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) - 2023

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	2023	1828	0.6	4.06	91.47%	43.84%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts	❌	✅	✅	✅	✅	❌	✅	5
$H$-Consistency Bounds for Pairwise Misranking Loss Surrogates	❌	❌	✅	❌	❌	❌	✅	2
$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation	❌	✅	✅	✅	✅	❌	✅	5
2D-Shapley: A Framework for Fragmented Data Valuation	✅	✅	✅	❌	✅	❌	✅	5
A Category-theoretical Meta-analysis of Definitions of Disentanglement	❌	❌	❌	❌	❌	❌	❌	0
A Closer Look at Few-shot Classification Again	❌	✅	✅	✅	❌	❌	✅	4
A Closer Look at Self-Supervised Lightweight Vision Transformers	❌	✅	✅	✅	✅	❌	✅	5
A Closer Look at the Intervention Procedure of Concept Bottleneck Models	✅	✅	✅	✅	✅	❌	✅	6
A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests	❌	✅	✅	✅	✅	❌	✅	5
A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging	❌	✅	✅	✅	✅	❌	✅	5
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
A Coupled Flow Approach to Imitation Learning	✅	✅	✅	❌	❌	❌	✅	4
A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification	✅	❌	✅	❌	✅	❌	✅	4
A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment	❌	✅	✅	✅	✅	❌	✅	5
A Deep Conjugate Direction Method for Iteratively Solving Linear Systems	✅	✅	✅	❌	✅	❌	✅	5
A Distribution Optimization Framework for Confidence Bounds of Risk Measures	✅	❌	✅	❌	❌	❌	✅	3
A Fast Optimistic Method for Monotone Variational Inequalities	✅	✅	✅	❌	❌	❌	✅	4
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel	❌	❌	✅	❌	✅	❌	✅	3
A Flexible Diffusion Model	❌	❌	✅	❌	✅	❌	✅	3
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback	✅	❌	✅	❌	❌	❌	✅	3
A Fully First-Order Method for Stochastic Bilevel Optimization	✅	❌	✅	✅	❌	❌	✅	4
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems	✅	❌	✅	❌	✅	✅	✅	5
A General Representation Learning Framework with Generalization Performance Guarantees	✅	✅	✅	✅	✅	❌	✅	6
A Generalization of ViT/MLP-Mixer to Graphs	❌	✅	✅	✅	✅	❌	✅	5
A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening	✅	✅	✅	✅	✅	❌	✅	6
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining	❌	✅	✅	✅	✅	❌	✅	5
A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer	✅	✅	✅	❌	✅	❌	✅	5
A Kernel Stein Test of Goodness of Fit for Sequential Models	✅	✅	❌	❌	❌	❌	✅	3
A Kernel-Based View of Language Model Fine-Tuning	❌	✅	✅	✅	❌	❌	✅	4
A Kernelized Stein Discrepancy for Biological Sequences	❌	✅	✅	❌	❌	❌	✅	3
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression	✅	✅	✅	✅	❌	❌	✅	5
A Law of Robustness beyond Isoperimetry	❌	❌	❌	❌	❌	❌	❌	0
A Mathematical Model for Curriculum Learning for Parities	❌	✅	❌	❌	❌	❌	✅	2
A Model-Based Method for Minimizing CVaR and Beyond	✅	❌	✅	❌	❌	❌	✅	3
A Model-free Closeness-of-influence Test for Features in Supervised Learning	✅	❌	✅	❌	❌	❌	✅	3
A Modern Look at the Relationship between Sharpness and Generalization	✅	✅	✅	❌	❌	❌	✅	4
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints	✅	❌	✅	❌	❌	❌	✅	3
A Nearly-Optimal Bound for Fast Regression with $\ell_∞$ Guarantee	❌	❌	❌	❌	❌	❌	❌	0
A Neural PDE Solver with Temporal Stencil Modeling	❌	✅	❌	❌	✅	❌	✅	3
A New PHO-rmula for Improved Performance of Semi-Structured Networks	✅	✅	✅	✅	❌	❌	✅	5
A Picture of the Space of Typical Learnable Tasks	❌	✅	✅	❌	❌	❌	✅	3
A Reinforcement Learning Framework for Dynamic Mediation Analysis	❌	✅	✅	✅	❌	❌	✅	4
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
A Robust Test for the Stationarity Assumption in Sequential Decision Making	✅	✅	✅	❌	❌	❌	✅	4
A Scalable Frank-Wolfe-Based Algorithm for the Max-Cut SDP	✅	❌	✅	❌	✅	✅	✅	5
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models	✅	✅	✅	✅	❌	❌	✅	5
A Statistical Perspective on Retrieval-Based Models	❌	❌	✅	✅	❌	❌	✅	3
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs	❌	✅	✅	✅	❌	❌	✅	4
A Study on Transformer Configuration and Training Objective	❌	❌	✅	✅	✅	❌	✅	4
A Theoretical Analysis of the Learning Dynamics under Class Imbalance	✅	✅	✅	✅	✅	❌	✅	6
A Three-regime Model of Network Pruning	✅	✅	✅	✅	❌	❌	✅	5
A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations	❌	✅	❌	✅	❌	❌	✅	3
A Two-Stage Active Learning Algorithm for k-Nearest Neighbors	✅	❌	❌	❌	❌	❌	❌	1
A Unified Audio-Visual Learning Framework for Localization, Separation, and Recognition	❌	✅	✅	✅	❌	❌	✅	4
A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates	✅	✅	✅	✅	❌	❌	✅	5
A Unifying Framework to the Analysis of Interaction Methods using Synergy Functions	❌	❌	❌	❌	❌	❌	❌	0
A Universal Unbiased Method for Classification from Aggregate Observations	✅	❌	✅	✅	❌	❌	✅	4
A Watermark for Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
A new near-linear time algorithm for k-nearest neighbor search using a compressed cover tree	✅	❌	❌	❌	❌	❌	❌	1
A theory of continuous generative flow networks	❌	✅	✅	❌	✅	❌	✅	4
A theory of representation learning gives a deep generalisation of kernel methods	✅	❌	✅	❌	❌	❌	✅	3
A/B Testing in Network Data with Covariate-Adaptive Randomization	✅	✅	✅	❌	❌	❌	✅	4
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging	✅	✅	✅	✅	✅	❌	✅	6
AbODE: Ab initio antibody design using conjoined ODEs	❌	❌	✅	✅	❌	❌	✅	3
Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization	❌	❌	❌	❌	❌	❌	✅	1
Abstracting Imperfect Information Away from Two-Player Zero-Sum Games	✅	❌	❌	❌	❌	❌	❌	1
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization	✅	✅	✅	❌	❌	❌	✅	4
Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations	❌	❌	❌	❌	❌	✅	✅	2
Accelerated Primal-Dual Methods for Convex-Strongly-Concave Saddle Point Problems	✅	❌	❌	❌	✅	❌	✅	3
Accelerated Stochastic Optimization Methods under Quasar-convexity	✅	✅	✅	❌	❌	❌	✅	4
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time	✅	✅	❌	✅	❌	❌	✅	4
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations	❌	✅	✅	❌	❌	❌	✅	3
Achieving Hierarchy-Free Approximation for Bilevel Programs with Equilibrium Constraints	✅	❌	✅	❌	✅	❌	✅	4
Achieving High Accuracy with PINNs via Energy Natural Gradient Descent	✅	✅	❌	❌	✅	❌	✅	4
Achieving Linear Speedup in Non-IID Federated Bilevel Learning	✅	❌	✅	❌	✅	❌	✅	4
Action Matching: Learning Stochastic Dynamics from Samples	✅	✅	✅	❌	❌	❌	✅	4
Active Learning based Structural Inference	✅	✅	✅	✅	✅	❌	✅	6
Active Policy Improvement from Multiple Black-box Oracles	✅	❌	✅	❌	✅	❌	✅	4
Active Ranking of Experts Based on their Performances in Many Tasks	✅	❌	❌	❌	❌	❌	✅	2
Active causal structure learning with advice	✅	✅	✅	❌	✅	❌	❌	4
Actor-Critic Alignment for Offline-to-Online Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
AdaBoost is not an Optimal Weak to Strong Learner	✅	❌	❌	❌	❌	❌	❌	1
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation	✅	✅	✅	✅	✅	❌	❌	5
AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners	❌	❌	✅	❌	✅	❌	✅	3
Adapting to game trees in zero-sum imperfect information games	✅	✅	✅	❌	❌	❌	✅	4
Adaptive Annealed Importance Sampling with Constant Rate Progress	✅	✅	✅	❌	❌	❌	✅	4
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics	✅	❌	❌	❌	❌	❌	✅	2
Adaptive Compositional Continual Meta-Learning	✅	✅	✅	✅	✅	❌	✅	6
Adaptive Computation with Elastic Input Sequence	✅	✅	✅	✅	✅	❌	✅	6
Adaptive Coordination in Social Embodied Rearrangement	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Estimation of Graphical Models under Total Positivity	✅	✅	✅	❌	❌	❌	❌	3
Adaptive IMLE for Few-shot Pretraining-free Generative Modelling	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions	✅	❌	❌	❌	❌	❌	✅	2
Adaptive Smoothing Gradient Learning for Spiking Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Adaptive Whitening in Neural Populations with Gain-modulating Interneurons	✅	✅	✅	❌	❌	❌	✅	4
Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift	✅	✅	✅	✅	❌	❌	✅	5
Additive Causal Bandits with Unknown Graph	✅	✅	❌	❌	❌	❌	✅	3
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm	✅	✅	✅	✅	❌	❌	✅	5
Adversarial Cheap Talk	✅	✅	✅	❌	✅	❌	✅	5
Adversarial Collaborative Learning on Non-IID Features	✅	❌	✅	❌	✅	❌	✅	4
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples	✅	✅	✅	❌	✅	❌	✅	5
Adversarial Learning of Distributional Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
Adversarial Parameter Attack on Deep Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Adversarial Policies Beat Superhuman Go AIs	❌	✅	✅	❌	✅	❌	✅	4
Adversarial robustness of amortized Bayesian inference	✅	✅	✅	✅	❌	❌	✅	5
Adversarially Robust PAC Learnability of Real-Valued Functions	✅	❌	❌	❌	❌	❌	❌	1
Algorithmic Collective Action in Machine Learning	❌	❌	✅	❌	❌	❌	✅	2
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions	❌	❌	❌	❌	❌	❌	❌	0
Algorithms for bounding contribution for histogram estimation under user-level privacy	✅	❌	✅	❌	❌	❌	✅	3
Aligning Language Models with Preferences through $f$-divergence Minimization	✅	❌	✅	❌	✅	❌	✅	4
All in a Row: Compressed Convolution Networks for Graphs	✅	✅	✅	✅	✅	❌	✅	6
Alternately Optimized Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations	✅	✅	✅	✅	❌	❌	✅	5
An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
An Effective Meaningful Way to Evaluate Survival Models	❌	✅	✅	✅	❌	❌	✅	4
An Information-Theoretic Analysis of Nonstationary Bandit Learning	❌	❌	❌	❌	❌	❌	✅	1
An Instrumental Variable Approach to Confounded Off-Policy Evaluation	✅	✅	❌	❌	❌	❌	❌	2
An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning	❌	✅	❌	✅	❌	❌	✅	3
An SDE for Modeling SAM: Theory and Insights	❌	❌	✅	❌	❌	❌	✅	2
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation	✅	❌	✅	✅	❌	❌	✅	4
Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels	❌	❌	❌	❌	✅	❌	✅	2
Analyzing Diffusion as Serial Reproduction	❌	✅	✅	❌	✅	❌	✅	4
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano	✅	❌	✅	❌	❌	❌	✅	3
Anchor Sampling for Federated Learning with Partial Client Participation	✅	✅	✅	❌	✅	✅	✅	6
Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization	✅	✅	✅	✅	✅	❌	✅	6
Anti-Exploration by Random Network Distillation	✅	✅	✅	❌	✅	❌	✅	5
Applied Online Algorithms with Heterogeneous Predictors	✅	❌	✅	✅	❌	❌	✅	4
Approximate Causal Effect Identification under Weak Confounding	❌	❌	✅	❌	❌	❌	❌	1
Approximate Stein Classes for Truncated Density Estimation	❌	✅	✅	❌	❌	❌	✅	3
Approximately Optimal Core Shapes for Tensor Decompositions	✅	✅	✅	❌	✅	❌	✅	5
Approximation Algorithms for Fair Range Clustering	✅	❌	❌	❌	❌	❌	❌	1
Approximation and Estimation Ability of Transformers for Sequence-to-Sequence Functions with Infinite Dimensional Input	❌	❌	✅	❌	❌	❌	❌	1
Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN	❌	✅	✅	✅	✅	❌	✅	5
Are Diffusion Models Vulnerable to Membership Inference Attacks?	❌	✅	✅	✅	❌	❌	✅	4
Are Equivariant Equilibrium Approximators Beneficial?	✅	❌	❌	❌	❌	❌	✅	2
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation	✅	✅	✅	❌	❌	❌	✅	4
Are Large Kernels Better Teachers than Transformers for ConvNets?	❌	✅	✅	✅	✅	❌	✅	5
Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations	❌	❌	✅	❌	❌	❌	✅	2
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?	✅	✅	✅	❌	✅	❌	✅	5
Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism.	✅	✅	✅	❌	❌	❌	❌	3
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
Atari-5: Distilling the Arcade Learning Environment down to Five Games	✅	✅	✅	✅	✅	❌	✅	6
Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability	✅	✅	✅	❌	✅	❌	✅	5
Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise	✅	❌	❌	❌	❌	❌	❌	1
Attributing Image Generative Models using Latent Fingerprints	❌	✅	✅	❌	✅	❌	✅	4
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning	✅	✅	✅	✅	✅	✅	✅	7
AutoCoreset: An Automatic Practical Coreset Construction Framework	✅	✅	✅	❌	✅	❌	✅	5
Automated Search for Conjectures on Mathematical Constants using Analysis of Integer Sequences	❌	✅	❌	❌	❌	❌	✅	2
Automatic Data Augmentation via Invariance-Constrained Learning	✅	❌	✅	✅	✅	❌	✅	5
Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Automatically Auditing Large Language Models via Discrete Optimization	✅	✅	✅	❌	✅	❌	✅	5
Automatically marginalized MCMC in probabilistic programming	✅	✅	✅	❌	❌	❌	✅	4
Autoregressive Diffusion Model for Graph Generation	✅	❌	✅	✅	❌	❌	✅	4
Auxiliary Learning as an Asymmetric Bargaining Game	✅	✅	✅	✅	❌	❌	✅	5
Auxiliary Modality Learning with Generalized Curriculum Distillation	✅	❌	✅	✅	✅	❌	✅	5
Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity	✅	✅	✅	❌	❌	❌	❌	3
B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding	✅	✅	✅	✅	✅	❌	✅	6
BEATs: Audio Pre-Training with Acoustic Tokenizers	❌	✅	✅	✅	✅	❌	✅	5
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming	✅	✅	✅	❌	✅	❌	❌	4
BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models	✅	❌	❌	❌	✅	✅	✅	4
Bag of Tricks for Training Data Extraction from Language Models	❌	✅	✅	✅	❌	✅	✅	5
Bandit Multi-linear DR-Submodular Maximization and Its Applications on Adversarial Submodular Bandits	✅	❌	❌	❌	❌	❌	❌	1
Bandit Online Linear Optimization with Hints and Queries	✅	❌	❌	❌	❌	❌	✅	2
Bandits with Knapsacks: Advice on Time-Varying Demands	✅	❌	❌	❌	❌	❌	✅	2
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning	✅	❌	❌	❌	❌	❌	❌	1
Bayes-optimal Learning of Deep Random Networks of Extensive-width	❌	✅	❌	❌	❌	❌	✅	2
Bayesian Design Principles for Frequentist Sequential Learning	✅	❌	❌	❌	❌	❌	✅	2
Bayesian Estimation of Differential Privacy	✅	✅	✅	❌	❌	❌	✅	4
Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts	❌	✅	✅	❌	❌	❌	✅	3
Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process	✅	❌	✅	❌	❌	❌	✅	3
Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models	✅	❌	✅	❌	✅	❌	✅	4
Bayesian online change point detection with Hilbert space approximate Student-t process	✅	❌	✅	❌	❌	❌	✅	3
Beam Tree Recursive Cells	✅	✅	✅	✅	✅	❌	✅	6
Behavior Contrastive Learning for Unsupervised Skill Discovery	✅	✅	✅	❌	✅	❌	✅	5
Benign Overfitting in Deep Neural Networks under Lazy Training	✅	❌	✅	❌	❌	❌	✅	3
Benign Overfitting in Two-layer ReLU Convolutional Neural Networks	❌	✅	❌	❌	❌	❌	✅	2
Best Arm Identification in Multi-Agent Multi-Armed Bandits	✅	✅	❌	❌	✅	❌	✅	4
Best of Both Worlds Policy Optimization	✅	❌	❌	❌	❌	❌	❌	1
Better Diffusion Models Further Improve Adversarial Training	❌	✅	✅	✅	✅	❌	✅	5
Better Training of GFlowNets with Local Credit and Incomplete Trajectories	✅	✅	❌	❌	❌	❌	✅	3
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic	✅	❌	❌	❌	❌	❌	✅	2
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering	❌	✅	✅	❌	❌	❌	✅	3
Beyond In-Domain Scenarios: Robust Density-Aware Calibration	❌	✅	✅	✅	✅	❌	✅	5
Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization	✅	❌	✅	❌	✅	❌	✅	4
Beyond Reward: Offline Preference-guided Policy Optimization	✅	✅	✅	❌	✅	❌	✅	5
Beyond Uniform Lipschitz Condition in Differentially Private Optimization	✅	❌	✅	❌	✅	❌	✅	4
Beyond the Edge of Stability via Two-step Gradient Updates	❌	❌	✅	❌	❌	❌	✅	2
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels	❌	✅	✅	❌	❌	❌	❌	2
Bi-directional Masks for Efficient N:M Sparse Training	✅	✅	✅	✅	✅	❌	✅	6
BiBench: Benchmarking and Analyzing Network Binarization	❌	✅	✅	✅	✅	❌	✅	5
BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning	✅	✅	✅	✅	✅	❌	✅	6
Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies	❌	✅	✅	❌	✅	✅	✅	5
Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions	✅	❌	✅	❌	✅	❌	✅	4
Bidirectional Learning for Offline Model-based Biological Sequence Design	✅	✅	✅	❌	✅	❌	✅	5
Bidirectional Looking with A Novel Double Exponential Moving Average to Adaptive and Non-adaptive Momentum Optimizers	✅	✅	✅	❌	✅	❌	✅	5
Bigger, Better, Faster: Human-level Atari with human-level efficiency	❌	✅	✅	✅	✅	❌	✅	5
Bilevel Optimization with Coupled Decision-Dependent Distributions	❌	❌	✅	❌	❌	❌	✅	2
Bit Allocation using Optimization	✅	✅	✅	❌	✅	✅	✅	6
Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces	✅	✅	✅	❌	✅	❌	✅	5
Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures	✅	✅	✅	❌	✅	✅	✅	6
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization	✅	✅	✅	✅	✅	❌	✅	6
Blossom: an Anytime Algorithm for Computing Optimal Decision Trees	✅	✅	✅	✅	✅	✅	✅	7
Boosting Graph Contrastive Learning via Graph Contrastive Saliency	✅	✅	✅	✅	❌	❌	✅	5
Boosting Offline Reinforcement Learning with Action Preference Query	✅	❌	✅	❌	❌	❌	✅	3
Bootstrap in High Dimension with Low Computation	❌	❌	✅	❌	✅	❌	✅	3
Bootstrapped Representations in Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
Brainformers: Trading Simplicity for Efficiency	✅	❌	✅	✅	✅	❌	✅	5
Brauer’s Group Equivariant Neural Networks	❌	❌	❌	❌	❌	❌	❌	0
Building Neural Networks on Matrix Manifolds: A Gyrovector Space Approach	❌	✅	✅	❌	❌	❌	✅	3
Buying Information for Stochastic Optimization	✅	❌	❌	❌	❌	❌	❌	1
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting	❌	✅	✅	✅	❌	❌	✅	4
CAB: Comprehensive Attention Benchmarking on Long Sequence Modeling	❌	✅	✅	❌	✅	❌	✅	4
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets	✅	✅	✅	✅	❌	❌	✅	5
CLIPood: Generalizing CLIP to Out-of-Distributions	✅	✅	✅	✅	✅	✅	✅	7
CLUSTSEG: Clustering for Universal Segmentation	✅	✅	✅	✅	❌	❌	✅	5
CLUTR: Curriculum Learning via Unsupervised Task Representation Learning	✅	✅	❌	❌	✅	❌	✅	4
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design	✅	✅	❌	❌	❌	✅	✅	4
COLA: Orchestrating Error Coding and Learning for Robust Neural Network Inference Against Hardware Defects	❌	✅	✅	❌	✅	❌	✅	4
COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models	❌	✅	✅	✅	✅	❌	✅	5
CRISP: Curriculum based Sequential neural decoders for Polar code family	❌	✅	❌	❌	✅	❌	✅	3
CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations	❌	✅	✅	✅	❌	❌	✅	4
Calibrating Multimodal Learning	✅	❌	✅	❌	✅	❌	✅	4
Can Forward Gradient Match Backpropagation?	❌	✅	✅	❌	❌	❌	✅	3
Can Large Language Models Reason about Program Invariants?	❌	❌	✅	✅	✅	❌	✅	4
Can Neural Network Memorization Be Localized?	❌	✅	✅	❌	❌	❌	✅	3
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?	❌	✅	✅	✅	✅	❌	✅	5
CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data	✅	✅	✅	❌	✅	❌	✅	5
Causal Bounds in Quasi-Markovian Graphs	✅	❌	❌	❌	❌	✅	✅	3
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants	✅	❌	❌	❌	❌	❌	❌	1
Causal Isotonic Calibration for Heterogeneous Treatment Effects	✅	✅	❌	❌	❌	✅	✅	4
Causal Modeling of Policy Interventions From Treatment-Outcome Sequences	✅	✅	✅	❌	❌	❌	✅	4
Causal Proxy Models for Concept-based Model Explanations	❌	✅	✅	✅	❌	❌	✅	4
Causal Strategic Classification: A Tale of Two Shifts	✅	✅	✅	✅	❌	❌	✅	5
Causal Structure Learning for Latent Intervened Non-stationary Data	✅	✅	✅	❌	❌	❌	✅	4
Cell-Free Latent Go-Explore	✅	✅	✅	❌	✅	✅	✅	6
Certified Robust Neural Networks: Generalization and Corruption Resistance	✅	✅	✅	✅	❌	❌	✅	5
Certifying Ensembles: A General Certification Theory with S-Lipschitzness	❌	❌	✅	❌	❌	❌	✅	2
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
Change is Hard: A Closer Look at Subpopulation Shift	❌	✅	✅	✅	❌	❌	✅	4
Chemically Transferable Generative Backmapping of Coarse-Grained Proteins	✅	✅	✅	✅	✅	❌	✅	6
ChiPFormer: Transferable Chip Placement via Offline Decision Transformer	✅	✅	✅	❌	✅	❌	✅	5
CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling	❌	❌	✅	✅	❌	❌	✅	3
ClimaX: A foundation model for weather and climate	❌	✅	✅	✅	✅	❌	✅	5
Cluster Explanation via Polyhedral Descriptions	❌	❌	✅	❌	✅	✅	✅	4
ClusterFuG: Clustering Fully connected Graphs by Multicut	✅	✅	✅	✅	✅	❌	✅	6
CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification	✅	❌	✅	❌	❌	❌	✅	3
CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis	✅	✅	✅	❌	✅	✅	✅	6
Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D	✅	✅	✅	❌	❌	❌	✅	4
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis	❌	❌	✅	❌	❌	❌	✅	2
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks	✅	❌	✅	❌	✅	❌	✅	4
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models	❌	✅	✅	❌	✅	❌	✅	4
Coder Reviewer Reranking for Code Generation	❌	❌	✅	❌	❌	❌	✅	2
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates	✅	✅	✅	✅	✅	❌	✅	6
Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator	✅	✅	✅	✅	✅	✅	✅	7
Collaborative Causal Inference with Fair Incentives	❌	✅	✅	❌	✅	❌	❌	3
Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits	✅	❌	❌	❌	❌	❌	✅	2
Combinatorial Neural Bandits	✅	❌	❌	❌	❌	❌	✅	2
Communication-Constrained Bandits under Additive Gaussian Noise	✅	❌	❌	❌	❌	❌	❌	1
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation	✅	❌	✅	❌	❌	❌	✅	3
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects	❌	✅	✅	❌	❌	❌	✅	3
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits	✅	✅	❌	❌	❌	❌	✅	3
Competitive Gradient Optimization	❌	✅	❌	❌	❌	❌	✅	2
Complementary Attention for Multi-Agent Reinforcement Learning	❌	✅	❌	❌	✅	❌	✅	3
Complexity of Block Coordinate Descent with Proximal Regularization and Applications to Wasserstein CP-dictionary Learning	✅	❌	✅	❌	❌	❌	✅	3
Composer: Creative and Controllable Image Synthesis with Composable Conditions	❌	❌	✅	❌	❌	❌	✅	2
Compositional Exemplars for In-context Learning	❌	✅	✅	✅	✅	❌	✅	5
Compositional Score Modeling for Simulation-Based Inference	✅	❌	✅	✅	❌	❌	✅	4
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data	✅	✅	✅	❌	✅	❌	✅	5
Compressing Tabular Data via Latent Variable Estimation	✅	❌	✅	❌	✅	❌	✅	4
Computational Asymmetries in Robust Classification	❌	✅	✅	✅	✅	✅	✅	6
Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions	✅	✅	❌	❌	❌	❌	✅	3
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings	✅	❌	✅	❌	❌	❌	✅	3
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction	❌	✅	❌	❌	✅	❌	✅	3
Concept-based Explanations for Out-of-Distribution Detectors	✅	✅	✅	✅	✅	❌	✅	6
Concurrent Shuffle Differential Privacy Under Continual Observation	✅	❌	❌	❌	❌	❌	❌	1
Conditional Graph Information Bottleneck for Molecular Relational Learning	❌	✅	✅	✅	✅	❌	✅	5
Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models	✅	✅	✅	✅	✅	❌	✅	6
Conditionally Strongly Log-Concave Generative Models	✅	✅	✅	❌	❌	❌	✅	4
Cones: Concept Neurons in Diffusion Models for Customized Generation	✅	❌	❌	❌	✅	❌	✅	3
Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation	❌	❌	✅	❌	✅	✅	✅	4
Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping	✅	✅	✅	✅	❌	❌	✅	5
Conformal Prediction Sets for Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift	✅	❌	✅	✅	❌	❌	✅	4
Conformal Prediction with Missing Values	✅	✅	✅	✅	❌	❌	✅	5
Conformalization of Sparse Generalized Linear Models	✅	✅	✅	❌	❌	❌	❌	3
Consistency Models	✅	❌	✅	❌	✅	❌	✅	4
Consistency of Multiple Kernel Clustering	❌	❌	✅	❌	✅	❌	✅	3
Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation	✅	❌	❌	❌	❌	❌	✅	2
Constrained Causal Bayesian Optimization	✅	✅	✅	❌	❌	❌	✅	4
Constrained Decision Transformer for Offline Safe Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Constrained Efficient Global Optimization of Expensive Black-box Functions	✅	❌	❌	❌	❌	❌	✅	2
Constrained Monotonic Neural Networks	❌	✅	✅	❌	✅	✅	❌	4
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching	✅	✅	✅	❌	❌	❌	✅	4
Constrained Phi-Equilibria	✅	❌	❌	❌	❌	❌	❌	1
Context Consistency Regularization for Label Sparsity in Time Series	✅	✅	✅	✅	✅	❌	✅	6
Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Contextual Combinatorial Bandits with Probabilistically Triggered Arms	✅	❌	✅	❌	❌	❌	✅	3
Contextual Conservative Interleaving Bandits	✅	❌	✅	❌	❌	❌	✅	3
Contextual Reliability: When Different Features Matter in Different Contexts	❌	❌	✅	✅	❌	❌	✅	3
Continual Learners are Incremental Model Generalizers	✅	❌	✅	❌	❌	❌	✅	3
Continual Learning in Linear Classification on Separable Data	✅	❌	❌	❌	❌	❌	❌	1
Continual Task Allocation in Meta-Policy Network via Sparse Prompting	✅	✅	✅	❌	❌	❌	✅	4
Continual Vision-Language Representation Learning with Off-Diagonal Information	❌	❌	✅	✅	✅	❌	✅	4
Continuation Path Learning for Homotopy Optimization	✅	✅	✅	❌	✅	❌	✅	5
Continuous Spatiotemporal Transformer	✅	✅	✅	✅	✅	❌	✅	6
Continuously Parameterized Mixture Models	❌	✅	✅	❌	❌	❌	✅	3
ContraBAR: Contrastive Bayes-Adaptive Deep RL	❌	✅	❌	❌	❌	❌	✅	2
Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining	❌	✅	✅	❌	✅	❌	✅	4
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Contrastive Learning Meets Homophily: Two Birds with One Stone	❌	❌	✅	✅	✅	❌	✅	4
Controllability-Aware Unsupervised Skill Discovery	✅	✅	✅	❌	✅	❌	✅	5
Controllable Neural Symbolic Regression	❌	✅	✅	❌	✅	❌	✅	4
Controlled Differential Equations on Long Sequences via Non-standard Wavelets	✅	✅	✅	✅	❌	❌	✅	5
Controlled Text Generation with Natural Language Instructions	❌	✅	✅	✅	❌	❌	✅	4
Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network	❌	❌	✅	❌	❌	❌	✅	2
Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification	✅	❌	✅	❌	❌	❌	✅	3
Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data	✅	❌	✅	❌	❌	❌	✅	3
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity	❌	✅	❌	❌	❌	❌	❌	1
Convex Geometry of ReLU-layers, Injectivity on the Ball and Local Reconstruction	✅	✅	✅	❌	❌	❌	✅	4
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders	❌	✅	✅	✅	✅	❌	✅	5
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Cooperative Open-ended Learning Framework for Zero-Shot Coordination	✅	❌	✅	❌	✅	❌	✅	4
Coordinate Descent Methods for Fractional Minimization	✅	✅	✅	❌	✅	❌	✅	5
Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets	✅	❌	✅	❌	❌	❌	✅	3
Correcting discount-factor mismatch in on-policy policy gradient methods	✅	✅	✅	❌	❌	❌	✅	4
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Counterfactual Analysis in Dynamic Latent State Models	✅	❌	✅	❌	✅	✅	✅	5
Counterfactual Identifiability of Bijective Causal Models	❌	✅	❌	❌	✅	❌	✅	3
Coupled Variational Autoencoder	✅	❌	✅	❌	❌	❌	✅	3
Covariate balancing using the integral probability metric for causal inference	✅	✅	✅	❌	✅	✅	✅	6
Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution	❌	❌	✅	❌	❌	❌	✅	2
Cramming: Training a Language Model on a single GPU in one day.	❌	✅	✅	✅	✅	❌	✅	5
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss	❌	✅	❌	❌	❌	❌	✅	2
Cross-Entropy Loss Functions: Theoretical Analysis and Applications	❌	❌	✅	✅	❌	❌	✅	3
Cross-Modal Fine-Tuning: Align then Refine	✅	✅	✅	✅	✅	❌	✅	6
CrossSplit: Mitigating Label Noise Memorization through Data Splitting	✅	✅	✅	✅	✅	❌	✅	6
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments	✅	❌	✅	❌	✅	❌	✅	4
Curious Replay for Model-based Adaptation	✅	✅	✅	❌	✅	✅	✅	6
Curriculum Co-disentangled Representation Learning across Multiple Environments for Social Recommendation	✅	❌	✅	✅	❌	❌	✅	4
Cut your Losses with Squentropy	❌	❌	✅	✅	❌	❌	✅	3
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization	✅	✅	✅	❌	❌	❌	✅	4
D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching	✅	❌	✅	✅	❌	❌	✅	4
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization	✅	✅	❌	❌	❌	❌	❌	2
DDGR: Continual Learning with Deep Diffusion-based Generative Replay	✅	✅	✅	❌	❌	❌	❌	3
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning	✅	❌	✅	❌	✅	✅	✅	5
DIVISION: Memory Efficient Training via Dual Activation Precision	✅	✅	✅	✅	✅	✅	✅	7
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference	✅	✅	✅	❌	❌	❌	✅	4
DRCFS: Doubly Robust Causal Feature Selection	✅	❌	✅	✅	❌	❌	✅	4
DRew: Dynamically Rewired Message Passing with Delay	❌	✅	✅	✅	✅	❌	✅	5
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation	❌	✅	✅	✅	❌	✅	✅	5
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm	✅	✅	✅	❌	✅	❌	✅	5
DUET: 2D Structured and Approximately Equivariant Representations	❌	✅	✅	✅	❌	❌	✅	4
Data Efficient Neural Scaling Law via Model Reusing	❌	✅	✅	❌	❌	❌	✅	3
Data Feedback Loops: Model-driven Amplification of Dataset Biases	✅	✅	✅	✅	❌	❌	✅	5
Data Poisoning Attacks Against Multimodal Encoders	❌	✅	✅	❌	❌	❌	✅	3
Data Representations’ Study of Latent Image Manifolds	❌	✅	✅	❌	❌	❌	❌	2
Data Structures for Density Estimation	✅	✅	✅	❌	❌	❌	✅	4
Data-Copying in Generative Models: A Formal Framework	✅	❌	✅	❌	❌	❌	✅	3
Data-Driven Subgroup Identification for Linear Regression	✅	✅	✅	✅	✅	❌	✅	6
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least	✅	✅	✅	❌	❌	❌	✅	4
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value	❌	✅	✅	✅	✅	❌	✅	5
Dataset Distillation with Convexified Implicit Gradients	✅	✅	✅	❌	✅	❌	✅	5
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models	❌	✅	✅	✅	✅	❌	✅	5
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent	❌	✅	✅	❌	✅	❌	✅	4
Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity	✅	❌	✅	❌	❌	✅	✅	4
Decoding Layer Saliency in Language Transformers	✅	❌	✅	✅	❌	❌	❌	3
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design	✅	✅	✅	✅	✅	❌	✅	6
Deep Anomaly Detection under Labeling Budget Constraints	✅	❌	✅	✅	❌	❌	✅	4
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach	❌	✅	✅	✅	❌	❌	✅	4
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search	❌	❌	✅	✅	❌	❌	✅	3
Deep Graph Representation Learning and Optimization for Influence Maximization	✅	✅	✅	❌	❌	❌	✅	4
Deep Laplacian-based Options for Temporally-Extended Exploration	✅	❌	✅	❌	❌	❌	✅	3
Deep Latent State Space Models for Time-Series Generation	✅	❌	✅	❌	✅	❌	✅	4
Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations	✅	❌	✅	✅	✅	❌	✅	5
Deep Regression Unlearning	✅	✅	✅	❌	✅	❌	✅	5
Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery	✅	✅	✅	❌	❌	❌	✅	4
Defects of Convolutional Decoder Networks in Frequency Representation	❌	❌	✅	❌	❌	❌	✅	2
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time	✅	✅	✅	❌	✅	❌	✅	5
Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback	✅	❌	✅	❌	❌	✅	✅	4
Delay-agnostic Asynchronous Coordinate Update Algorithm	✅	❌	✅	❌	✅	❌	✅	4
Delayed Bandits: When Do Intermediate Observations Help?	✅	❌	❌	❌	❌	❌	✅	2
Delayed Feedback in Kernel Bandits	✅	✅	❌	❌	❌	❌	✅	3
Delving into Noisy Label Detection with Clean Data	✅	✅	✅	✅	❌	❌	✅	5
Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum	✅	✅	✅	❌	❌	❌	✅	4
Demystifying Disagreement-on-the-Line in High Dimensions	❌	✅	✅	❌	❌	❌	✅	3
Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Denoising MCMC for Accelerating Diffusion-Based Generative Models	✅	✅	✅	❌	✅	❌	✅	5
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature	✅	✅	✅	❌	❌	❌	✅	4
Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score	✅	✅	✅	❌	✅	✅	✅	6
Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions	✅	❌	✅	❌	❌	❌	✅	3
Detecting Out-of-distribution Data through In-distribution Class Prior	❌	✅	✅	❌	✅	✅	❌	4
Deterministic equivalent and error universality of deep random features learning	❌	✅	❌	❌	❌	❌	❌	1
DevFormer: A Symmetric Transformer for Context-Aware Device Placement	❌	✅	✅	✅	✅	❌	✅	5
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation	✅	❌	✅	❌	❌	❌	✅	3
Difference of submodular minimization via DC programming	✅	✅	✅	❌	❌	❌	✅	4
Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding	❌	❌	✅	✅	❌	❌	✅	3
Differentiable Multi-Target Causal Bayesian Experimental Design	✅	✅	✅	❌	❌	❌	✅	4
Differentiable Simulations for Enhanced Sampling of Rare Events	❌	✅	✅	❌	❌	❌	✅	3
Differentiable Tree Operations Promote Compositional Generalization	❌	✅	✅	✅	✅	❌	✅	5
Differentiable and Transportable Structure Learning	✅	✅	❌	❌	❌	❌	✅	3
Differential Privacy has Bounded Impact on Fairness in Classification	❌	✅	✅	❌	❌	❌	✅	3
Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models	❌	✅	✅	✅	✅	✅	✅	6
Differentially Private Distributed Bayesian Linear Regression with MCMC	✅	✅	✅	❌	✅	✅	✅	6
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards	✅	❌	✅	❌	❌	❌	✅	3
Differentially Private Hierarchical Clustering with Provable Approximation Guarantees	✅	✅	✅	❌	❌	❌	✅	4
Differentially Private Optimization on Large Model at Small Cost	✅	✅	✅	❌	✅	❌	✅	5
Differentially Private Sharpness-Aware Training	✅	✅	✅	✅	✅	❌	✅	6
Differentially Private Stochastic Convex Optimization under a Quantile Loss Function	✅	❌	❌	❌	❌	❌	✅	2
Diffusion Based Representation Learning	❌	❌	✅	✅	✅	❌	✅	4
Diffusion Models are Minimax Optimal Distribution Estimators	❌	❌	❌	❌	❌	❌	❌	0
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?	❌	✅	✅	✅	❌	❌	✅	4
Diffusion Models for Black-Box Optimization	✅	✅	✅	❌	✅	❌	✅	5
Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing	❌	❌	✅	❌	✅	✅	✅	4
Dimensionality Reduction for General KDE Mode Finding	✅	❌	✅	❌	❌	❌	✅	3
Dink-Net: Neural Clustering on Large Graphs	✅	✅	✅	❌	✅	❌	✅	5
Direct Parameterization of Lipschitz-Bounded Deep Networks	✅	✅	✅	❌	✅	❌	✅	5
Directed Chain Generative Adversarial Networks	✅	✅	✅	❌	❌	❌	✅	4
Dirichlet Diffusion Score Model for Biological Sequence Generation	❌	✅	✅	✅	❌	✅	✅	5
DiscoBAX: Discovery of optimal intervention sets in genomic experiment design	✅	✅	✅	❌	❌	❌	✅	4
Discover and Cure: Concept-aware Mitigation of Spurious Correlation	✅	✅	✅	✅	❌	✅	✅	6
Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning	✅	✅	✅	❌	❌	❌	✅	4
Discovering Object-Centric Generalized Value Functions From Pixels	✅	✅	✅	❌	✅	❌	✅	5
Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models	✅	✅	✅	✅	✅	❌	✅	6
Discrete Key-Value Bottleneck	❌	✅	✅	✅	❌	❌	✅	4
Disentangled Generative Models for Robust Prediction of System Dynamics	❌	✅	❌	✅	❌	❌	✅	3
Disentangled Multi-Fidelity Deep Bayesian Active Learning	✅	✅	❌	❌	❌	❌	✅	3
Disentangled Multiplex Graph Representation Learning	✅	✅	✅	❌	❌	❌	✅	4
Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning	❌	✅	✅	❌	❌	❌	✅	3
Distance Weighted Supervised Learning for Offline Interaction Data	✅	✅	✅	✅	❌	❌	✅	5
Distilling Internet-Scale Vision-Language Models into Embodied Agents	❌	❌	✅	❌	❌	❌	✅	2
Distortion and Uncertainty Aware Loss for Panoramic Depth Completion	❌	❌	✅	❌	✅	❌	✅	3
Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost	✅	❌	❌	❌	❌	❌	✅	2
Distributed Linear Bandits under Communication Constraints	✅	❌	❌	❌	❌	❌	✅	2
Distribution Free Domain Generalization	✅	✅	✅	✅	❌	❌	✅	5
Distribution Free Prediction Sets for Node Classification	❌	✅	✅	✅	✅	❌	✅	5
Distribution-dependent McDiarmid-type Inequalities for Functions of Unbounded Interaction	❌	❌	❌	❌	❌	❌	❌	0
Distributional Offline Policy Evaluation with Predictive Error Guarantees	✅	✅	❌	❌	❌	❌	✅	3
Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference	✅	✅	✅	✅	✅	❌	✅	6
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation	✅	❌	✅	✅	✅	✅	✅	6
Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions	✅	✅	✅	✅	✅	❌	✅	6
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat	✅	✅	✅	✅	❌	❌	✅	5
Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling	✅	✅	✅	❌	❌	✅	✅	5
Do Machine Learning Models Learn Statistical Rules Inferred from Data?	✅	✅	✅	✅	❌	❌	✅	5
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks	✅	❌	✅	✅	✅	✅	✅	6
Do Perceptually Aligned Gradients Imply Robustness?	❌	✅	✅	✅	✅	❌	✅	5
Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detection	✅	❌	✅	✅	❌	❌	✅	4
Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark	❌	✅	✅	❌	❌	❌	✅	3
DoCoFL: Downlink Compression for Cross-Device Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule	❌	✅	✅	✅	❌	✅	✅	5
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm	✅	❌	✅	❌	❌	❌	✅	3
Does Continual Learning Equally Forget All Parameters?	✅	❌	✅	✅	❌	❌	✅	4
Does Sparsity Help in Learning Misspecified Linear Bandits?	✅	❌	❌	❌	❌	❌	❌	1
Does a Neural Network Really Encode Symbolic Concepts?	❌	✅	✅	❌	❌	❌	✅	3
Domain Adaptation for Time Series Under Feature and Label Shifts	✅	✅	✅	✅	✅	❌	✅	6
Double-Weighting for Covariate Shift Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Doubly Adversarial Federated Bandits	✅	✅	✅	❌	✅	❌	✅	5
Doubly Optimal No-Regret Learning in Monotone Games	✅	✅	❌	❌	❌	❌	✅	3
Dropout Reduces Underfitting	❌	✅	✅	✅	❌	❌	✅	4
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions	❌	✅	✅	✅	❌	❌	✅	4
Dual Focal Loss for Calibration	❌	✅	✅	✅	✅	❌	✅	5
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons	✅	✅	✅	✅	✅	❌	✅	6
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Constrained Submodular Optimization with Polylogarithmic Update Time	✅	❌	❌	❌	❌	❌	❌	1
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape	✅	❌	✅	✅	✅	✅	✅	6
Dynamical Linear Bandits	✅	✅	❌	❌	✅	❌	✅	4
Dynamics-inspired Neuromorphic Visual Representation Learning	✅	✅	✅	❌	✅	❌	✅	5
E$(n)$ Equivariant Message Passing Simplicial Networks	✅	❌	✅	✅	❌	❌	✅	4
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines	✅	✅	✅	❌	✅	✅	✅	6
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression	✅	❌	✅	❌	❌	❌	✅	3
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models	❌	❌	✅	❌	✅	❌	✅	3
EM-Network: Oracle Guided Self-distillation for Sequence Learning	❌	✅	✅	✅	✅	❌	✅	5
ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation	✅	❌	✅	✅	❌	❌	✅	4
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories	❌	❌	❌	❌	❌	❌	❌	0
Effective Neural Topic Modeling with Embedding Clustering Regularization	✅	✅	✅	❌	❌	❌	✅	4
Effective Structured Prompting by Meta-Learning and Representative Verbalizer	✅	❌	✅	✅	✅	❌	✅	5
Effective and Efficient Structural Inference with Reservoir Computing	✅	✅	✅	✅	✅	✅	✅	7
Effectively Using Public Data in Privacy Preserving Machine Learning	✅	❌	✅	❌	✅	❌	✅	4
Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation	✅	✅	✅	❌	❌	❌	✅	4
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction	❌	✅	✅	✅	✅	❌	✅	5
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration	✅	✅	✅	❌	✅	❌	✅	5
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization	✅	❌	✅	❌	❌	❌	✅	3
Efficient Graph Field Integrators Meet Point Clouds	✅	✅	✅	✅	✅	❌	✅	6
Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming	✅	✅	✅	✅	✅	❌	✅	6
Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network	✅	✅	✅	✅	✅	❌	✅	6
Efficient List-Decodable Regression using Batches	✅	❌	❌	❌	❌	❌	❌	1
Efficient Online Reinforcement Learning with Offline Data	✅	✅	✅	❌	❌	❌	✅	4
Efficient Parametric Approximations of Neural Network Function Space Distance	✅	❌	✅	❌	❌	❌	✅	3
Efficient Personalized Federated Learning via Sparse Model-Adaptation	✅	✅	✅	✅	✅	❌	✅	6
Efficient Quantum Algorithms for Quantum Optimal Control	✅	❌	❌	❌	❌	❌	✅	2
Efficient RL via Disentangled Environment and Agent Representations	✅	✅	✅	❌	✅	❌	✅	5
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language	❌	✅	✅	✅	✅	❌	✅	5
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations	✅	✅	✅	✅	❌	❌	✅	5
Efficient Training of Language Models using Few-Shot Learning	✅	❌	✅	❌	❌	❌	✅	3
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification	❌	❌	✅	✅	❌	✅	✅	4
Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling	✅	✅	✅	✅	✅	❌	✅	6
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian	❌	✅	✅	✅	✅	✅	✅	6
Efficient displacement convex optimization with particle gradient descent	❌	✅	❌	❌	❌	❌	✅	2
Efficient preconditioned stochastic gradient descent for estimation in latent variable models	✅	✅	✅	❌	❌	❌	✅	4
Efficiently predicting high resolution mass spectra with graph neural networks	✅	✅	✅	✅	✅	❌	✅	6
Eliminating Adversarial Noise via Information Discard and Robust Representation Restoration	✅	✅	✅	❌	❌	❌	✅	4
Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning	❌	✅	❌	❌	❌	✅	✅	3
Emergence of Sparse Representations from Noise	❌	✅	✅	❌	❌	❌	✅	3
Emergent Agentic Transformer from Chain of Hindsight Experience	✅	❌	✅	❌	✅	❌	✅	4
Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions	❌	✅	✅	❌	❌	❌	✅	3
Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets	❌	✅	❌	❌	✅	❌	✅	3
End-to-End Full-Atom Antibody Design	❌	✅	✅	✅	✅	❌	✅	5
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective	✅	✅	✅	❌	❌	❌	✅	4
End-to-End Multi-Object Detection with a Regularized Mixture Model	❌	✅	✅	✅	✅	❌	✅	5
End-to-end Differentiable Clustering with Associative Memories	✅	✅	✅	❌	✅	❌	✅	5
End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization	✅	✅	✅	❌	❌	❌	✅	4
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments	✅	❌	✅	❌	❌	❌	❌	2
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language	❌	✅	✅	✅	✅	✅	✅	6
Entity Divider with Language Grounding in Multi-Agent Reinforcement Learning	❌	✅	✅	✅	❌	❌	✅	4
Entropy-driven Unsupervised Keypoint Representation Learning in Videos	❌	✅	✅	❌	✅	❌	✅	4
Equivariance with Learned Canonicalization Functions	✅	✅	✅	✅	✅	❌	✅	6
Equivariant Architectures for Learning in Deep Weight Spaces	❌	✅	✅	✅	❌	❌	✅	4
Equivariant Polynomials for Graph Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Escaping saddle points in zeroth-order optimization: the power of two-point estimators	✅	✅	✅	❌	❌	❌	✅	4
Estimating Causal Effects using a Multi-task Deep Ensemble	❌	✅	✅	✅	❌	❌	✅	4
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms	✅	✅	✅	✅	❌	❌	❌	4
Estimating Joint Treatment Effects by Combining Multiple Experiments	❌	❌	✅	❌	❌	❌	✅	2
Estimating Possible Causal Effects with Latent Variables via Adjustment	✅	❌	❌	❌	❌	❌	✅	2
Estimating the Contamination Factor’s Distribution in Unsupervised Anomaly Detection	❌	✅	✅	❌	❌	❌	✅	3
Estimation Beyond Data Reweighting: Kernel Method of Moments	✅	✅	❌	✅	❌	❌	✅	4
Evaluating Self-Supervised Learning via Risk Decomposition	✅	✅	✅	✅	❌	✅	✅	6
Evaluating Unsupervised Denoising Requires Unsupervised Metrics	✅	✅	✅	✅	❌	❌	✅	5
Eventual Discounting Temporal Logic Counterfactual Experience Replay	✅	✅	❌	❌	❌	❌	✅	3
Everyone’s Preference Changes Differently: A Weighted Multi-Interest Model For Retrieval	❌	✅	✅	✅	✅	✅	✅	6
Evidential Interactive Learning for Medical Image Captioning	❌	✅	✅	✅	✅	❌	✅	5
Evolving Semantic Prototype Improves Generative Zero-Shot Learning	❌	❌	✅	✅	❌	❌	✅	3
Ewald-based Long-Range Message Passing for Molecular Graphs	❌	❌	✅	✅	✅	❌	✅	4
Exact Inference in High-order Structured Prediction	❌	❌	✅	❌	❌	❌	✅	2
Existence and Estimation of Critical Batch Size for Training Generative Adversarial Networks with Two Time-Scale Update Rule	✅	✅	✅	❌	✅	✅	✅	6
Expectation-Complete Graph Representations with Homomorphisms	✅	✅	✅	✅	✅	❌	✅	6
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization	❌	✅	✅	✅	✅	❌	✅	5
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making	✅	✅	✅	❌	❌	❌	✅	4
Exphormer: Sparse Transformers for Graphs	❌	✅	✅	✅	✅	❌	✅	5
Explainability as statistical inference	❌	❌	✅	✅	❌	❌	✅	3
Explainable Data-Driven Optimization: From Context to Decision and Back Again	✅	✅	✅	❌	✅	✅	✅	6
Explaining Reinforcement Learning with Shapley Values	❌	✅	✅	❌	❌	❌	✅	3
Explaining the effects of non-convergent MCMC in the training of Energy-Based Models	❌	❌	✅	❌	❌	❌	✅	2
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization	❌	❌	✅	✅	❌	❌	✅	3
Exploring Chemical Space with Score-based Out-of-distribution Generation	❌	✅	✅	❌	✅	❌	✅	4
Exploring Model Dynamics for Accumulative Poisoning Discovery	✅	✅	✅	❌	✅	❌	✅	5
Exploring the Benefits of Training Expert Language Models over Instruction Tuning	❌	✅	✅	✅	❌	❌	✅	4
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks	✅	✅	✅	✅	✅	❌	✅	6
Exponential Smoothing for Off-Policy Learning	✅	❌	✅	❌	❌	❌	✅	3
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti’s Theorem for Markov Chains	✅	❌	✅	❌	❌	❌	✅	3
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms	✅	✅	✅	❌	✅	❌	✅	5
Extrapolated Random Tree for Regression	✅	✅	✅	✅	✅	❌	✅	6
Extrapolative Controlled Sequence Generation via Iterative Refinement	❌	✅	✅	❌	❌	❌	✅	3
FAENet: Frame Averaging Equivariant GNN for Materials Modeling	❌	✅	✅	✅	✅	✅	✅	6
FAIRER: Fairness as Decision Rationale Alignment	✅	❌	✅	✅	❌	❌	✅	4
FARE: Provably Fair Representation Learning with Practical Certificates	❌	✅	✅	✅	✅	❌	✅	5
FLEX: an Adaptive Exploration Algorithm for Nonlinear Systems	✅	✅	✅	❌	❌	❌	✅	4
FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation	❌	✅	✅	❌	✅	❌	✅	4
FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning	✅	✅	✅	✅	❌	❌	✅	5
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels	❌	❌	✅	❌	❌	❌	✅	2
Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction	✅	✅	✅	✅	✅	❌	✅	6
Fair Densities via Boosting the Sufficient Statistics of Exponential Families	✅	✅	✅	✅	✅	❌	✅	6
Fair Neighbor Embedding	❌	✅	✅	❌	❌	❌	✅	3
Fair and Accurate Decision Making through Group-Aware Learning	✅	✅	✅	✅	✅	❌	✅	6
Fair and Optimal Classification via Post-Processing	✅	✅	✅	✅	✅	❌	✅	6
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning	❌	❌	✅	✅	❌	❌	✅	3
Fair yet Asymptotically Equal Collaborative Learning	✅	✅	✅	❌	✅	❌	✅	5
Fairness in Matching under Uncertainty	❌	❌	✅	❌	❌	❌	✅	2
Fairness in Streaming Submodular Maximization over a Matroid Constraint	✅	✅	✅	❌	❌	❌	✅	4
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning	✅	✅	✅	❌	✅	❌	✅	5
Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization	✅	❌	✅	❌	✅	❌	❌	3
Fast Algorithms for Distributed k-Clustering with Outliers	✅	❌	✅	❌	✅	❌	✅	4
Fast Combinatorial Algorithms for Min Max Correlation Clustering	✅	✅	✅	❌	❌	❌	✅	4
Fast Excess Risk Rates via Offset Rademacher Complexity	❌	❌	❌	❌	❌	❌	❌	0
Fast Federated Machine Unlearning with Nonlinear Functional Theory	❌	❌	✅	❌	✅	✅	✅	4
Fast Inference from Transformers via Speculative Decoding	✅	❌	✅	❌	✅	❌	✅	4
Fast Online Node Labeling for Very Large Graphs	✅	✅	✅	❌	❌	❌	✅	4
Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control	✅	✅	✅	✅	❌	❌	✅	5
Fast Private Kernel Density Estimation via Locality Sensitive Quantization	✅	✅	✅	❌	❌	❌	✅	4
Fast Rates for Maximum Entropy Exploration	✅	✅	✅	❌	❌	❌	✅	4
Fast Rates in Time-Varying Strongly Monotone Games	✅	❌	✅	❌	❌	❌	✅	3
Fast Sampling of Diffusion Models via Operator Learning	❌	✅	✅	❌	✅	❌	✅	4
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization	✅	✅	✅	❌	✅	❌	✅	5
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective	✅	✅	✅	❌	✅	❌	✅	5
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization	✅	❌	✅	❌	❌	❌	✅	3
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization	✅	❌	❌	❌	❌	❌	❌	1
FeDXL: Provable Federated Learning for Deep X-Risk Optimization	✅	✅	✅	✅	✅	❌	✅	6
Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation	❌	✅	✅	✅	❌	❌	✅	4
Feature Expansion for Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Feature Programming for Multivariate Time Series Prediction	❌	✅	✅	❌	✅	❌	✅	4
Feature learning in deep classifiers through Intermediate Neural Collapse	❌	✅	✅	❌	✅	❌	✅	4
Featured Graph Coarsening with Similarity Guarantees	✅	❌	✅	✅	❌	❌	✅	4
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction	✅	❌	✅	❌	❌	❌	✅	3
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction	✅	✅	✅	✅	❌	❌	✅	5
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization	✅	✅	✅	✅	✅	✅	✅	7
FedDisco: Federated Learning with Discrepancy-Aware Collaboration	✅	✅	✅	❌	✅	❌	✅	5
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization	✅	✅	✅	✅	✅	✅	✅	7
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models	✅	❌	✅	✅	✅	❌	✅	5
Federated Adversarial Learning: A Framework with Convergence Analysis	✅	❌	❌	❌	❌	❌	✅	2
Federated Conformal Predictors for Distributed Uncertainty Quantification	✅	✅	✅	✅	❌	❌	✅	5
Federated Heavy Hitter Recovery under Linear Sketching	✅	✅	✅	❌	❌	❌	✅	4
Federated Linear Contextual Bandits with User-level Differential Privacy	✅	❌	❌	❌	❌	❌	❌	1
Federated Online and Bandit Convex Optimization	✅	❌	❌	❌	❌	❌	❌	1
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection	❌	✅	✅	✅	✅	✅	✅	6
Few-Sample Feature Selection via Feature Manifold Learning	✅	✅	✅	✅	✅	❌	✅	6
Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction	✅	✅	✅	✅	✅	❌	✅	6
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation	✅	❌	✅	❌	✅	❌	✅	4
Finding Generalization Measures by Contrasting Signal and Noise	✅	✅	✅	❌	✅	❌	✅	5
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs	❌	✅	✅	✅	❌	❌	✅	4
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron	❌	❌	❌	❌	❌	❌	✅	1
Fisher Information Embedding for Node and Graph Learning	❌	✅	✅	✅	✅	❌	✅	5
Flash: Concept Drift Adaptation in Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU	✅	✅	✅	❌	✅	❌	✅	5
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization	❌	❌	✅	❌	❌	❌	✅	2
Flexible Phase Dynamics for Bio-Plausible Contrastive Learning	❌	✅	✅	❌	❌	❌	✅	3
Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal	❌	✅	✅	✅	❌	❌	✅	4
Forget Unlearning: Towards True Data-Deletion in Machine Learning	✅	❌	❌	❌	❌	❌	✅	2
Formalizing Preferences Over Runtime Distributions	❌	✅	✅	❌	❌	❌	❌	2
Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space	✅	✅	❌	❌	❌	❌	✅	3
Fourmer: An Efficient Global Modeling Paradigm for Image Restoration	❌	✅	✅	❌	❌	❌	✅	3
Fractional Denoising for 3D Molecular Pre-training	✅	✅	✅	✅	❌	❌	✅	5
Free-Form Variational Inference for Gaussian Process State-Space Models	✅	✅	✅	❌	✅	❌	✅	5
From Adaptive Query Release to Machine Unlearning	✅	❌	❌	❌	❌	❌	❌	1
From Hypergraph Energy Functions to Hypergraph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning	✅	✅	❌	❌	❌	❌	✅	3
From Perception to Programs: Regularize, Overparameterize, and Amortize	✅	❌	✅	❌	❌	❌	✅	3
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks	✅	❌	✅	✅	❌	❌	✅	4
From Robustness to Privacy and Back	✅	❌	✅	❌	❌	❌	❌	2
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders	✅	❌	✅	❌	❌	❌	✅	3
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes	✅	❌	✅	✅	✅	❌	✅	5
Fully Dynamic Submodular Maximization over Matroids	✅	❌	❌	❌	❌	❌	❌	1
Fully-Adaptive Composition in Differential Privacy	❌	❌	❌	❌	❌	❌	❌	0
Function-Space Regularization in Neural Networks: A Probabilistic Perspective	❌	✅	✅	✅	❌	❌	✅	4
Functional Neural Networks: Shift invariant models for functional data with applications to EEG classification	❌	❌	✅	✅	✅	❌	✅	4
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods	❌	❌	✅	❌	❌	❌	✅	2
Fundamental Tradeoffs in Learning with Prior Information	❌	❌	✅	❌	❌	❌	❌	1
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning	✅	✅	✅	✅	✅	✅	✅	7
Future-conditioned Unsupervised Pretraining for Decision Transformer	✅	✅	✅	❌	✅	❌	✅	5
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks	✅	✅	✅	❌	✅	❌	✅	5
GC-Flow: A Graph-Based Flow Network for Effective Clustering	❌	✅	✅	✅	✅	❌	✅	5
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models	❌	✅	✅	❌	✅	❌	✅	4
GFlowNet-EM for Learning Compositional Latent Variable Models	✅	✅	✅	✅	✅	✅	✅	7
GFlowOut: Dropout with Generative Flow Networks	✅	✅	✅	✅	✅	❌	✅	6
GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations	✅	❌	✅	❌	❌	❌	✅	3
GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming	✅	✅	❌	❌	✅	✅	✅	5
GNOT: A General Neural Operator Transformer for Operator Learning	❌	✅	✅	❌	✅	✅	✅	5
GOAT: A Global Transformer on Large-scale Graphs	✅	✅	✅	✅	✅	❌	✅	6
GRAFENNE: Learning on Graphs with Heterogeneous and Dynamic Feature Sets	❌	✅	✅	✅	✅	❌	✅	5
GREAD: Graph Neural Reaction-Diffusion Networks	✅	✅	✅	✅	✅	✅	✅	7
Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients	❌	✅	❌	❌	✅	✅	✅	4
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents	❌	✅	✅	❌	❌	❌	✅	3
GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency	✅	❌	✅	❌	✅	❌	✅	4
General Covariance Data Augmentation for Neural PDE Solvers	❌	✅	✅	❌	❌	❌	✅	3
General Sequential Episodic Memory Model	❌	✅	❌	❌	❌	❌	✅	2
Generalization Analysis for Contrastive Representation Learning	❌	❌	❌	❌	❌	❌	❌	0
Generalization Bounds using Data-Dependent Fractal Dimensions	❌	✅	✅	✅	❌	❌	✅	4
Generalization on the Unseen, Logic Reasoning and Degree Curriculum	✅	✅	❌	❌	✅	❌	✅	4
Generalized Disparate Impact for Configurable Fairness Solutions in ML	❌	✅	✅	✅	✅	✅	✅	6
Generalized Implicit Follow-The-Regularized-Leader	✅	❌	✅	❌	❌	❌	✅	3
Generalized Polyak Step Size for First Order Optimization with Momentum	✅	❌	✅	❌	❌	❌	✅	3
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost	✅	✅	✅	❌	❌	❌	✅	4
Generalized Teacher Forcing for Learning Chaotic Dynamics	✅	✅	✅	✅	❌	❌	✅	5
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization	✅	✅	✅	❌	❌	❌	✅	4
Generalizing Neural Wave Functions	✅	✅	✅	❌	✅	❌	✅	5
Generated Graph Detection	❌	✅	✅	❌	❌	❌	✅	3
Generating Language Corrections for Teaching Physical Control Tasks	✅	✅	✅	✅	✅	✅	✅	7
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds	❌	✅	✅	❌	✅	❌	✅	4
Generating Private Synthetic Data with Genetic Algorithms	✅	✅	✅	❌	❌	❌	✅	4
Generative Adversarial Symmetry Discovery	❌	✅	✅	❌	❌	❌	✅	3
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting	❌	✅	✅	✅	❌	❌	✅	4
Generative Decoding of Visual Stimuli	❌	❌	✅	❌	❌	❌	✅	2
Generative Graph Dictionary Learning	✅	✅	✅	✅	✅	❌	❌	5
Generative Pretraining for Black-Box Optimization	✅	✅	✅	❌	✅	❌	✅	5
Geometric Autoencoders - What You See is What You Decode	✅	✅	✅	❌	❌	❌	✅	4
Geometric Clifford Algebra Networks	✅	❌	❌	✅	✅	❌	✅	4
Geometric Latent Diffusion Models for 3D Molecule Generation	✅	✅	✅	✅	❌	❌	✅	5
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration	✅	✅	✅	❌	✅	❌	✅	5
Gibbsian Polar Slice Sampling	✅	✅	✅	✅	✅	✅	✅	7
Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models	❌	✅	✅	❌	✅	❌	❌	3
Global Context Vision Transformers	✅	✅	✅	✅	✅	❌	✅	6
Global Optimization with Parametric Function Approximation	✅	❌	✅	✅	❌	❌	✅	4
Global Selection of Contrastive Batches via Optimization on Sample Permutations	✅	✅	✅	✅	✅	✅	✅	7
Global optimality for Euclidean CCCP under Riemannian convexity	✅	❌	❌	❌	❌	❌	❌	1
Global optimality of Elman-type RNNs in the mean-field regime	❌	✅	❌	❌	❌	❌	✅	2
Go Beyond Imagination: Maximizing Episodic Reachability with World Models	✅	❌	✅	❌	✅	❌	✅	4
Gradient Descent Converges Linearly for Logistic Regression on Separable Data	✅	❌	✅	❌	❌	❌	✅	3
Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks	❌	❌	❌	❌	❌	❌	✅	1
Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond	❌	❌	✅	❌	❌	❌	✅	2
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space	❌	❌	❌	❌	❌	❌	❌	0
Gradient-Free Structured Pruning with Unlabeled Data	✅	❌	✅	✅	✅	❌	✅	5
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space	✅	✅	✅	✅	❌	❌	✅	5
Graph Contrastive Backdoor Attacks	✅	❌	✅	❌	❌	❌	✅	3
Graph Generative Model for Benchmarking Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Graph Inductive Biases in Transformers without Message Passing	❌	✅	✅	✅	✅	❌	✅	5
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication	✅	✅	✅	✅	✅	❌	✅	6
Graph Mixup with Soft Alignments	✅	✅	✅	✅	❌	❌	✅	5
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure	❌	✅	✅	✅	❌	❌	✅	4
Graph Neural Networks with Learnable and Optimal Polynomial Bases	✅	✅	✅	✅	❌	❌	✅	5
Graph Neural Tangent Kernel: Convergence on Large Graphs	❌	✅	✅	✅	✅	❌	✅	5
Graph Positional Encoding via Random Feature Propagation	✅	❌	✅	✅	✅	❌	✅	5
Graph Reinforcement Learning for Network Control via Bi-Level Optimization	❌	✅	✅	❌	✅	❌	✅	4
Graph Switching Dynamical Systems	✅	✅	✅	✅	✅	❌	✅	6
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks	✅	✅	✅	✅	❌	❌	✅	5
Graphically Structured Diffusion Models	✅	✅	❌	❌	✅	❌	✅	4
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement	✅	✅	✅	✅	❌	❌	✅	5
Grounding Language Models to Images for Multimodal Inputs and Outputs	❌	✅	✅	❌	✅	✅	✅	5
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Group Equivariant Fourier Neural Operators for Partial Differential Equations	❌	✅	✅	✅	✅	❌	✅	5
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning	✅	❌	✅	❌	✅	❌	✅	4
Guiding Pretraining in Reinforcement Learning with Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features	✅	✅	✅	✅	✅	❌	✅	6
HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption	✅	✅	✅	✅	✅	❌	✅	6
HOPE: High-order Graph ODE For Modeling Interacting Dynamics	✅	❌	✅	✅	❌	❌	✅	4
Half-Hop: A graph upsampling approach for slowing down message passing	❌	✅	✅	✅	✅	❌	✅	5
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing	✅	✅	✅	❌	✅	❌	✅	5
Harmonic Neural Networks	❌	✅	❌	❌	✅	✅	✅	4
HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation	❌	✅	✅	❌	❌	❌	✅	3
Hidden Symmetries of ReLU Networks	❌	❌	❌	❌	❌	❌	✅	1
Hiding Data Helps: On the Benefits of Masking for Sparse Coding	✅	✅	❌	❌	✅	❌	✅	4
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles	❌	✅	✅	✅	✅	✅	✅	6
Hierarchical Diffusion for Offline Decision Making	✅	✅	✅	❌	❌	❌	✅	4
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction	✅	✅	✅	❌	❌	❌	✅	4
Hierarchical Imitation Learning with Vector Quantized Models	✅	❌	❌	❌	✅	❌	✅	3
Hierarchical Neural Coding for Controllable CAD Model Generation	❌	✅	✅	✅	✅	❌	✅	5
Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs	✅	❌	❌	✅	❌	❌	✅	3
Hierarchies of Reward Machines	✅	✅	✅	❌	✅	❌	✅	5
High Fidelity Image Counterfactuals with Probabilistic Causal Models	❌	✅	✅	✅	❌	❌	✅	4
High Probability Convergence of Stochastic Gradient Methods	✅	❌	❌	❌	❌	❌	❌	1
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance	✅	❌	❌	❌	❌	❌	❌	1
High-dimensional Clustering onto Hamiltonian Cycle	✅	✅	✅	❌	❌	❌	✅	4
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors	✅	✅	❌	❌	❌	❌	✅	3
Hindsight Learning for MDPs with Exogenous Inputs	✅	✅	✅	✅	❌	❌	✅	5
Homomorphism AutoEncoder -- Learning Group Structured Representations from Observed Transitions	❌	✅	✅	❌	✅	❌	✅	4
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds	✅	❌	❌	❌	❌	❌	❌	1
How Bad is Top-$K$ Recommendation under Competing Content Creators?	✅	❌	✅	❌	❌	❌	✅	3
How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding	❌	✅	✅	❌	❌	❌	✅	3
How Does Information Bottleneck Help Deep Learning?	❌	✅	✅	❌	❌	❌	✅	3
How Jellyfish Characterise Alternating Group Equivariant Neural Networks	✅	❌	❌	❌	❌	❌	❌	1
How Many Perturbations Break This Model? Evaluating Robustness Beyond Adversarial Accuracy	✅	✅	✅	❌	✅	❌	✅	5
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?	❌	❌	✅	❌	❌	❌	✅	2
How much does Initialization Affect Generalization?	❌	❌	✅	❌	❌	❌	✅	2
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control	✅	✅	✅	✅	✅	❌	✅	6
How to address monotonicity for model risk management?	✅	✅	✅	❌	❌	❌	✅	4
Human-Timescale Adaptation in an Open-Ended Task Space	❌	❌	✅	❌	✅	❌	✅	3
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection	✅	✅	✅	❌	✅	❌	✅	5
Hyena Hierarchy: Towards Larger Convolutional Language Models	✅	✅	✅	❌	✅	❌	✅	5
HyperTuning: Toward Adapting Large Language Models without Back-propagation	✅	❌	✅	❌	❌	❌	✅	3
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
Hyperbolic Image-text Representations	❌	❌	✅	✅	✅	❌	✅	4
Hyperbolic Representation Learning: Revisiting and Advancing	✅	❌	✅	✅	❌	❌	✅	4
Hyperparameters in Reinforcement Learning and How To Tune Them	❌	✅	✅	✅	✅	❌	✅	5
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information	❌	✅	✅	❌	✅	❌	✅	4
Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability	❌	❌	❌	❌	❌	❌	✅	1
