	✅	✅	✅	❌	✅	❌	✅	5
Self-Rewarding Language Models	❌	❌	✅	✅	❌	❌	✅	3
Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation	❌	✅	❌	❌	✅	❌	✅	3
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity	❌	✅	✅	✅	✅	❌	✅	5
Self-attention Networks Localize When QK-eigenspectrum Concentrates	❌	❌	✅	❌	❌	✅	✅	3
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources	✅	❌	✅	✅	❌	❌	✅	4
SelfIE: Self-Interpretation of Large Language Model Embeddings	❌	❌	✅	✅	✅	❌	✅	4
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations	✅	❌	✅	❌	✅	❌	✅	4
Semantic-Aware Human Object Interaction Image Generation	✅	✅	✅	❌	✅	❌	✅	5
Semantically-correlated memories in a dense associative model	❌	✅	✅	❌	✅	❌	✅	4
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach	✅	❌	✅	❌	✅	❌	✅	4
Sequential Disentanglement by Extracting Static Information From A Single Sequence Element	❌	✅	✅	✅	❌	❌	✅	4
Sequential Kernel Goodness-of-fit Testing	✅	❌	❌	❌	❌	❌	✅	2
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models	✅	✅	✅	✅	❌	❌	✅	5
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss	❌	❌	❌	❌	❌	❌	❌	0
Sharpness-Aware Data Generation for Zero-shot Quantization	✅	❌	✅	❌	❌	❌	✅	3
Shifted Interpolation for Differential Privacy	❌	✅	✅	✅	❌	❌	✅	4
Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences	❌	❌	✅	✅	✅	❌	✅	4
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs	❌	✅	✅	❌	❌	❌	✅	3
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States	✅	✅	✅	✅	❌	❌	✅	5
SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network	✅	✅	✅	❌	✅	❌	✅	5
Sign Rank Limitations for Inner Product Graph Decoders	❌	❌	✅	❌	✅	❌	✅	3
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs	❌	✅	✅	✅	✅	❌	✅	5
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding	✅	❌	✅	❌	❌	❌	✅	3
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning	✅	✅	✅	❌	❌	❌	✅	4
Simple Ingredients for Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Simple linear attention language models balance the recall-throughput tradeoff	✅	✅	✅	❌	✅	❌	✅	5
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data	❌	✅	✅	✅	❌	❌	✅	4
Simplicity Bias via Global Convergence of Sharpness Minimization	❌	❌	❌	❌	❌	❌	✅	1
Simulation of Graph Algorithms with Looped Transformers	✅	❌	✅	✅	❌	❌	✅	4
Simulation-Based Inference with Quantile Regression	✅	✅	✅	✅	✅	❌	✅	6
Simultaneous identification of models and parameters of scientific simulators	✅	✅	✅	✅	✅	✅	✅	7
Single-Model Attribution of Generative Models Through Final-Layer Inversion	❌	✅	✅	✅	✅	❌	✅	5
Single-Trajectory Distributionally Robust Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection	❌	✅	✅	❌	✅	✅	✅	5
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills	✅	✅	✅	❌	❌	❌	✅	4
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals	❌	✅	❌	✅	✅	❌	✅	4
Sliced Wasserstein with Random-Path Projecting Directions	✅	✅	✅	❌	✅	❌	✅	5
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates	✅	✅	✅	❌	✅	✅	✅	6
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices	✅	❌	✅	❌	✅	❌	✅	4
Slicing Mutual Information Generalization Bounds for Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Slot Abstractors: Toward Scalable Abstract Visual Reasoning	✅	✅	✅	✅	✅	❌	✅	6
Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks	✅	✅	✅	❌	✅	❌	✅	5
Small-loss Adaptive Regret for Online Convex Optimization	✅	❌	❌	❌	❌	❌	❌	1
Smooth Min-Max Monotonic Networks	❌	✅	✅	✅	✅	❌	✅	5
Smooth Tchebycheff Scalarization for Multi-Objective Optimization	✅	✅	✅	✅	❌	❌	✅	5
Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence	✅	✅	✅	❌	✅	❌	✅	5
Smoothness Adaptive Hypothesis Transfer Learning	✅	✅	✅	✅	❌	❌	✅	5
Sobolev Space Regularised Pre Density Models	✅	✅	✅	❌	✅	❌	✅	5
Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration	✅	✅	✅	✅	✅	✅	✅	7
Soft Prompt Recovers Compressed LLMs, Transferably	❌	✅	✅	✅	✅	✅	✅	6
Solving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game Approach	✅	❌	✅	❌	❌	❌	✅	3
Solving Poisson Equations using Neural Walk-on-Spheres	✅	✅	❌	❌	✅	❌	✅	4
SparQ Attention: Bandwidth-Efficient LLM Inference	✅	✅	✅	❌	✅	✅	✅	6
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once	✅	✅	✅	✅	✅	❌	✅	6
