reproducibilityindex.ai

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 [1].

International Conference on Machine Learning (ICML) - 2024

Website:

Venue	Year	Papers	Reproducibility Score Reproducibility Score based on Gundersen et al. (2025)	Documentation Score Global mean is the average score over the seven reproducibility variables for empirical research papers.	% 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