I$^2$SB: Image-to-Image Schrödinger Bridge	✅	✅	✅	✅	❌	❌	✅	5
ILLUME: Rationalizing Vision-Language Models through Human Interactions	❌	✅	✅	✅	✅	❌	✅	5
IRNeXt: Rethinking Convolutional Network Design for Image Restoration	❌	✅	✅	✅	✅	❌	✅	5
Identifiability and Generalizability in Constrained Inverse Reinforcement Learning	✅	✅	✅	❌	❌	✅	✅	5
Identifiability of Label Noise Transition Matrix	✅	✅	✅	❌	❌	❌	✅	4
Identification of the Adversary from a Single Adversarial Example	❌	✅	✅	❌	✅	❌	✅	4
Identifying Interpretable Subspaces in Image Representations	✅	❌	✅	✅	❌	❌	✅	4
Identifying Useful Learnwares for Heterogeneous Label Spaces	✅	❌	✅	❌	✅	❌	✅	4
Image Restoration with Mean-Reverting Stochastic Differential Equations	❌	✅	✅	❌	✅	❌	✅	4
Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression	❌	✅	✅	❌	❌	❌	✅	3
Image generation with shortest path diffusion	✅	✅	✅	✅	❌	❌	✅	5
Implicit Graph Neural Networks: A Monotone Operator Viewpoint	✅	✅	✅	✅	❌	❌	✅	5
Implicit Jacobian regularization weighted with impurity of probability output	✅	❌	✅	✅	❌	❌	✅	4
Implicit Neural Spatial Representations for Time-dependent PDEs	✅	✅	❌	❌	✅	❌	✅	4
Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression	❌	❌	❌	❌	❌	❌	✅	1
Importance Weighted Expectation-Maximization for Protein Sequence Design	✅	✅	✅	✅	✅	❌	✅	6
Improved Active Multi-Task Representation Learning via Lasso	✅	❌	✅	❌	❌	❌	✅	3
Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback	✅	❌	❌	❌	❌	❌	✅	2
Improved Algorithms for White-Box Adversarial Streams	✅	❌	❌	❌	❌	❌	❌	1
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions	❌	❌	❌	❌	❌	❌	❌	0
Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis	❌	❌	❌	❌	❌	❌	✅	1
Improved Online Conformal Prediction via Strongly Adaptive Online Learning	✅	✅	✅	❌	❌	✅	✅	5
Improved Online Learning Algorithms for CTR Prediction in Ad Auctions	✅	❌	❌	❌	❌	❌	❌	1
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation	✅	❌	✅	❌	❌	❌	✅	3
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs	✅	❌	✅	❌	✅	❌	✅	4
Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process	✅	❌	✅	❌	✅	❌	✅	4
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples	✅	✅	✅	❌	❌	❌	✅	4
Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics	✅	✅	✅	❌	✅	❌	✅	5
Improving Bi-level Optimization Based Methods with Inspiration from Humans’ Classroom Study Techniques	✅	❌	✅	✅	✅	✅	✅	6
Improving Expert Predictions with Conformal Prediction	✅	✅	✅	✅	✅	✅	✅	7
Improving Fair Training under Correlation Shifts	✅	❌	✅	❌	✅	❌	✅	4
Improving Graph Generation by Restricting Graph Bandwidth	✅	✅	✅	✅	❌	❌	✅	5
Improving Graph Neural Networks with Learnable Propagation Operators	❌	❌	✅	✅	✅	❌	✅	4
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models	✅	✅	✅	✅	✅	❌	✅	6
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling	❌	✅	✅	✅	✅	❌	✅	5
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models	❌	✅	✅	✅	❌	✅	✅	5
Improving Visual Prompt Tuning for Self-supervised Vision Transformers	✅	✅	✅	❌	❌	❌	✅	4
Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints	✅	✅	✅	✅	❌	❌	✅	5
Improving the Model Consistency of Decentralized Federated Learning	✅	❌	✅	✅	❌	❌	✅	4
In Search for a Generalizable Method for Source Free Domain Adaptation	❌	❌	✅	✅	❌	❌	✅	3
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation	❌	✅	✅	✅	❌	❌	✅	4
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation	❌	✅	✅	❌	❌	✅	✅	4
InGram: Inductive Knowledge Graph Embedding via Relation Graphs	✅	✅	✅	✅	✅	❌	✅	6
IncDSI: Incrementally Updatable Document Retrieval	✅	✅	✅	✅	✅	❌	✅	6
Incentivizing Exploration with Linear Contexts and Combinatorial Actions	✅	❌	❌	❌	❌	❌	❌	1
Individually Fair Learning with One-Sided Feedback	✅	❌	❌	❌	❌	❌	❌	1
Inferring Relational Potentials in Interacting Systems	✅	✅	✅	✅	✅	✅	✅	7
Infinite Action Contextual Bandits with Reusable Data Exhaust	✅	✅	✅	✅	❌	❌	✅	5
Inflow, Outflow, and Reciprocity in Machine Learning	❌	❌	✅	✅	❌	❌	✅	3
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models	❌	❌	✅	✅	✅	❌	✅	4
InfoOT: Information Maximizing Optimal Transport	❌	✅	✅	✅	❌	❌	✅	4
Information-Theoretic State Space Model for Multi-View Reinforcement Learning	✅	✅	✅	✅	✅	✅	✅	7
Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning	❌	❌	✅	❌	❌	❌	❌	1
Input Perturbation Reduces Exposure Bias in Diffusion Models	✅	✅	✅	❌	✅	✅	✅	6
Input uncertainty propagation through trained neural networks	✅	✅	✅	❌	✅	✅	✅	6
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models	✅	✅	✅	❌	❌	❌	✅	4
Instrumental Variable Estimation of Average Partial Causal Effects	✅	❌	✅	✅	❌	❌	✅	4
Integrating Prior Knowledge in Contrastive Learning with Kernel	✅	✅	✅	✅	✅	❌	✅	6
Interactive Object Placement with Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Internally Rewarded Reinforcement Learning	❌	✅	✅	✅	❌	❌	✅	4
Internet Explorer: Targeted Representation Learning on the Open Web	✅	✅	✅	✅	✅	❌	✅	6
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics	✅	❌	✅	❌	✅	❌	✅	4
Interpretable Neural-Symbolic Concept Reasoning	❌	✅	✅	✅	✅	✅	✅	6
Interval Bound Interpolation for Few-shot Learning with Few Tasks	✅	✅	✅	✅	✅	❌	✅	6
Interventional Causal Representation Learning	✅	✅	❌	✅	❌	❌	✅	4
Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs	❌	✅	✅	❌	❌	❌	✅	3
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning	❌	❌	❌	❌	❌	❌	❌	0
Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames	✅	✅	✅	✅	❌	❌	✅	5
Inverse Reinforcement Learning without Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Investigating the Role of Model-Based Learning in Exploration and Transfer	❌	❌	✅	❌	❌	❌	✅	2
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?	✅	❌	❌	❌	❌	❌	❌	1
Is Learning Summary Statistics Necessary for Likelihood-free Inference?	✅	❌	❌	✅	❌	❌	✅	3
Is Overfitting Necessary for Implicit Video Representation?	✅	❌	✅	❌	✅	❌	✅	4
Iterative Approximate Cross-Validation	❌	✅	❌	✅	❌	❌	✅	3
JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift	❌	✅	✅	❌	❌	❌	✅	3
Jump-Start Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs	✅	❌	✅	❌	❌	❌	✅	3
KDEformer: Accelerating Transformers via Kernel Density Estimation	✅	❌	✅	✅	❌	❌	✅	4
Kernel Logistic Regression Approximation of an Understandable ReLU Neural Network	❌	❌	✅	✅	❌	❌	✅	3
Kernel QuantTree	✅	✅	✅	❌	❌	❌	✅	4
Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation	❌	✅	✅	✅	❌	❌	✅	4
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework	✅	✅	✅	❌	❌	❌	✅	4
LEVER: Learning to Verify Language-to-Code Generation with Execution	❌	✅	✅	✅	❌	❌	✅	4
LIV: Language-Image Representations and Rewards for Robotic Control	✅	✅	✅	❌	✅	❌	✅	5
LSDS++ : Dual Sampling for Accelerated k-means++	✅	❌	✅	❌	❌	❌	✅	3
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity	✅	✅	✅	✅	✅	❌	✅	6
Label differential privacy and private training data release	✅	❌	✅	✅	❌	❌	✅	4
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning	✅	❌	✅	❌	❌	❌	❌	2
Language Instructed Reinforcement Learning for Human-AI Coordination	✅	✅	✅	❌	❌	❌	✅	4
Large Language Models Can Be Easily Distracted by Irrelevant Context	❌	❌	✅	❌	❌	❌	✅	2
Large Language Models Struggle to Learn Long-Tail Knowledge	❌	✅	✅	✅	✅	❌	✅	5
Last Switch Dependent Bandits with Monotone Payoff Functions	✅	❌	❌	❌	❌	❌	❌	1
Latent Traversals in Generative Models as Potential Flows	❌	✅	✅	✅	❌	❌	✅	4
Layered State Discovery for Incremental Autonomous Exploration	✅	✅	❌	❌	❌	❌	✅	3
Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation	❌	✅	✅	✅	❌	❌	✅	4
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Learn to Accumulate Evidence from All Training Samples: Theory and Practice	❌	✅	✅	❌	❌	❌	✅	3
Learnability and Algorithm for Continual Learning	❌	✅	✅	✅	❌	❌	✅	4
Learning Affinity with Hyperbolic Representation for Spatial Propagation	✅	❌	✅	✅	✅	❌	✅	5
Learning Antidote Data to Individual Unfairness	✅	✅	✅	✅	❌	❌	✅	5
Learning Belief Representations for Partially Observable Deep RL	✅	✅	❌	❌	❌	❌	✅	3
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction	❌	✅	✅	✅	❌	❌	✅	4
Learning Control by Iterative Inversion	✅	❌	✅	✅	❌	❌	✅	4
Learning Control-Oriented Dynamical Structure from Data	❌	✅	❌	✅	❌	❌	✅	3
Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows	❌	❌	✅	❌	✅	❌	✅	3
Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic	❌	✅	✅	✅	✅	❌	✅	5
Learning Deep Time-index Models for Time Series Forecasting	✅	✅	✅	✅	✅	❌	✅	6
Learning Dense Correspondences between Photos and Sketches	❌	✅	✅	❌	❌	❌	✅	3
Learning Distributions over Quantum Measurement Outcomes	✅	❌	❌	❌	❌	❌	❌	1
Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation	❌	❌	✅	✅	✅	❌	✅	4
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Learning Functional Distributions with Private Labels	✅	❌	❌	❌	❌	❌	❌	1
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability	❌	❌	✅	✅	❌	❌	✅	3
Learning Globally Smooth Functions on Manifolds	✅	✅	✅	❌	✅	❌	✅	5
Learning Hidden Markov Models When the Locations of Missing Observations are Unknown	✅	✅	✅	❌	❌	❌	✅	4
Learning Instance-Specific Augmentations by Capturing Local Invariances	✅	✅	✅	✅	✅	❌	✅	6
Learning Intuitive Policies Using Action Features	❌	❌	❌	❌	✅	❌	✅	2
Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation	✅	✅	✅	✅	✅	❌	✅	6
Learning Mixtures of Gaussians with Censored Data	✅	❌	❌	❌	❌	❌	❌	1
Learning Mixtures of Markov Chains and MDPs	✅	✅	✅	❌	❌	❌	❌	3
Learning Neural Constitutive Laws from Motion Observations for Generalizable PDE Dynamics	✅	❌	❌	❌	✅	❌	✅	3
Learning Neural PDE Solvers with Parameter-Guided Channel Attention	✅	✅	✅	✅	✅	✅	✅	7
Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation	✅	✅	✅	❌	✅	❌	✅	5
Learning Perturbations to Explain Time Series Predictions	❌	✅	✅	❌	❌	❌	✅	3
Learning Physical Models that Can Respect Conservation Laws	✅	✅	❌	❌	❌	❌	✅	3
Learning Preconditioners for Conjugate Gradient PDE Solvers	✅	❌	❌	❌	✅	✅	✅	4
Learning Prescriptive ReLU Networks	❌	❌	❌	✅	❌	❌	✅	2
Learning Rate Schedules in the Presence of Distribution Shift	✅	✅	✅	❌	❌	❌	✅	4
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation	✅	❌	✅	❌	❌	❌	✅	3
Learning Representations without Compositional Assumptions	❌	✅	✅	✅	✅	❌	✅	5
Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping	❌	✅	✅	✅	❌	❌	✅	4
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design	✅	✅	✅	✅	✅	❌	✅	6
Learning Temporally AbstractWorld Models without Online Experimentation	❌	❌	✅	❌	❌	❌	✅	2
Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator	✅	✅	✅	✅	❌	❌	✅	5
Learning Unnormalized Statistical Models via Compositional Optimization	✅	❌	✅	❌	✅	❌	✅	4
Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees	✅	❌	✅	❌	✅	❌	✅	4
Learning in POMDPs is Sample-Efficient with Hindsight Observability	✅	❌	❌	❌	❌	❌	❌	1
Learning the Dynamics of Sparsely Observed Interacting Systems	✅	✅	✅	❌	❌	❌	✅	4
Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs	✅	✅	✅	✅	❌	❌	✅	5
Learning to Bid in Repeated First-Price Auctions with Budgets	✅	❌	❌	❌	❌	❌	✅	2
Learning to Boost Training by Periodic Nowcasting Near Future Weights	✅	✅	✅	✅	✅	❌	✅	6
Learning to Decouple Complex Systems	❌	✅	✅	✅	❌	❌	✅	4
Learning to Design Analog Circuits to Meet Threshold Specifications	❌	✅	✅	✅	❌	❌	✅	4
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model	✅	❌	❌	❌	❌	❌	❌	1
Learning to Initiate and Reason in Event-Driven Cascading Processes	❌	❌	❌	✅	❌	❌	✅	2
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling	✅	✅	✅	❌	❌	❌	✅	4
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning	✅	❌	✅	✅	❌	❌	✅	4
Learning to Maximize Mutual Information for Dynamic Feature Selection	✅	✅	✅	✅	❌	❌	✅	5
Learning to Optimize Differentiable Games	✅	✅	✅	✅	❌	❌	✅	5
Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement	✅	✅	✅	❌	✅	❌	✅	5
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning	❌	✅	✅	❌	❌	❌	✅	3
Learning useful representations for shifting tasks and distributions	❌	✅	✅	✅	❌	❌	✅	4
Learning-Rate-Free Learning by D-Adaptation	✅	✅	✅	✅	✅	❌	✅	6
Learning-augmented private algorithms for multiple quantile release	✅	✅	✅	✅	❌	❌	✅	5
LegendreTron: Uprising Proper Multiclass Loss Learning	✅	❌	✅	❌	✅	❌	✅	4
Less is More: Task-aware Layer-wise Distillation for Language Model Compression	❌	✅	✅	✅	✅	✅	✅	6
Leveraging Demonstrations to Improve Online Learning: Quality Matters	✅	❌	❌	❌	❌	❌	✅	2
Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Leveraging Offline Data in Online Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Leveraging Proxy of Training Data for Test-Time Adaptation	❌	❌	✅	✅	❌	❌	✅	3
Lifelong Language Pretraining with Distribution-Specialized Experts	❌	❌	✅	❌	✅	❌	✅	3
Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data	✅	❌	✅	❌	❌	❌	✅	3
LinSATNet: The Positive Linear Satisfiability Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Linear CNNs Discover the Statistical Structure of the Dataset Using Only the Most Dominant Frequencies	❌	❌	✅	❌	❌	❌	✅	2
Linear Causal Disentanglement via Interventions	✅	✅	✅	❌	❌	❌	✅	4
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains	✅	❌	✅	❌	❌	❌	✅	3
Linear optimal partial transport embedding	❌	✅	✅	❌	✅	❌	✅	4
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach	✅	✅	✅	❌	❌	❌	✅	4
Linkless Link Prediction via Relational Distillation	❌	✅	✅	✅	✅	❌	✅	5
LipsNet: A Smooth and Robust Neural Network with Adaptive Lipschitz Constant for High Accuracy Optimal Control	✅	✅	✅	❌	✅	❌	✅	5
Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy	✅	❌	✅	❌	✅	✅	✅	5
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation	✅	✅	✅	✅	✅	❌	✅	6
Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Local Vertex Colouring Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Locally Regularized Neural Differential Equations: Some Black Boxes were meant to remain closed!	✅	✅	✅	✅	❌	❌	✅	5
Long Horizon Temperature Scaling	✅	✅	✅	❌	❌	❌	✅	4
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels	❌	✅	✅	❌	❌	❌	✅	3
Long-Term Rhythmic Video Soundtracker	❌	✅	✅	✅	✅	✅	✅	6
LongCoder: A Long-Range Pre-trained Language Model for Code Completion	❌	✅	✅	✅	✅	❌	✅	5
Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers	❌	❌	✅	❌	✅	❌	✅	3
LookupFFN: Making Transformers Compute-lite for CPU inference	❌	✅	✅	✅	✅	❌	✅	5
Looped Transformers as Programmable Computers	✅	✅	❌	❌	❌	❌	❌	2
Loss Balancing for Fair Supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation	❌	❌	✅	✅	✅	❌	✅	4
Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability	✅	✅	✅	❌	✅	❌	✅	5
Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set	✅	✅	❌	❌	❌	❌	✅	3
Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling	✅	❌	✅	❌	❌	❌	✅	3
Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single	✅	✅	✅	❌	❌	❌	✅	4
Lower Bounds for Learning in Revealing POMDPs	❌	❌	❌	❌	❌	❌	❌	0
Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit	❌	✅	✅	✅	❌	❌	✅	4
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior	❌	✅	✅	✅	❌	❌	✅	4
MAGANet: Achieving Combinatorial Generalization by Modeling a Group Action	✅	❌	✅	✅	❌	❌	✅	4
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations	✅	✅	✅	❌	❌	❌	✅	4
MANSA: Learning Fast and Slow in Multi-Agent Systems	❌	❌	✅	❌	❌	❌	✅	2
MEWL: Few-shot multimodal word learning with referential uncertainty	❌	✅	✅	✅	✅	❌	✅	5
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods	❌	✅	❌	❌	✅	❌	✅	3
MODeL: Memory Optimizations for Deep Learning	✅	✅	✅	❌	✅	✅	✅	6
Machine Learning Force Fields with Data Cost Aware Training	❌	✅	✅	✅	❌	❌	✅	4
Magneto: A Foundation Transformer	✅	❌	✅	✅	❌	❌	✅	4
Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models	❌	❌	✅	✅	✅	❌	✅	4
Margin-based Neural Network Watermarking	✅	✅	✅	✅	❌	❌	✅	5
Margin-based sampling in high dimensions: When being active is less efficient than staying passive	✅	❌	✅	❌	❌	❌	✅	3
Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations	❌	❌	✅	❌	❌	❌	✅	2
Markovian Gaussian Process Variational Autoencoders	✅	❌	✅	✅	✅	❌	✅	5
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference	✅	✅	✅	✅	❌	❌	✅	5
Masked Trajectory Models for Prediction, Representation, and Control	❌	✅	✅	✅	❌	❌	✅	4
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning	❌	❌	✅	✅	❌	❌	✅	3
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels	✅	✅	✅	❌	❌	❌	✅	4
Matrix Estimation for Individual Fairness	❌	❌	✅	✅	❌	❌	✅	3
Maximal Initial Learning Rates in Deep ReLU Networks	✅	❌	✅	✅	❌	❌	✅	4
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming	✅	✅	✅	✅	❌	❌	✅	5
Measuring the Impact of Programming Language Distribution	❌	✅	✅	❌	❌	❌	✅	3
Mechanistic Mode Connectivity	❌	✅	✅	✅	❌	❌	✅	4
Memory-Based Dual Gaussian Processes for Sequential Learning	✅	✅	✅	✅	❌	❌	✅	5
Memory-Based Meta-Learning on Non-Stationary Distributions	✅	✅	❌	❌	❌	❌	✅	3
Men Also Do Laundry: Multi-Attribute Bias Amplification	❌	✅	✅	✅	✅	❌	✅	5
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks	✅	❌	❌	❌	❌	❌	✅	2
Meta Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Meta-Learning the Inductive Bias of Simple Neural Circuits	✅	✅	✅	❌	❌	❌	❌	3
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization	✅	✅	✅	❌	✅	❌	✅	5
Meta-learning Parameterized Skills	✅	✅	✅	❌	❌	✅	✅	5
MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL	✅	❌	✅	❌	❌	❌	✅	3
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks	❌	✅	✅	❌	❌	❌	✅	3
Metagenomic Binning using Connectivity-constrained Variational Autoencoders	✅	✅	✅	❌	❌	❌	✅	4
MetricGAN-OKD: Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement	✅	❌	✅	✅	✅	✅	✅	6
Mimetic Initialization of Self-Attention Layers	❌	❌	✅	❌	❌	❌	✅	2
Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints	✅	❌	❌	❌	❌	❌	❌	1
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case	❌	❌	❌	❌	❌	❌	✅	1
Minimizing Trajectory Curvature of ODE-based Generative Models	❌	✅	✅	❌	❌	❌	✅	3
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation	❌	❌	❌	❌	❌	❌	❌	0
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes	✅	❌	✅	❌	❌	❌	✅	3
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction	❌	❌	✅	✅	✅	❌	✅	4
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling	✅	✅	✅	❌	✅	❌	✅	5
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning	❌	✅	✅	✅	❌	❌	✅	4
MixFlows: principled variational inference via mixed flows	✅	✅	✅	❌	✅	❌	✅	5
Mixing Predictions for Online Metric Algorithms	✅	❌	❌	❌	❌	❌	❌	1
Mixture Proportion Estimation Beyond Irreducibility	✅	✅	✅	❌	❌	❌	✅	4
Moccasin: Efficient Tensor Rematerialization for Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
Modality-Agnostic Variational Compression of Implicit Neural Representations	✅	❌	✅	✅	❌	❌	✅	4
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization	❌	✅	✅	✅	❌	❌	✅	4
Model Transferability with Responsive Decision Subjects	✅	✅	✅	❌	❌	❌	❌	3
Model-Aware Contrastive Learning: Towards Escaping the Dilemmas	✅	❌	✅	✅	✅	✅	✅	6
Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
Model-Free Robust Average-Reward Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Model-agnostic Measure of Generalization Difficulty	❌	✅	✅	✅	❌	❌	✅	4
Model-based Offline Reinforcement Learning with Count-based Conservatism	✅	✅	✅	❌	❌	❌	✅	4
Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators	❌	❌	✅	❌	✅	❌	✅	3
ModelDiff: A Framework for Comparing Learning Algorithms	❌	✅	✅	✅	✅	❌	✅	5
Modeling Dynamic Environments with Scene Graph Memory	✅	✅	✅	❌	❌	✅	✅	5
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion	✅	✅	✅	❌	❌	❌	❌	3
Moderately Distributional Exploration for Domain Generalization	✅	✅	✅	✅	❌	❌	✅	5
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation	❌	✅	✅	✅	❌	❌	✅	4
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions	✅	❌	✅	❌	❌	❌	✅	3
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps	❌	✅	✅	❌	❌	❌	✅	3
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows	❌	✅	✅	❌	❌	❌	✅	3
MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Poses	❌	❌	✅	❌	❌	❌	✅	2
Monotonic Location Attention for Length Generalization	❌	✅	✅	✅	❌	❌	✅	4
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes	❌	❌	✅	❌	❌	❌	✅	2
Motion Question Answering via Modular Motion Programs	✅	✅	✅	✅	❌	❌	✅	5
Mu$^2$SLAM: Multitask, Multilingual Speech and Language Models	❌	❌	✅	❌	✅	❌	✅	3
Multi-Agent Best Arm Identification with Private Communications	✅	❌	✅	❌	❌	❌	✅	3
Multi-Agent Learning from Learners	✅	✅	❌	❌	✅	❌	✅	4
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets	✅	✅	✅	❌	❌	❌	✅	4
Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning	✅	✅	✅	✅	❌	❌	✅	5
Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry	✅	✅	❌	❌	❌	❌	✅	3
Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces	❌	❌	❌	❌	❌	❌	✅	1
Multi-Modal Classifiers for Open-Vocabulary Object Detection	❌	❌	✅	✅	✅	❌	✅	4
Multi-Objective GFlowNets	✅	✅	✅	❌	❌	❌	✅	4
Multi-Objective Population Based Training	✅	✅	✅	✅	✅	❌	✅	6
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries	❌	✅	✅	✅	❌	❌	✅	4
Multi-Task Differential Privacy Under Distribution Skew	✅	✅	✅	❌	❌	❌	✅	4
Multi-Task Off-Policy Learning from Bandit Feedback	✅	❌	✅	❌	❌	❌	✅	3
Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal	✅	✅	✅	✅	✅	❌	✅	6
Multi-User Reinforcement Learning with Low Rank Rewards	✅	❌	❌	❌	❌	❌	❌	1
Multi-View Masked World Models for Visual Robotic Manipulation	✅	❌	✅	❌	✅	❌	✅	4
Multi-agent Online Scheduling: MMS Allocations for Indivisible Items	✅	❌	❌	❌	❌	❌	❌	1
Multi-channel Autobidding with Budget and ROI Constraints	✅	❌	❌	❌	❌	❌	❌	1
Multi-class Graph Clustering via Approximated Effective $p$-Resistance	✅	✅	✅	❌	✅	❌	✅	5
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Multi-task Representation Learning for Pure Exploration in Linear Bandits	✅	❌	❌	❌	❌	❌	✅	2
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks	✅	✅	❌	❌	❌	✅	✅	4
MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation	✅	❌	✅	❌	❌	❌	✅	3
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks	❌	❌	✅	❌	❌	❌	✅	2
Multicalibration as Boosting for Regression	✅	✅	✅	❌	❌	❌	✅	4
Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation	❌	❌	✅	✅	✅	❌	✅	4
Multiplier Bootstrap-based Exploration	✅	❌	✅	❌	❌	❌	✅	3
Multiply Robust Off-policy Evaluation and Learning under Truncation by Death	✅	❌	✅	❌	❌	❌	❌	2
Multisample Flow Matching: Straightening Flows with Minibatch Couplings	✅	❌	✅	❌	❌	❌	✅	3
Muse: Text-To-Image Generation via Masked Generative Transformers	❌	❌	✅	❌	✅	❌	✅	3
MyoDex: A Generalizable Prior for Dexterous Manipulation	❌	❌	✅	❌	❌	❌	✅	2
N$\text{A}^{\text{2}}$Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning	✅	✅	✅	❌	✅	❌	✅	5
NNSplitter: An Active Defense Solution for DNN Model via Automated Weight Obfuscation	✅	✅	✅	✅	❌	❌	✅	5
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning	❌	✅	✅	✅	✅	❌	✅	5
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data	✅	✅	✅	❌	✅	❌	✅	5
Naive imputation implicitly regularizes high-dimensional linear models	❌	❌	❌	❌	❌	❌	✅	1
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations	❌	✅	✅	❌	❌	❌	✅	3
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal $Φ$-Regret Learning in Extensive-Form Games	✅	❌	✅	❌	❌	❌	✅	3
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals	❌	❌	❌	❌	❌	❌	❌	0
Near-Optimal Quantum Coreset Construction Algorithms for Clustering	✅	❌	❌	❌	❌	❌	❌	1
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints	✅	❌	❌	❌	❌	❌	✅	2
Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path	✅	❌	❌	❌	❌	❌	✅	2
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression	✅	✅	✅	❌	✅	❌	✅	5
Nearly Optimal Competitive Ratio for Online Allocation Problems with Two-sided Resource Constraints and Finite Requests	✅	❌	❌	❌	❌	❌	❌	1
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA	✅	❌	❌	❌	❌	❌	❌	1
Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs	✅	✅	✅	❌	✅	✅	✅	6
Nearly-tight Bounds for Deep Kernel Learning	❌	❌	❌	❌	❌	❌	❌	0
NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion	✅	❌	✅	✅	✅	❌	✅	5
Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback	✅	❌	✅	❌	✅	✅	✅	5
Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization	✅	❌	❌	❌	❌	❌	✅	2
Network Effects in Performative Prediction Games	✅	❌	✅	❌	❌	❌	✅	3
Neural Algorithmic Reasoning with Causal Regularisation	❌	❌	✅	❌	❌	❌	✅	2
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data	❌	❌	✅	❌	❌	❌	✅	2
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series	✅	✅	✅	✅	✅	❌	✅	6
Neural Diffusion Processes	✅	✅	✅	❌	✅	❌	✅	5
Neural FIM for learning Fisher information metrics from point cloud data	✅	✅	✅	❌	❌	❌	✅	4
Neural Inverse Operators for Solving PDE Inverse Problems	❌	✅	✅	✅	✅	❌	✅	5
Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data	❌	❌	✅	✅	✅	❌	✅	4
Neural Markov Jump Processes	✅	✅	❌	✅	✅	❌	✅	5
Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods	✅	✅	✅	❌	✅	❌	✅	5
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective	❌	❌	❌	❌	❌	❌	❌	0
Neural Prediction Errors enable Analogical Visual Reasoning in Human Standard Intelligence Tests	❌	✅	✅	✅	❌	❌	✅	4
Neural Status Registers	❌	✅	✅	❌	❌	❌	✅	3
Neural Stochastic Differential Games for Time-series Analysis	✅	✅	✅	❌	❌	❌	✅	4
Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels	✅	✅	✅	❌	❌	❌	✅	4
Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Neural networks trained with SGD learn distributions of increasing complexity	❌	✅	✅	❌	❌	❌	✅	3
Neural signature kernels as infinite-width-depth-limits of controlled ResNets	✅	✅	❌	❌	❌	❌	✅	3
NeuralSlice: Neural 3D Triangle Mesh Reconstruction via Slicing 4D Tetrahedral Meshes	✅	✅	✅	✅	✅	❌	✅	6
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition	❌	❌	❌	❌	✅	❌	✅	2
Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal	❌	✅	✅	✅	✅	❌	✅	5
Never mind the metrics---what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective	❌	✅	✅	❌	❌	❌	✅	3
New metrics and search algorithms for weighted causal DAGs	✅	✅	❌	❌	✅	❌	✅	4
No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation	✅	✅	✅	❌	❌	❌	✅	4
Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Non-autoregressive Conditional Diffusion Models for Time Series Prediction	✅	❌	✅	✅	✅	❌	✅	5
Non-stationary Reinforcement Learning under General Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think	❌	❌	✅	✅	✅	✅	✅	5
Nonlinear Causal Discovery with Latent Confounders	❌	✅	✅	❌	❌	❌	❌	2
Nonparametric Density Estimation under Distribution Drift	❌	❌	❌	❌	❌	❌	❌	0
Nonparametric Extensions of Randomized Response for Private Confidence Sets	✅	✅	❌	❌	❌	❌	❌	2
Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows	✅	✅	✅	❌	❌	❌	✅	4
Nonparametric Iterative Machine Teaching	✅	✅	✅	❌	✅	❌	✅	5
Normalizing Flows for Interventional Density Estimation	✅	✅	✅	✅	✅	❌	✅	6
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization	✅	✅	✅	✅	✅	❌	✅	6
Not all Strongly Rayleigh Distributions Have Small Probabilistic Generating Circuits	❌	❌	❌	❌	❌	❌	❌	0
Nugget: Neural Agglomerative Embeddings of Text	❌	❌	✅	❌	✅	❌	✅	3
OCD: Learning to Overfit with Conditional Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift	✅	❌	✅	✅	✅	❌	✅	5
OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models	✅	✅	✅	❌	✅	❌	✅	5
Off-Policy Average Reward Actor-Critic with Deterministic Policy Search	✅	✅	✅	❌	❌	❌	✅	4
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling	❌	✅	✅	❌	❌	❌	✅	3
Offline Learning in Markov Games with General Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators	✅	✅	✅	✅	❌	✅	✅	6
Omnipredictors for Constrained Optimization	❌	❌	❌	❌	❌	❌	❌	0
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation	✅	❌	✅	❌	✅	❌	✅	4
On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization	❌	✅	✅	❌	❌	❌	✅	3
On Computing Optimal Tree Ensembles	✅	❌	❌	❌	❌	❌	❌	1
On Coresets for Clustering in Small Dimensional Euclidean spaces	✅	❌	❌	❌	❌	❌	❌	1
On Data Manifolds Entailed by Structural Causal Models	❌	✅	✅	❌	❌	❌	❌	2
On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing	✅	❌	✅	❌	❌	❌	✅	3
On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network	❌	❌	✅	❌	❌	❌	✅	2
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances	✅	❌	❌	❌	❌	❌	✅	2
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs	✅	✅	✅	❌	✅	❌	✅	5
On Investigating the Conservative Property of Score-Based Generative Models	✅	✅	✅	❌	✅	❌	✅	5
On Kinetic Optimal Probability Paths for Generative Models	❌	❌	✅	❌	✅	❌	✅	3
On Many-Actions Policy Gradient	✅	✅	✅	❌	❌	❌	✅	4
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology	❌	❌	✅	✅	❌	❌	✅	3
On Penalty-based Bilevel Gradient Descent Method	✅	✅	✅	✅	❌	❌	✅	5
On Pitfalls of Test-Time Adaptation	✅	✅	✅	✅	❌	❌	✅	5
On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline	❌	✅	✅	❌	❌	❌	✅	3
On Preemption and Learning in Stochastic Scheduling	✅	✅	❌	❌	✅	❌	✅	4
On Provable Copyright Protection for Generative Models	✅	❌	✅	✅	❌	❌	✅	4
On Regularization and Inference with Label Constraints	❌	❌	❌	❌	❌	❌	❌	0
On Sampling with Approximate Transport Maps	❌	✅	✅	❌	✅	❌	✅	4
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification	❌	❌	❌	❌	❌	❌	❌	0
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation	✅	✅	✅	✅	✅	❌	✅	6
On Uni-Modal Feature Learning in Supervised Multi-Modal Learning	✅	✅	✅	✅	❌	❌	✅	5
On User-Level Private Convex Optimization	✅	❌	❌	❌	❌	❌	❌	1