Sparse Dimensionality Reduction Revisited	❌	❌	❌	❌	❌	❌	❌	0
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference	✅	❌	✅	✅	✅	❌	✅	5
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications	❌	✅	✅	❌	✅	❌	✅	4
Sparse and Structured Hopfield Networks	✅	✅	✅	✅	❌	❌	✅	5
Sparse is Enough in Fine-tuning Pre-trained Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency	❌	✅	✅	✅	✅	❌	✅	5
Sparse-to-dense Multimodal Image Registration via Multi-Task Learning	❌	✅	✅	❌	✅	❌	✅	4
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters	✅	✅	✅	✅	✅	❌	✅	6
Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization	✅	✅	✅	✅	❌	❌	✅	5
Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities	✅	✅	❌	❌	❌	❌	✅	3
Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models	❌	❌	❌	❌	❌	❌	❌	0
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions	✅	❌	✅	❌	❌	❌	✅	3
Speech Self-Supervised Learning Using Diffusion Model Synthetic Data	❌	✅	✅	✅	✅	❌	✅	5
Spider: A Unified Framework for Context-dependent Concept Segmentation	✅	❌	✅	❌	✅	❌	✅	4
Spike Distance Function as a Learning Objective for Spike Prediction	✅	❌	✅	✅	✅	✅	✅	6
SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms	❌	✅	✅	✅	✅	❌	✅	5
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN	❌	✅	✅	❌	❌	❌	✅	3
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting	✅	❌	✅	❌	✅	❌	✅	4
Split-and-Denoise: Protect large language model inference with local differential privacy	❌	✅	✅	❌	✅	✅	✅	5
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text	❌	✅	✅	❌	✅	❌	✅	4
SqueezeLLM: Dense-and-Sparse Quantization	❌	✅	✅	✅	✅	❌	✅	5
Stability Evaluation through Distributional Perturbation Analysis	✅	❌	✅	✅	✅	❌	✅	5
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations	✅	❌	❌	❌	❌	❌	✅	2
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms	✅	❌	❌	❌	❌	❌	❌	1
Stability and Multigroup Fairness in Ranking with Uncertain Predictions	❌	❌	✅	❌	❌	❌	✅	2
Stability-Informed Initialization of Neural Ordinary Differential Equations	✅	✅	✅	❌	❌	❌	❌	3
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process	✅	❌	✅	❌	❌	❌	✅	3
Stable Differentiable Causal Discovery	✅	✅	✅	✅	✅	❌	✅	6
StableMask: Refining Causal Masking in Decoder-only Transformer	✅	✅	✅	✅	✅	❌	✅	6
StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization	❌	❌	✅	❌	❌	❌	✅	2
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation	❌	❌	✅	❌	❌	✅	✅	3
Stacking Deep Set Networks and Pooling by Quantiles	✅	❌	✅	❌	❌	❌	✅	3
Standardized Interpretable Fairness Measures for Continuous Risk Scores	❌	✅	✅	❌	❌	❌	❌	2
State-Constrained Zero-Sum Differential Games with One-Sided Information	✅	✅	❌	❌	❌	❌	✅	3
State-Free Inference of State-Space Models: The Transfer Function Approach	✅	✅	✅	✅	✅	❌	✅	6
Stationarity without mean reversion in improper Gaussian processes	❌	❌	✅	❌	❌	❌	✅	2
Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation	✅	❌	✅	✅	✅	❌	✅	5
Statistical Inference Under Constrained Selection Bias	❌	✅	✅	❌	❌	❌	✅	3
Statistical Properties of Robust Satisficing	❌	❌	❌	❌	❌	❌	✅	1
Statistical Test for Attention Maps in Vision Transformers	✅	✅	✅	❌	❌	❌	✅	4
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution	✅	✅	✅	❌	❌	❌	✅	4
Stay on Topic with Classifier-Free Guidance	❌	✅	✅	❌	❌	❌	✅	3
Stealing part of a production language model	✅	✅	✅	❌	❌	❌	❌	3
Stealthy Imitation: Reward-guided Environment-free Policy Stealing	✅	❌	✅	✅	✅	❌	✅	5
Stereo Risk: A Continuous Modeling Approach to Stereo Matching	✅	❌	✅	❌	✅	✅	✅	5
Stereographic Spherical Sliced Wasserstein Distances	✅	✅	✅	❌	✅	❌	✅	5
Stochastic Bandits with ReLU Neural Networks	✅	✅	❌	❌	❌	❌	✅	3
Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis	✅	✅	✅	❌	✅	❌	✅	5
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features	❌	✅	✅	❌	❌	❌	✅	3
Stochastic Interpolants with Data-Dependent Couplings	✅	✅	✅	✅	❌	❌	✅	5
Stochastic Localization via Iterative Posterior Sampling	✅	✅	✅	❌	✅	❌	✅	5
Stochastic Optimization with Arbitrary Recurrent Data Sampling	✅	❌	✅	❌	❌	❌	✅	3
Stochastic Q-learning for Large Discrete Action Spaces	✅	❌	✅	❌	✅	✅	✅	5
Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions	✅	❌	❌	❌	❌	❌	❌	1
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity	✅	❌	❌	❌	❌	❌	✅	2
Stochastic positional embeddings improve masked image modeling	✅	✅	✅	❌	✅	❌	✅	5
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL	✅	❌	✅	❌	✅	❌	✅	4
StrWAEs to Invariant Representations	✅	✅	✅	❌	✅	✅	✅	6
Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm	✅	✅	✅	❌	❌	❌	✅	4
StrokeNUWA—Tokenizing Strokes for Vector Graphic Synthesis	❌	✅	✅	✅	✅	❌	✅	5
Structure Your Data: Towards Semantic Graph Counterfactuals	❌	✅	✅	✅	✅	❌	✅	5
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks	✅	✅	✅	✅	✅	❌	✅	6
Structure-based drug design by denoising voxel grids	✅	❌	✅	✅	✅	❌	✅	5
Structured Chemistry Reasoning with Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC	✅	✅	✅	❌	❌	❌	✅	4
Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens	✅	✅	✅	✅	✅	✅	✅	7
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization	✅	✅	✅	❌	❌	❌	✅	4
SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors	✅	❌	❌	❌	✅	❌	✅	3
Sub-token ViT Embedding via Stochastic Resonance Transformers	❌	✅	✅	❌	✅	❌	✅	4
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments	✅	✅	✅	❌	❌	❌	✅	4
Subgoal-based Demonstration Learning for Formal Theorem Proving	✅	❌	✅	✅	✅	✅	✅	6
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products	❌	✅	✅	✅	✅	❌	✅	5
Subhomogeneous Deep Equilibrium Models	❌	✅	✅	✅	❌	❌	✅	4
Submodular framework for structured-sparse optimal transport	✅	✅	✅	✅	✅	❌	✅	6
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation	❌	✅	❌	❌	❌	❌	❌	1
Successor Features for Efficient Multi-Subject Controlled Text Generation	❌	✅	✅	❌	✅	❌	✅	4
Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction	❌	❌	✅	❌	✅	❌	✅	3
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation	✅	✅	✅	✅	✅	❌	✅	6
Supervised Matrix Factorization: Local Landscape Analysis and Applications	✅	❌	✅	❌	✅	❌	✅	4
SurfPro: Functional Protein Design Based on Continuous Surface	❌	❌	✅	✅	✅	❌	✅	4
Surface-VQMAE: Vector-quantized Masked Auto-encoders on Molecular Surfaces	❌	✅	✅	✅	✅	❌	✅	5
Surprisingly Strong Performance Prediction with Neural Graph Features	❌	✅	✅	✅	✅	❌	✅	5
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation	✅	❌	✅	✅	✅	❌	✅	5
Switchable Decision: Dynamic Neural Generation Networks	✅	❌	✅	✅	✅	❌	✅	5
Switched Flow Matching: Eliminating Singularities via Switching ODEs	✅	✅	✅	❌	✅	❌	✅	5
Switching the Loss Reduces the Cost in Batch Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment	❌	❌	✅	✅	✅	❌	✅	4
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion	✅	✅	✅	❌	✅	❌	✅	5
Symmetric Matrix Completion with ReLU Sampling	✅	❌	❌	❌	✅	✅	✅	4
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization	✅	✅	✅	✅	❌	❌	✅	5
Symmetry Induces Structure and Constraint of Learning	❌	❌	✅	❌	❌	❌	✅	2
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs	❌	✅	✅	❌	✅	❌	✅	4
TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision	✅	✅	✅	❌	✅	❌	✅	5
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors	✅	✅	✅	❌	✅	❌	✅	5
TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression	✅	✅	✅	❌	❌	❌	✅	4
TSLANet: Rethinking Transformers for Time Series Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
TVE: Learning Meta-attribution for Transferable Vision Explainer	✅	✅	✅	❌	✅	❌	✅	5
TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules	❌	✅	✅	❌	✅	❌	✅	4
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images	❌	❌	✅	✅	❌	❌	✅	3
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation	✅	✅	✅	❌	✅	❌	✅	5
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More	❌	✅	✅	✅	✅	❌	✅	5
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains	❌	✅	✅	❌	✅	❌	✅	4
Tandem Transformers for Inference Efficient LLMs	❌	❌	✅	❌	✅	❌	✅	3
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation	❌	❌	❌	❌	❌	❌	✅	1
Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models	✅	❌	✅	✅	❌	❌	✅	4
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning	✅	❌	✅	❌	✅	❌	✅	4
Taylor Videos for Action Recognition	✅	✅	✅	✅	✅	❌	✅	6
Tell, Don’t Show: Language Guidance Eases Transfer Across Domains in Images and Videos	❌	✅	✅	✅	❌	❌	✅	4