On the Complexity of Bayesian Generalization	❌	✅	✅	✅	✅	❌	✅	5
On the Connection Between MPNN and Graph Transformer	❌	✅	✅	✅	❌	❌	✅	4
On the Convergence Rate of Gaussianization with Random Rotations	❌	✅	✅	❌	❌	❌	✅	3
On the Convergence of Federated Averaging with Cyclic Client Participation	✅	✅	✅	✅	✅	✅	✅	7
On the Convergence of Gradient Flow on Multi-layer Linear Models	❌	❌	❌	❌	❌	❌	✅	1
On the Convergence of SARSA with Linear Function Approximation	✅	❌	✅	❌	❌	❌	✅	3
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters	❌	❌	❌	❌	❌	❌	❌	0
On the Effectiveness of Offline RL for Dialogue Response Generation	❌	✅	✅	❌	✅	❌	✅	4
On the Estimation of Gaussian Mixture Copula Models	❌	✅	✅	✅	❌	❌	✅	4
On the Expressive Power of Geometric Graph Neural Networks	❌	✅	❌	❌	❌	❌	✅	2
On the Forward Invariance of Neural ODEs	✅	✅	✅	❌	✅	❌	✅	5
On the Functional Similarity of Robust and Non-Robust Neural Representations	❌	✅	✅	❌	✅	❌	✅	4
On the Generalization of Multi-modal Contrastive Learning	❌	✅	✅	✅	❌	❌	✅	4
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization	✅	❌	❌	❌	❌	❌	❌	1
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures	✅	❌	✅	❌	❌	❌	✅	3
On the Identifiability and Estimation of Causal Location-Scale Noise Models	❌	✅	✅	❌	❌	❌	✅	3
On the Impact of Algorithmic Recourse on Social Segregation	✅	✅	✅	❌	❌	❌	✅	4
On the Impact of Knowledge Distillation for Model Interpretability	✅	✅	✅	✅	✅	✅	✅	7
On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
On the Initialization of Graph Neural Networks	❌	❌	✅	✅	✅	❌	✅	4
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits	✅	❌	✅	❌	✅	❌	✅	4
On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs	❌	❌	❌	❌	❌	❌	❌	0
On the Optimality of Misspecified Kernel Ridge Regression	❌	❌	❌	✅	❌	❌	✅	2
On the Power of Foundation Models	❌	❌	❌	❌	❌	❌	❌	0
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness	✅	❌	❌	❌	❌	❌	❌	1
On the Privacy-Robustness-Utility Trilemma in Distributed Learning	✅	❌	✅	❌	❌	❌	✅	3
On the Relationship Between Explanation and Prediction: A Causal View	❌	❌	✅	❌	❌	❌	✅	2
On the Robustness of Randomized Ensembles to Adversarial Perturbations	✅	✅	✅	❌	❌	❌	✅	4
On the Robustness of Text Vectorizers	❌	✅	✅	❌	❌	❌	✅	3
On the Role of Attention in Prompt-tuning	✅	❌	✅	❌	❌	❌	✅	3
On the Statistical Benefits of Temporal Difference Learning	❌	❌	❌	❌	❌	❌	✅	1
On the Stepwise Nature of Self-Supervised Learning	❌	✅	✅	❌	❌	❌	✅	3
On the Training Instability of Shuffling SGD with Batch Normalization	❌	✅	✅	❌	❌	✅	✅	4
On the Within-Group Fairness of Screening Classifiers	✅	✅	✅	✅	✅	❌	✅	6
On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm	✅	✅	❌	❌	❌	❌	✅	3
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale	✅	✅	✅	❌	✅	❌	✅	5
One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding	✅	✅	✅	❌	❌	❌	❌	3
One-Shot Federated Conformal Prediction	✅	✅	✅	✅	❌	❌	✅	5
One-Step Estimator for Permuted Sparse Recovery	✅	❌	✅	❌	❌	❌	✅	3
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill	✅	❌	✅	✅	❌	❌	✅	4
One-sided Matrix Completion from Two Observations Per Row	❌	❌	✅	❌	✅	❌	✅	3
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training	✅	❌	✅	✅	✅	❌	✅	5
Online Learning in Stackelberg Games with an Omniscient Follower	✅	❌	❌	❌	❌	❌	❌	1
Online Learning with Feedback Graphs: The True Shape of Regret	✅	❌	❌	❌	❌	❌	❌	1
Online Local Differential Private Quantile Inference via Self-normalization	✅	❌	✅	❌	❌	❌	✅	3
Online Mechanism Design for Information Acquisition	✅	❌	❌	❌	❌	❌	❌	1
Online Nonstochastic Control with Adversarial and Static Constraints	✅	❌	❌	❌	❌	❌	✅	2
Online Platt Scaling with Calibeating	✅	✅	✅	❌	✅	❌	✅	5
Online Prototype Alignment for Few-shot Policy Transfer	✅	✅	✅	❌	❌	❌	✅	4
Online Restless Bandits with Unobserved States	✅	❌	❌	❌	❌	❌	✅	2
Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization	✅	✅	✅	✅	❌	❌	✅	5
Open-Vocabulary Universal Image Segmentation with MaskCLIP	✅	✅	✅	✅	✅	❌	✅	6
OpenFE: Automated Feature Generation with Expert-level Performance	✅	✅	✅	✅	✅	❌	✅	6
Opponent-Limited Online Search for Imperfect Information Games	❌	❌	✅	❌	✅	❌	✅	3
Optimal Arms Identification with Knapsacks	✅	✅	❌	❌	❌	❌	✅	3
Optimal Convergence Rates for Agnostic Nyström Kernel Learning	❌	❌	❌	❌	❌	❌	❌	0
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning	❌	✅	✅	❌	❌	❌	✅	3
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs	✅	❌	❌	❌	❌	❌	❌	1
Optimal LP Rounding and Linear-Time Approximation Algorithms for Clustering Edge-Colored Hypergraphs	✅	✅	✅	❌	✅	❌	❌	4
Optimal No-Regret Learning for One-Sided Lipschitz Functions	✅	❌	❌	❌	❌	❌	❌	1
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits	✅	❌	❌	❌	❌	❌	✅	2
Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion	✅	❌	❌	❌	❌	❌	❌	1
Optimal Sets and Solution Paths of ReLU Networks	✅	✅	✅	✅	❌	✅	✅	6
Optimal Shrinkage for Distributed Second-Order Optimization	✅	✅	✅	❌	✅	❌	✅	5
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion	✅	❌	❌	❌	❌	❌	❌	1
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations	✅	✅	❌	❌	❌	❌	✅	3
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits	✅	❌	❌	❌	❌	❌	✅	2
Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference	✅	✅	✅	❌	❌	✅	✅	5
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization	✅	❌	❌	❌	❌	❌	❌	1
Optimistic Planning by Regularized Dynamic Programming	✅	❌	❌	❌	❌	❌	❌	1
Optimization for Amortized Inverse Problems	✅	❌	✅	❌	❌	❌	✅	3
Optimizing DDPM Sampling with Shortcut Fine-Tuning	✅	✅	✅	❌	✅	❌	✅	5
Optimizing Hyperparameters with Conformal Quantile Regression	✅	✅	✅	✅	✅	❌	✅	6
Optimizing Mode Connectivity for Class Incremental Learning	✅	✅	✅	✅	❌	✅	✅	6
Optimizing NOTEARS Objectives via Topological Swaps	✅	✅	❌	❌	❌	❌	✅	3
Optimizing the Collaboration Structure in Cross-Silo Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning	✅	❌	✅	❌	✅	✅	✅	5
Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations	✅	✅	✅	❌	✅	❌	✅	5
Oscillation-free Quantization for Low-bit Vision Transformers	✅	✅	✅	✅	❌	❌	✅	5
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships	✅	✅	✅	✅	❌	❌	✅	5
Out-of-Domain Robustness via Targeted Augmentations	✅	✅	✅	✅	❌	❌	✅	5
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation	✅	✅	✅	❌	❌	❌	✅	4
Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points	❌	✅	❌	❌	❌	❌	✅	2
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve	✅	✅	✅	✅	❌	❌	✅	5
PAC Generalization via Invariant Representations	❌	✅	❌	❌	❌	❌	✅	2
PAC Prediction Sets for Large Language Models of Code	✅	✅	✅	❌	❌	❌	✅	4
PAC-Bayesian Generalization Bounds for Adversarial Generative Models	❌	❌	✅	❌	❌	❌	✅	2
PAC-Bayesian Offline Contextual Bandits With Guarantees	❌	❌	✅	✅	❌	❌	✅	3
PAL: Program-aided Language Models	✅	✅	✅	❌	❌	❌	✅	4
PASTA: Pessimistic Assortment Optimization	✅	❌	❌	❌	❌	❌	✅	2
PCA-based Multi-Task Learning: a Random Matrix Approach	✅	✅	✅	✅	❌	❌	✅	5
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models	✅	✅	✅	❌	✅	❌	✅	5
PFNs4BO: In-Context Learning for Bayesian Optimization	✅	✅	✅	✅	✅	❌	✅	6
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation	✅	✅	✅	❌	✅	❌	✅	5
PLay: Parametrically Conditioned Layout Generation using Latent Diffusion	❌	❌	✅	❌	✅	❌	✅	3
POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models	✅	✅	✅	✅	✅	❌	✅	6
PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient	✅	❌	✅	❌	✅	❌	✅	4
PWSHAP: A Path-Wise Explanation Model for Targeted Variables	❌	✅	✅	✅	✅	❌	❌	4
PaLM-E: An Embodied Multimodal Language Model	❌	❌	✅	✅	❌	❌	❌	2
Paging with Succinct Predictions	✅	❌	❌	❌	❌	❌	❌	1
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions	❌	❌	✅	✅	❌	❌	✅	3
Parallel $Q$-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation	✅	✅	✅	❌	✅	❌	✅	5
Parallel Neurosymbolic Integration with Concordia	✅	✅	✅	✅	✅	✅	✅	7
Parallel Online Clustering of Bandits via Hedonic Game	✅	❌	✅	❌	❌	❌	✅	3
Parameter-Level Soft-Masking for Continual Learning	✅	✅	✅	✅	❌	❌	✅	5
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models	✅	✅	✅	✅	❌	❌	✅	5
Pareto Regret Analyses in Multi-objective Multi-armed Bandit	✅	❌	❌	❌	❌	❌	❌	1
Partial Optimality in Cubic Correlation Clustering	✅	❌	❌	❌	✅	✅	✅	4
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing	✅	❌	✅	❌	❌	❌	✅	3
Patch-level Contrastive Learning via Positional Query for Visual Pre-training	❌	✅	✅	❌	✅	❌	✅	4
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Path Neural Networks: Expressive and Accurate Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Performative Recommendation: Diversifying Content via Strategic Incentives	❌	✅	✅	✅	✅	❌	✅	5
Performative Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Personalized Federated Learning under Mixture of Distributions	✅	✅	✅	✅	✅	✅	✅	7
Personalized Federated Learning with Inferred Collaboration Graphs	✅	✅	✅	✅	❌	❌	✅	5
Personalized Subgraph Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
Perturbation Analysis of Neural Collapse	❌	❌	✅	❌	❌	❌	✅	2
Phase Transitions in the Detection of Correlated Databases	❌	❌	❌	❌	❌	❌	❌	0
Phase-aware Adversarial Defense for Improving Adversarial Robustness	✅	✅	✅	❌	❌	❌	✅	4
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding	❌	✅	✅	✅	✅	❌	✅	5
PixelAsParam: A Gradient View on Diffusion Sampling with Guidance	✅	✅	✅	❌	✅	❌	✅	5
Poisoning Generative Replay in Continual Learning to Promote Forgetting	✅	✅	✅	❌	❌	❌	✅	4
Poisoning Language Models During Instruction Tuning	❌	✅	✅	❌	✅	❌	✅	4
Polarity Is All You Need to Learn and Transfer Faster	✅	✅	✅	✅	✅	❌	✅	6
Policy Contrastive Imitation Learning	❌	❌	✅	❌	❌	❌	✅	2
Policy Gradient in Robust MDPs with Global Convergence Guarantee	✅	✅	✅	❌	✅	✅	✅	6
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games	✅	❌	❌	❌	❌	❌	❌	1
Policy Regularization with Dataset Constraint for Offline Reinforcement Learning	✅	✅	✅	❌	✅	✅	✅	6
Polyhedral Complex Extraction from ReLU Networks using Edge Subdivision	❌	✅	❌	❌	✅	❌	✅	3
Polynomial Preconditioning for Gradient Methods	✅	❌	✅	❌	✅	❌	❌	3
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models	✅	❌	❌	❌	❌	❌	❌	1
Posterior Sampling for Deep Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference	❌	❌	✅	❌	❌	❌	✅	2
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute	❌	❌	✅	❌	❌	❌	✅	2
Pre-training for Speech Translation: CTC Meets Optimal Transport	❌	✅	✅	✅	✅	❌	✅	5
PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search	✅	✅	✅	❌	✅	❌	✅	5
Predictable MDP Abstraction for Unsupervised Model-Based RL	✅	✅	✅	❌	✅	❌	✅	5
Predicting Ordinary Differential Equations with Transformers	❌	✅	✅	❌	✅	❌	✅	4
Predicting Rare Events by Shrinking Towards Proportional Odds	❌	✅	✅	✅	✅	✅	✅	6
Predictive Flows for Faster Ford-Fulkerson	✅	✅	✅	❌	✅	❌	✅	5
Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning	✅	✅	✅	✅	❌	❌	✅	5
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems	✅	✅	✅	❌	✅	❌	✅	5
Pretraining Language Models with Human Preferences	❌	✅	✅	✅	❌	❌	✅	4
Pricing Experimental Design: Causal Effect, Expected Revenue and Tail Risk	✅	❌	❌	❌	❌	❌	❌	1
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems	✅	❌	❌	❌	❌	❌	✅	2
Principled Acceleration of Iterative Numerical Methods Using Machine Learning	✅	❌	❌	✅	❌	❌	✅	3
Principled Offline RL in the Presence of Rich Exogenous Information	❌	❌	✅	❌	❌	❌	✅	2
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons	✅	❌	❌	❌	❌	❌	❌	1
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design	❌	❌	✅	✅	❌	❌	✅	3
Private Federated Learning with Autotuned Compression	✅	❌	✅	✅	❌	❌	✅	4
Private Statistical Estimation of Many Quantiles	❌	❌	❌	❌	❌	❌	✅	1
Probabilistic Attention-to-Influence Neural Models for Event Sequences	✅	❌	✅	✅	✅	❌	✅	5
Probabilistic Categorical Adversarial Attack and Adversarial Training	✅	✅	✅	❌	❌	❌	✅	4
Probabilistic Concept Bottleneck Models	✅	✅	✅	✅	❌	❌	✅	5
Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs	❌	✅	✅	✅	✅	✅	✅	6
Probabilistic Imputation for Time-series Classification with Missing Data	❌	❌	✅	❌	❌	❌	✅	2
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models	✅	✅	✅	✅	✅	❌	✅	6
Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits	✅	✅	❌	❌	❌	❌	❌	2
Progressive Purification for Instance-Dependent Partial Label Learning	✅	✅	✅	✅	❌	❌	✅	5
Projected Tensor Power Method for Hypergraph Community Recovery	✅	❌	✅	❌	❌	✅	✅	4
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning	✅	❌	✅	✅	❌	❌	✅	4
PromptBoosting: Black-Box Text Classification with Ten Forward Passes	✅	✅	✅	✅	❌	❌	✅	5
Prompting Large Language Model for Machine Translation: A Case Study	❌	❌	✅	✅	✅	✅	✅	5
Propensity Matters: Measuring and Enhancing Balancing for Recommendation	❌	❌	✅	❌	❌	❌	✅	2
Proper Losses for Discrete Generative Models	❌	❌	❌	❌	❌	❌	✅	1
Proper Scoring Rules for Survival Analysis	❌	✅	✅	✅	✅	✅	✅	6
Properties of the Mallows Model Depending on the Number of Alternatives: A Warning for an Experimentalist	❌	✅	✅	❌	❌	❌	✅	3
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts	❌	✅	✅	✅	✅	❌	✅	5
Protecting Language Generation Models via Invisible Watermarking	✅	✅	✅	✅	✅	❌	✅	6
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning	❌	✅	✅	✅	❌	❌	✅	4
Prototype-oriented unsupervised anomaly detection for multivariate time series	✅	✅	✅	❌	✅	❌	✅	5
Provable Benefit of Mixup for Finding Optimal Decision Boundaries	❌	❌	✅	❌	❌	❌	✅	2
Provable Data Subset Selection For Efficient Neural Networks Training	✅	✅	✅	❌	✅	❌	✅	5
Provable Dynamic Fusion for Low-Quality Multimodal Data	✅	✅	✅	✅	❌	❌	✅	5
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling	✅	✅	✅	✅	❌	❌	✅	5
Provable Reset-free Reinforcement Learning by No-Regret Reduction	✅	❌	❌	❌	❌	❌	❌	1
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation	✅	✅	✅	❌	❌	❌	✅	4
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources	✅	❌	❌	❌	❌	❌	✅	2
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP	✅	✅	✅	❌	❌	❌	✅	4
Provably Invariant Learning without Domain Information	✅	✅	✅	❌	✅	❌	✅	5
Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup	❌	✅	✅	❌	✅	❌	✅	4
Provably Learning Object-Centric Representations	❌	✅	✅	✅	❌	❌	✅	4
Provably and Practically Efficient Neural Contextual Bandits	✅	❌	✅	❌	✅	❌	✅	4
Proximal Causal Learning of Conditional Average Treatment Effects	✅	❌	✅	✅	❌	❌	✅	4
Pruning via Sparsity-indexed ODE: a Continuous Sparsity Viewpoint	✅	✅	✅	❌	❌	❌	✅	4
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling	❌	✅	✅	✅	✅	❌	✅	5
Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows	✅	❌	❌	❌	❌	❌	✅	2
Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL	✅	❌	✅	❌	❌	❌	✅	3