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning	❌	✅	✅	✅	✅	❌	✅	5
Test-Time Degradation Adaptation for Open-Set Image Restoration	❌	✅	✅	❌	✅	❌	✅	4
Test-Time Model Adaptation with Only Forward Passes	✅	✅	✅	✅	✅	❌	✅	6
Test-Time Regret Minimization in Meta Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Testing the Feasibility of Linear Programs with Bandit Feedback	✅	❌	❌	❌	✅	❌	✅	3
The Balanced-Pairwise-Affinities Feature Transform	✅	✅	✅	✅	❌	❌	✅	5
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents	❌	✅	❌	❌	❌	❌	✅	2
The Computational Complexity of Finding Second-Order Stationary Points	✅	❌	❌	❌	❌	❌	❌	1
The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks	✅	❌	❌	❌	❌	❌	❌	1
The Emergence of Reproducibility and Consistency in Diffusion Models	✅	❌	✅	❌	❌	❌	✅	3
The Entropy Enigma: Success and Failure of Entropy Minimization	❌	✅	✅	✅	❌	❌	✅	4
The Expressive Power of Path-Based Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
The Fundamental Limits of Least-Privilege Learning	❌	❌	✅	✅	❌	❌	✅	3
The Good, The Bad, and Why: Unveiling Emotions in Generative AI	❌	❌	✅	❌	❌	❌	✅	2
The Illusion of State in State-Space Models	❌	✅	❌	❌	❌	❌	❌	1
The Linear Representation Hypothesis and the Geometry of Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm	✅	✅	✅	❌	✅	❌	✅	5
The Merit of River Network Topology for Neural Flood Forecasting	✅	✅	✅	✅	❌	❌	✅	5
The Non-linear $F$-Design and Applications to Interactive Learning	✅	❌	❌	❌	❌	❌	❌	1
The Perception-Robustness Tradeoff in Deterministic Image Restoration	✅	❌	✅	❌	❌	❌	✅	3
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks	❌	✅	✅	✅	❌	❌	✅	4
The Pitfalls of Next-Token Prediction	❌	✅	❌	❌	❌	❌	✅	2
The Privacy Power of Correlated Noise in Decentralized Learning	✅	✅	✅	❌	❌	❌	✅	4
The Relative Value of Prediction in Algorithmic Decision Making	❌	❌	❌	❌	❌	❌	✅	1
The Role of Learning Algorithms in Collective Action	✅	❌	✅	✅	❌	❌	✅	4
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline	❌	✅	✅	❌	✅	❌	✅	4
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling	✅	❌	✅	❌	❌	❌	❌	2
The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning	✅	✅	✅	❌	✅	✅	✅	6
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability	✅	❌	❌	❌	❌	❌	❌	1
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians	❌	❌	❌	❌	❌	❌	✅	1
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models	❌	❌	✅	❌	❌	❌	✅	2
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling	❌	❌	❌	❌	❌	❌	❌	0
Thermometer: Towards Universal Calibration for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Think Before You Act: Decision Transformers with Working Memory	✅	✅	✅	❌	✅	❌	✅	5
Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders	✅	❌	✅	❌	❌	❌	✅	3
Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration	✅	✅	✅	✅	✅	❌	✅	6
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers	✅	✅	✅	✅	✅	❌	✅	6
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Time Series Diffusion in the Frequency Domain	❌	✅	✅	✅	✅	❌	✅	5
Time Weaver: A Conditional Time Series Generation Model	✅	❌	✅	✅	✅	❌	✅	5
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning	✅	✅	✅	✅	❌	❌	✅	5
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning	✅	✅	✅	✅	✅	❌	✅	6
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling	❌	✅	✅	✅	✅	❌	✅	5
TimeX++: Learning Time-Series Explanations with Information Bottleneck	✅	✅	✅	✅	✅	❌	✅	6
Timer: Generative Pre-trained Transformers Are Large Time Series Models	❌	✅	✅	✅	✅	❌	✅	5
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge	✅	✅	✅	✅	✅	✅	✅	7
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO	✅	✅	✅	✅	✅	✅	✅	7
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
To the Max: Reinventing Reward in Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Token-level Direct Preference Optimization	✅	✅	✅	❌	❌	❌	✅	4
Topological Neural Networks go Persistent, Equivariant, and Continuous	❌	✅	✅	✅	✅	❌	✅	5
Total Variation Distance Meets Probabilistic Inference	✅	❌	❌	❌	❌	❌	❌	1
Total Variation Floodgate for Variable Importance Inference in Classification	✅	✅	✅	✅	❌	❌	✅	5
Toward Adaptive Reasoning in Large Language Models with Thought Rollback	❌	✅	✅	❌	❌	❌	✅	3
Toward Availability Attacks in 3D Point Clouds	✅	✅	✅	✅	❌	❌	✅	5
Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components	✅	✅	✅	❌	❌	❌	✅	4
Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention	✅	✅	✅	✅	❌	❌	✅	5
Towards Certified Unlearning for Deep Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
Towards Compositionality in Concept Learning	✅	✅	✅	❌	❌	❌	✅	4
Towards Efficient Exact Optimization of Language Model Alignment	❌	✅	✅	❌	✅	❌	✅	4
Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration	✅	❌	✅	❌	✅	❌	✅	4
Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations	✅	✅	✅	❌	✅	❌	✅	5
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph	✅	✅	✅	✅	✅	✅	✅	7
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators	❌	✅	❌	❌	✅	❌	✅	3
Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective	❌	✅	✅	❌	✅	❌	✅	4
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles	✅	❌	❌	❌	❌	❌	✅	2
Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation	✅	❌	✅	❌	✅	❌	✅	4
Towards Modular LLMs by Building and Reusing a Library of LoRAs	✅	❌	✅	✅	❌	❌	✅	4
Towards Neural Architecture Search through Hierarchical Generative Modeling	✅	❌	✅	✅	✅	✅	✅	6
Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error	✅	✅	✅	❌	❌	❌	✅	4
Towards Realistic Model Selection for Semi-supervised Learning	✅	❌	✅	✅	❌	❌	✅	4
Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering	✅	❌	✅	❌	❌	❌	❌	2
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption	✅	❌	❌	❌	❌	❌	❌	1
Towards Scalable and Versatile Weight Space Learning	✅	✅	✅	✅	❌	❌	✅	5
Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features	❌	✅	✅	✅	❌	❌	✅	4
Towards Theoretical Understandings of Self-Consuming Generative Models	✅	❌	✅	❌	❌	❌	❌	2
Towards Understanding Inductive Bias in Transformers: A View From Infinity	❌	❌	✅	❌	❌	❌	✅	2
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features	❌	✅	✅	❌	❌	❌	✅	3
Towards Unified Multi-granularity Text Detection with Interactive Attention	❌	❌	✅	❌	✅	❌	✅	3
Towards a Better Theoretical Understanding of Independent Subnetwork Training	✅	❌	✅	❌	❌	❌	✅	3
Towards a Self-contained Data-driven Global Weather Forecasting Framework	✅	✅	✅	❌	✅	❌	✅	5
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model	✅	✅	❌	✅	❌	❌	✅	4
Towards efficient deep spiking neural networks construction with spiking activity based pruning	✅	❌	✅	❌	❌	❌	✅	3
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms	✅	❌	✅	❌	❌	❌	✅	3
Trainable Transformer in Transformer	❌	❌	✅	✅	✅	❌	✅	4
Trained Random Forests Completely Reveal your Dataset	❌	✅	✅	❌	✅	✅	✅	5
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization	✅	✅	✅	❌	❌	❌	✅	4
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Training-Free Long-Context Scaling of Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation	❌	❌	✅	❌	❌	❌	✅	2
Transferring Knowledge From Large Foundation Models to Small Downstream Models	✅	✅	✅	✅	✅	❌	✅	6
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language Models	✅	✅	✅	❌	❌	❌	✅	4
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context	❌	❌	❌	❌	❌	❌	✅	1
Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape	✅	❌	❌	❌	❌	❌	✅	2
Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot	❌	❌	❌	❌	✅	❌	✅	2
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality	✅	✅	✅	❌	✅	❌	✅	5
Transformers, parallel computation, and logarithmic depth	✅	✅	❌	❌	✅	❌	✅	4
Transforming and Combining Rewards for Aligning Large Language Models	❌	❌	✅	✅	❌	❌	✅	3
Transitional Uncertainty with Layered Intermediate Predictions	✅	❌	✅	✅	✅	❌	✅	5
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Translation Equivariant Transformer Neural Processes	❌	❌	✅	✅	❌	❌	✅	3
Transolver: A Fast Transformer Solver for PDEs on General Geometries	❌	✅	✅	❌	✅	❌	✅	4
Transport of Algebraic Structure to Latent Embeddings	✅	✅	❌	✅	✅	✅	✅	6
TravelPlanner: A Benchmark for Real-World Planning with Language Agents	❌	✅	✅	✅	❌	❌	✅	4
Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence	✅	❌	✅	❌	❌	❌	✅	3
Triple Changes Estimator for Targeted Policies	❌	✅	✅	❌	❌	❌	✅	3
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers	❌	✅	✅	✅	✅	❌	✅	5
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning	✅	✅	✅	✅	❌	❌	✅	5
TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks	❌	✅	✅	❌	❌	❌	✅	3
Truly No-Regret Learning in Constrained MDPs	✅	✅	❌	❌	✅	❌	✅	4
Trust Regions for Explanations via Black-Box Probabilistic Certification	✅	✅	✅	❌	✅	❌	✅	5
Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption	✅	✅	✅	❌	❌	❌	✅	4
Trustless Audits without Revealing Data or Models	❌	✅	✅	❌	✅	❌	❌	3
Trustworthy Actionable Perturbations	✅	✅	✅	✅	❌	❌	✅	5
Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Tuning-Free Stochastic Optimization	✅	❌	❌	❌	❌	❌	❌	1
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy	✅	❌	❌	❌	✅	❌	✅	3
Turnstile $\ell_p$ leverage score sampling with applications	✅	✅	✅	❌	✅	❌	❌	4
Two Fists, One Heart: Multi-Objective Optimization Based Strategy Fusion for Long-tailed Learning	✅	✅	✅	❌	✅	❌	✅	5
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness	✅	✅	✅	✅	✅	❌	✅	6
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection	✅	✅	✅	❌	✅	❌	✅	5
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation	❌	✅	✅	✅	✅	❌	✅	5
Two Tales of Single-Phase Contrastive Hebbian Learning	❌	✅	✅	✅	❌	❌	✅	4
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias	✅	✅	✅	❌	✅	✅	✅	6
Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints	✅	✅	❌	❌	❌	❌	✅	3
Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data	✅	❌	❌	❌	✅	✅	✅	4
UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs	❌	✅	❌	❌	✅	❌	✅	3
ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision	✅	✅	✅	✅	❌	❌	✅	5
ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback	❌	❌	✅	❌	❌	❌	✅	2
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis	❌	✅	✅	✅	✅	❌	✅	5
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers	❌	❌	✅	❌	❌	❌	✅	2
UPOCR: Towards Unified Pixel-Level OCR Interface	❌	✅	✅	✅	✅	❌	✅	5
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval	❌	❌	✅	✅	❌	❌	✅	3
Unbiased Multi-Label Learning from Crowdsourced Annotations	✅	✅	✅	✅	❌	❌	✅	5
Uncertainty Estimation by Density Aware Evidential Deep Learning	✅	✅	✅	✅	❌	❌	✅	5
Uncertainty for Active Learning on Graphs	❌	✅	✅	✅	✅	❌	✅	5
Uncertainty-Aware Reward-Free Exploration with General Function Approximation	✅	✅	✅	❌	❌	❌	✅	4
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise	❌	❌	❌	❌	❌	❌	✅	1
Understanding Diffusion Models by Feynman’s Path Integral	✅	✅	✅	❌	❌	❌	✅	4
Understanding Finetuning for Factual Knowledge Extraction	❌	❌	✅	✅	❌	❌	✅	3
Understanding Forgetting in Continual Learning with Linear Regression	❌	❌	❌	❌	❌	❌	✅	1
Understanding Heterophily for Graph Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
Understanding Inter-Concept Relationships in Concept-Based Models	✅	✅	✅	✅	✅	❌	✅	6
Understanding MLP-Mixer as a wide and sparse MLP	❌	❌	✅	❌	✅	❌	✅	3
Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation	✅	✅	✅	❌	✅	❌	✅	5
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models	❌	❌	✅	✅	✅	❌	✅	4
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation	✅	❌	✅	❌	❌	❌	✅	3
Understanding Stochastic Natural Gradient Variational Inference	✅	❌	✅	❌	❌	❌	✅	3
Understanding Unimodal Bias in Multimodal Deep Linear Networks	❌	✅	✅	❌	❌	❌	✅	3
Understanding and Diagnosing Deep Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Understanding the Effects of Iterative Prompting on Truthfulness	❌	❌	✅	❌	❌	❌	✅	2
Understanding the Impact of Introducing Constraints at Inference Time on Generalization Error	❌	❌	❌	❌	❌	❌	❌	0
Understanding the Learning Dynamics of Alignment with Human Feedback	❌	❌	✅	❌	❌	❌	✅	2
Understanding the Training Speedup from Sampling with Approximate Losses	✅	❌	✅	❌	✅	❌	✅	4
UniAudio: Towards Universal Audio Generation with Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning	✅	❌	✅	✅	❌	❌	✅	4
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding	✅	✅	✅	✅	✅	❌	✅	6
Unified Training of Universal Time Series Forecasting Transformers	❌	✅	✅	✅	✅	❌	✅	5
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models	✅	✅	✅	✅	❌	❌	✅	5
Uniformly Stable Algorithms for Adversarial Training and Beyond	✅	✅	✅	❌	❌	❌	✅	4
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations	✅	✅	✅	❌	❌	❌	✅	4
Unifying Image Processing as Visual Prompting Question Answering	❌	✅	✅	❌	✅	❌	✅	4
Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes	❌	❌	❌	❌	❌	❌	❌	0
Universal Gradient Methods for Stochastic Convex Optimization	✅	❌	✅	❌	❌	❌	✅	3
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues	❌	❌	✅	✅	✅	❌	✅	4
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts	✅	✅	✅	✅	❌	❌	✅	5
Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation	✅	❌	✅	✅	✅	✅	✅	6
Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training	❌	✅	✅	✅	✅	❌	✅	5
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs	✅	❌	❌	❌	❌	❌	✅	2
Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning	✅	❌	✅	❌	❌	❌	✅	3
Unsupervised Concept Discovery Mitigates Spurious Correlations	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised Domain Adaptation for Anatomical Structure Detection in Ultrasound Images	✅	✅	✅	✅	❌	❌	✅	5
Unsupervised Episode Generation for Graph Meta-learning	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness	❌	✅	✅	❌	❌	❌	✅	3
Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms	❌	✅	✅	✅	❌	❌	✅	4
Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity	❌	❌	✅	✅	❌	❌	✅	3
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings	✅	✅	✅	❌	❌	❌	✅	4
Unveiling Privacy, Memorization, and Input Curvature Links	❌	✅	✅	❌	❌	✅	✅	4
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration	❌	✅	✅	✅	❌	❌	✅	4
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression	❌	✅	❌	❌	❌	❌	❌	1
Unveiling the Dynamics of Information Interplay in Supervised Learning	❌	❌	✅	❌	❌	❌	✅	2
Unveiling the Potential of AI for Nanomaterial Morphology Prediction	❌	✅	✅	✅	✅	❌	✅	5
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers	❌	✅	✅	✅	✅	❌	✅	5
Using AI Uncertainty Quantification to Improve Human Decision-Making	❌	✅	✅	❌	✅	❌	✅	4
Using Left and Right Brains Together: Towards Vision and Language Planning	❌	❌	✅	❌	❌	❌	❌	1
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs	❌	✅	❌	❌	❌	❌	✅	2
VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees	❌	✅	✅	✅	✅	✅	✅	6
VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling	❌	❌	✅	✅	✅	❌	✅	4
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection	✅	❌	✅	✅	✅	✅	✅	6
Value-Evolutionary-Based Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Vanilla Bayesian Optimization Performs Great in High Dimensions	❌	✅	✅	❌	❌	❌	✅	3
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models	✅	✅	✅	✅	✅	❌	✅	6
Variational Inference with Coverage Guarantees in Simulation-Based Inference	✅	✅	✅	✅	✅	❌	✅	6
Variational Learning is Effective for Large Deep Networks	✅	✅	✅	✅	✅	❌	✅	6
Variational Linearized Laplace Approximation for Bayesian Deep Learning	✅	✅	✅	✅	❌	❌	✅	5
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts	❌	✅	✅	❌	❌	❌	✅	3
Variational Schrödinger Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention	✅	✅	✅	✅	✅	❌	✅	6
Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment	❌	✅	✅	✅	✅	❌	✅	5
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations	✅	✅	✅	❌	✅	❌	✅	5
Verification of Machine Unlearning is Fragile	✅	✅	✅	✅	✅	❌	✅	6
Verifying message-passing neural networks via topology-based bounds tightening	✅	✅	✅	❌	✅	✅	✅	6
ViP: A Differentially Private Foundation Model for Computer Vision	❌	✅	✅	❌	✅	❌	✅	4
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization	❌	✅	✅	✅	✅	❌	✅	5
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition	❌	✅	✅	✅	✅	❌	✅	5
VideoPoet: A Large Language Model for Zero-Shot Video Generation	❌	❌	✅	❌	✅	❌	✅	3
VideoPrism: A Foundational Visual Encoder for Video Understanding	✅	❌	✅	✅	❌	❌	✅	4
Viewing Transformers Through the Lens of Long Convolutions Layers	❌	❌	✅	✅	✅	❌	✅	4
VinT-6D: A Large-Scale Object-in-hand Dataset from Vision, Touch and Proprioception	❌	✅	✅	❌	✅	❌	✅	4
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model	✅	✅	✅	✅	✅	❌	✅	6
Vision Transformers as Probabilistic Expansion from Learngene	❌	❌	✅	✅	❌	❌	✅	3
VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context	✅	✅	✅	❌	❌	❌	✅	4
Visual Representation Learning with Stochastic Frame Prediction	✅	✅	✅	❌	❌	❌	✅	4
Visual Transformer with Differentiable Channel Selection: An Information Bottleneck Inspired Approach	✅	✅	✅	✅	✅	❌	✅	6
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models	✅	✅	✅	✅	✅	❌	✅	6
Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions	❌	❌	❌	❌	❌	❌	❌	0
VoroNav: Voronoi-based Zero-shot Object Navigation with Large Language Model	✅	✅	✅	✅	✅	❌	✅	6
WARM: On the Benefits of Weight Averaged Reward Models	❌	❌	✅	✅	❌	❌	✅	3
WAVES: Benchmarking the Robustness of Image Watermarks	❌	✅	✅	✅	❌	❌	✅	4
WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer	✅	✅	✅	✅	✅	❌	✅	6
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer	✅	✅	✅	❌	✅	✅	✅	6
Watermark Stealing in Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Watermarks in the Sand: Impossibility of Strong Watermarking for Language Models	✅	✅	✅	❌	✅	❌	✅	5
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision	❌	✅	✅	✅	❌	❌	✅	4
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation	❌	❌	✅	✅	❌	❌	✅	3
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation	❌	✅	✅	✅	❌	❌	✅	4
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue	❌	✅	✅	✅	✅	❌	✅	5
Weighted distance nearest neighbor condensing	✅	❌	✅	❌	❌	❌	❌	2
Weisfeiler Leman for Euclidean Equivariant Machine Learning	✅	✅	✅	✅	✅	✅	✅	7
Weisfeiler-Leman at the margin: When more expressivity matters	❌	✅	✅	✅	✅	❌	✅	5
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks	❌	❌	❌	❌	❌	❌	✅	1
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding	✅	❌	✅	❌	❌	❌	✅	3
What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement	✅	❌	✅	✅	❌	❌	✅	4
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks	✅	❌	✅	❌	✅	❌	✅	4
What is Dataset Distillation Learning?	❌	✅	✅	❌	❌	❌	✅	3
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis	❌	❌	❌	❌	❌	❌	❌	0
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation	✅	✅	✅	❌	✅	❌	✅	5
What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions	✅	❌	✅	❌	❌	❌	✅	3
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions	❌	✅	✅	❌	✅	❌	✅	4
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
When Representations Align: Universality in Representation Learning Dynamics	❌	❌	✅	❌	❌	❌	✅	2
When Will Gradient Regularization Be Harmful?	✅	✅	✅	❌	❌	❌	✅	4
When and How Does In-Distribution Label Help Out-of-Distribution Detection?	❌	✅	✅	❌	❌	❌	✅	3
When is Transfer Learning Possible?	✅	❌	✅	✅	❌	❌	✅	4
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning	❌	❌	✅	❌	❌	❌	✅	2
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models	✅	✅	✅	❌	❌	❌	✅	4
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning	❌	❌	❌	❌	❌	❌	✅	1
Why Do You Grok? A Theoretical Analysis on Grokking Modular Addition	❌	❌	❌	❌	✅	✅	✅	3
Why Larger Language Models Do In-context Learning Differently?	❌	❌	✅	❌	❌	❌	✅	2
Why do Variational Autoencoders Really Promote Disentanglement?	❌	✅	✅	❌	❌	❌	✅	3
Winner-takes-all learners are geometry-aware conditional density estimators	❌	✅	✅	✅	✅	❌	✅	5
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?	❌	✅	✅	❌	✅	✅	✅	5
Wukong: Towards a Scaling Law for Large-Scale Recommendation	❌	❌	✅	❌	✅	❌	✅	3
X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation	❌	✅	❌	❌	✅	✅	✅	4
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement	❌	✅	✅	✅	✅	❌	✅	5
Zero-Shot Reinforcement Learning via Function Encoders	✅	✅	✅	❌	✅	❌	✅	5
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion	✅	✅	✅	❌	❌	✅	✅	5
Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach	❌	❌	✅	❌	❌	❌	✅	2
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization	✅	❌	✅	❌	❌	❌	✅	3
convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data	✅	✅	✅	❌	✅	❌	✅	5
diff History for Neural Language Agents	❌	✅	✅	✅	✅	❌	✅	5
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data	❌	✅	✅	✅	❌	❌	✅	4
tinyBenchmarks: evaluating LLMs with fewer examples	❌	✅	✅	✅	❌	❌	✅	4
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)	✅	✅	✅	✅	❌	❌	✅	5
video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
xT: Nested Tokenization for Larger Context in Large Images	❌	✅	✅	❌	✅	❌	✅	4