QAS-Bench: Rethinking Quantum Architecture Search and A Benchmark	✅	✅	✅	❌	✅	❌	✅	5
QASA: Advanced Question Answering on Scientific Articles	❌	❌	✅	❌	✅	❌	✅	3
Quantifying Human Priors over Social and Navigation Networks	✅	❌	❌	❌	❌	❌	✅	2
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs	✅	✅	✅	✅	✅	✅	✅	7
Quantifying the Variability Collapse of Neural Networks	❌	❌	✅	❌	✅	❌	✅	3
Quantile Credit Assignment	✅	❌	❌	❌	❌	❌	✅	2
Quantitative Universal Approximation Bounds for Deep Belief Networks	❌	❌	❌	❌	❌	❌	❌	0
Quantized Distributed Training of Large Models with Convergence Guarantees	✅	❌	✅	❌	✅	✅	✅	5
Quantum 3D Graph Learning with Applications to Molecule Embedding	❌	❌	✅	✅	✅	❌	✅	4
Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions	❌	❌	❌	❌	❌	❌	❌	0
Quantum Policy Gradient Algorithm with Optimized Action Decoding	❌	✅	✅	❌	✅	❌	✅	4
Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation	✅	❌	❌	❌	❌	✅	✅	3
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling	✅	❌	❌	❌	❌	❌	❌	1
QuantumDARTS: Differentiable Quantum Architecture Search for Variational Quantum Algorithms	✅	❌	✅	❌	✅	✅	✅	5
R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents	✅	✅	❌	❌	✅	❌	✅	4
RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution	✅	✅	✅	❌	✅	❌	✅	5
RGE: A Repulsive Graph Rectification for Node Classification via Influence	✅	✅	✅	✅	❌	❌	✅	5
RLEG: Vision-Language Representation Learning with Diffusion-based Embedding Generation	❌	❌	✅	❌	✅	❌	✅	3
RLSbench: Domain Adaptation Under Relaxed Label Shift	✅	✅	✅	✅	✅	❌	✅	6
RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents	✅	✅	✅	❌	❌	❌	✅	4
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations	✅	✅	✅	✅	✅	✅	✅	7
Raising the Cost of Malicious AI-Powered Image Editing	✅	✅	✅	❌	✅	❌	✅	5
Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice	✅	❌	✅	❌	❌	❌	❌	2
Random Grid Neural Processes for Parametric Partial Differential Equations	✅	❌	❌	❌	✅	❌	✅	3
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption	✅	❌	✅	✅	✅	❌	✅	5
Random Shuffle Transformer for Image Restoration	✅	✅	✅	✅	✅	❌	✅	6
Random Teachers are Good Teachers	✅	✅	✅	❌	❌	❌	✅	4
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds	✅	❌	✅	❌	❌	❌	✅	3
Randomized Schur Complement Views for Graph Contrastive Learning	✅	✅	✅	✅	✅	✅	✅	7
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank	✅	❌	✅	✅	❌	❌	✅	4
ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval	✅	✅	✅	✅	✅	❌	✅	6
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs	✅	❌	✅	❌	❌	❌	✅	3
Reachability-Aware Laplacian Representation in Reinforcement Learning	❌	❌	❌	❌	✅	❌	✅	2
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality	❌	❌	✅	✅	❌	❌	✅	3
Recasting Self-Attention with Holographic Reduced Representations	✅	✅	✅	✅	✅	❌	✅	6
Reconstructive Neuron Pruning for Backdoor Defense	✅	✅	✅	✅	❌	❌	✅	5
Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing	✅	✅	✅	✅	✅	❌	✅	6
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework	✅	❌	✅	❌	❌	❌	✅	3
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC	✅	❌	✅	❌	✅	❌	✅	4
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs	❌	✅	✅	✅	❌	❌	✅	4
Refined Regret for Adversarial MDPs with Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Reflected Diffusion Models	❌	✅	✅	✅	❌	❌	✅	4
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts	❌	✅	✅	❌	❌	❌	✅	3
Regression with Label Permutation in Generalized Linear Model	✅	❌	❌	❌	❌	❌	✅	2
Regression with Sensor Data Containing Incomplete Observations	✅	❌	✅	✅	✅	❌	✅	5
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents	✅	❌	❌	❌	❌	❌	✅	2
Regret Minimization and Convergence to Equilibria in General-sum Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Regret-Minimizing Double Oracle for Extensive-Form Games	✅	✅	✅	❌	❌	❌	✅	4
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice	✅	✅	✅	❌	❌	❌	✅	4
Regularization-free Diffeomorphic Temporal Alignment Nets	✅	✅	✅	✅	✅	✅	✅	7
Regularizing Towards Soft Equivariance Under Mixed Symmetries	❌	❌	✅	✅	✅	❌	✅	4
Reinforcement Learning Can Be More Efficient with Multiple Rewards	✅	❌	❌	❌	❌	❌	❌	1
Reinforcement Learning from Passive Data via Latent Intentions	✅	✅	✅	❌	✅	❌	✅	5
Reinforcement Learning in Low-rank MDPs with Density Features	✅	❌	❌	❌	❌	❌	❌	1
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space	✅	✅	✅	❌	❌	❌	❌	3
Reinforcement Learning with History Dependent Dynamic Contexts	✅	❌	✅	❌	❌	❌	✅	3
Relevant Walk Search for Explaining Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Reliable Measures of Spread in High Dimensional Latent Spaces	❌	❌	❌	❌	❌	❌	✅	1
Reparameterized Policy Learning for Multimodal Trajectory Optimization	✅	✅	✅	❌	❌	❌	✅	4
Repository-Level Prompt Generation for Large Language Models of Code	❌	✅	✅	✅	✅	✅	✅	6
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL	✅	✅	✅	❌	❌	❌	✅	4
Representation-Driven Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition	❌	❌	✅	❌	❌	❌	✅	2
Representer Point Selection for Explaining Regularized High-dimensional Models	✅	❌	✅	✅	❌	❌	✅	4
Reprogramming Pretrained Language Models for Antibody Sequence Infilling	❌	✅	✅	✅	✅	❌	✅	5
Restoration based Generative Models	✅	✅	✅	❌	✅	❌	✅	5
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers	❌	❌	❌	❌	❌	❌	❌	0
Resurrecting Recurrent Neural Networks for Long Sequences	✅	✅	✅	✅	✅	❌	✅	6
Rethink DARTS Search Space and Renovate a New Benchmark	❌	✅	✅	✅	✅	✅	✅	6
Rethinking Backdoor Attacks	❌	❌	✅	✅	✅	❌	✅	4
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching	✅	✅	✅	❌	✅	❌	✅	5
Rethinking Visual Reconstruction: Experience-Based Content Completion Guided by Visual Cues	❌	❌	✅	❌	❌	❌	✅	2
Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster $\text{L}$-/$\text{L}^\natural$-Convex Function Minimization	✅	✅	❌	❌	❌	❌	✅	3
Rethinking Weak Supervision in Helping Contrastive Learning	✅	❌	✅	❌	✅	❌	✅	4
Retrieval-Augmented Multimodal Language Modeling	❌	❌	✅	✅	✅	❌	✅	4
Retrosynthetic Planning with Dual Value Networks	❌	❌	✅	❌	✅	❌	✅	3
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge	✅	✅	❌	✅	❌	✅	✅	5
Revisiting Bellman Errors for Offline Model Selection	✅	✅	✅	✅	✅	✅	✅	7
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers	✅	✅	✅	❌	❌	❌	✅	4
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications	❌	✅	✅	✅	✅	❌	✅	5
Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization	✅	✅	✅	❌	❌	❌	✅	4
Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees	❌	❌	✅	❌	❌	❌	✅	2
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature	✅	✅	✅	✅	✅	✅	✅	7
Revisiting Pseudo-Label for Single-Positive Multi-Label Learning	✅	❌	✅	✅	❌	❌	✅	4
Revisiting Sampling for Combinatorial Optimization	✅	❌	✅	❌	✅	❌	✅	4
Revisiting Simple Regret: Fast Rates for Returning a Good Arm	✅	❌	✅	❌	✅	❌	✅	4
Revisiting Structured Variational Autoencoders	❌	✅	❌	❌	✅	❌	✅	3
Revisiting Weighted Aggregation in Federated Learning with Neural Networks	✅	❌	✅	❌	✅	✅	✅	5
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation	❌	❌	❌	❌	❌	❌	❌	0
Reward-Mixing MDPs with Few Latent Contexts are Learnable	✅	❌	❌	❌	❌	❌	❌	1
Rigid Body Flows for Sampling Molecular Crystal Structures	❌	✅	❌	❌	✅	❌	✅	3
Robust Budget Pacing with a Single Sample	✅	❌	❌	❌	❌	❌	❌	1
Robust Camera Pose Refinement for Multi-Resolution Hash Encoding	❌	❌	✅	❌	❌	❌	✅	2
Robust Collaborative Learning with Linear Gradient Overhead	✅	✅	✅	❌	✅	✅	✅	6
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues	✅	✅	✅	❌	❌	❌	✅	4
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees	✅	❌	✅	✅	❌	❌	✅	4
Robust Explanation for Free or At the Cost of Faithfulness	❌	❌	✅	❌	❌	❌	✅	2
Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning	✅	✅	❌	❌	❌	❌	✅	3
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Robust Perception through Equivariance	✅	✅	✅	❌	✅	❌	✅	5
Robust Satisficing MDPs	✅	✅	✅	❌	✅	✅	✅	6
Robust Situational Reinforcement Learning in Face of Context Disturbances	❌	❌	❌	❌	❌	❌	✅	1
Robust Speech Recognition via Large-Scale Weak Supervision	❌	✅	✅	❌	❌	✅	✅	4
Robust Subtask Learning for Compositional Generalization	✅	✅	❌	❌	❌	❌	✅	3
Robust Weak Supervision with Variational Auto-Encoders	❌	❌	✅	❌	❌	❌	✅	2
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?	❌	✅	✅	❌	❌	❌	✅	3
Robust and Scalable Bayesian Online Changepoint Detection	❌	✅	✅	✅	✅	❌	✅	5
Robust and private stochastic linear bandits	✅	❌	❌	❌	❌	❌	❌	1
Robustly Learning a Single Neuron via Sharpness	✅	❌	❌	❌	❌	❌	✅	2
Robustness in Multimodal Learning under Train-Test Modality Mismatch	❌	❌	✅	✅	❌	❌	✅	3
Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch	✅	✅	❌	❌	✅	✅	❌	4
Rotation and Translation Invariant Representation Learning with Implicit Neural Representations	❌	✅	✅	❌	✅	❌	✅	4
Run-off Election: Improved Provable Defense against Data Poisoning Attacks	✅	✅	✅	❌	✅	❌	✅	5
SAAL: Sharpness-Aware Active Learning	✅	✅	✅	❌	❌	❌	✅	4
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon	❌	❌	✅	❌	❌	❌	✅	2
SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation	✅	❌	✅	❌	❌	❌	✅	3
SE(3) diffusion model with application to protein backbone generation	✅	✅	✅	❌	✅	❌	✅	5
SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning	✅	✅	✅	✅	❌	❌	✅	5
SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance	❌	❌	❌	❌	❌	❌	❌	0
SGD with Large Step Sizes Learns Sparse Features	❌	✅	✅	❌	❌	❌	✅	3
SLAMB: Accelerated Large Batch Training with Sparse Communication	✅	✅	✅	❌	✅	❌	✅	5
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process	❌	✅	✅	✅	❌	❌	❌	3
SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series	✅	✅	✅	✅	❌	❌	✅	5
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning.	✅	✅	✅	❌	❌	❌	✅	4
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition	✅	❌	✅	❌	✅	❌	✅	4
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient	✅	✅	✅	❌	✅	✅	✅	6
Safe Offline Reinforcement Learning with Real-Time Budget Constraints	✅	✅	✅	❌	❌	❌	✅	4
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models	❌	✅	✅	❌	❌	❌	✅	3
Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes	❌	❌	❌	❌	❌	❌	❌	0
Sample Complexity of Probability Divergences under Group Symmetry	❌	❌	❌	❌	❌	❌	✅	1
Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation	✅	✅	✅	❌	❌	❌	✅	4
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference	✅	✅	✅	❌	❌	❌	✅	4
Sampling-based Nyström Approximation and Kernel Quadrature	❌	✅	✅	❌	✅	❌	❌	3
Scalable Adaptive Computation for Iterative Generation	✅	❌	✅	❌	✅	❌	✅	4
Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation	❌	✅	✅	❌	❌	❌	✅	3
Scalable Safe Policy Improvement via Monte Carlo Tree Search	✅	✅	✅	❌	✅	❌	✅	5
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation	✅	✅	✅	✅	✅	❌	✅	6
Scaling Laws for Generative Mixed-Modal Language Models	❌	✅	✅	❌	✅	❌	✅	4
Scaling Laws for Multilingual Neural Machine Translation	❌	❌	✅	❌	❌	❌	✅	2
Scaling Laws for Reward Model Overoptimization	❌	❌	✅	✅	❌	❌	✅	3
Scaling Spherical CNNs	❌	✅	✅	✅	✅	❌	✅	5
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory	✅	❌	✅	❌	✅	❌	✅	4
Scaling Vision Transformers to 22 Billion Parameters	❌	❌	✅	✅	✅	❌	✅	4
Scaling of Class-wise Training Losses for Post-hoc Calibration	❌	✅	✅	✅	✅	❌	✅	5
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data	❌	❌	❌	❌	❌	❌	❌	0
SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models	✅	✅	✅	❌	✅	✅	✅	6
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning	❌	✅	✅	✅	✅	✅	✅	6
Second-Order Optimization with Lazy Hessians	✅	❌	✅	❌	❌	❌	✅	3
Second-order regression models exhibit progressive sharpening to the edge of stability	❌	❌	✅	❌	❌	❌	✅	2
Secure Federated Correlation Test and Entropy Estimation	✅	✅	✅	❌	✅	❌	✅	5
SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching	❌	✅	✅	❌	✅	❌	✅	4
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction	✅	✅	✅	✅	✅	❌	✅	6
Self-Interpretable Time Series Prediction with Counterfactual Explanations	✅	✅	✅	❌	❌	❌	❌	3
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains	❌	❌	✅	❌	❌	❌	✅	2
Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations	✅	❌	✅	❌	❌	❌	✅	3
Self-supervised learning of Split Invariant Equivariant representations	❌	✅	✅	✅	✅	❌	✅	5
SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification	❌	✅	✅	✅	✅	❌	✅	5
Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.	✅	✅	❌	❌	❌	❌	✅	3
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows	✅	✅	✅	✅	❌	❌	✅	5
Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm.	❌	❌	✅	❌	❌	❌	✅	2
Semi-Offline Reinforcement Learning for Optimized Text Generation	❌	✅	✅	✅	✅	❌	✅	5
Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model	✅	✅	❌	❌	❌	❌	✅	3
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories	✅	✅	✅	✅	❌	❌	✅	5
Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes	✅	❌	❌	✅	❌	❌	✅	3
Sequence Modeling with Multiresolution Convolutional Memory	✅	✅	✅	✅	❌	❌	✅	5
Sequential Changepoint Detection via Backward Confidence Sequences	❌	✅	❌	❌	❌	❌	✅	2
Sequential Counterfactual Risk Minimization	✅	✅	✅	❌	❌	✅	✅	5
Sequential Kernelized Independence Testing	✅	❌	✅	❌	❌	❌	✅	3
Sequential Monte Carlo Learning for Time Series Structure Discovery	✅	✅	✅	❌	✅	❌	✅	5
Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series	❌	✅	✅	✅	✅	❌	✅	5
Sequential Predictive Conformal Inference for Time Series	✅	✅	✅	✅	❌	❌	✅	5
Sequential Strategic Screening	❌	❌	❌	❌	❌	❌	❌	0
Sequential Underspecified Instrument Selection for Cause-Effect Estimation	✅	✅	❌	❌	❌	❌	✅	3
Set-membership Belief State-based Reinforcement Learning for POMDPs	✅	❌	✅	❌	❌	❌	❌	2
Settling the Reward Hypothesis	✅	❌	❌	❌	❌	❌	❌	1
Shape-Guided Dual-Memory Learning for 3D Anomaly Detection	❌	❌	✅	✅	✅	❌	✅	4
Shapley Based Residual Decomposition for Instance Analysis	❌	✅	✅	❌	✅	❌	✅	4
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments	✅	❌	❌	❌	❌	❌	❌	1
Sharper Bounds for $\ell_p$ Sensitivity Sampling	❌	❌	❌	❌	❌	❌	❌	0
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances	✅	✅	✅	❌	✅	❌	✅	5
Shiftable Context: Addressing Training-Inference Context Mismatch in Simultaneous Speech Translation	❌	✅	✅	✅	✅	❌	✅	5
Short-lived High-volume Bandits	✅	❌	❌	❌	❌	❌	✅	2
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search	❌	✅	✅	✅	✅	❌	✅	5
Simple Disentanglement of Style and Content in Visual Representations	✅	✅	✅	✅	❌	❌	✅	5
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning	❌	❌	❌	❌	❌	❌	✅	1
Simple Hardware-Efficient Long Convolutions for Sequence Modeling	✅	✅	✅	✅	✅	❌	✅	6
Simple and Fast Group Robustness by Automatic Feature Reweighting	✅	✅	✅	✅	✅	❌	✅	6
Simplex Random Features	✅	✅	✅	✅	✅	❌	✅	6
Simplified Temporal Consistency Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning	✅	❌	✅	✅	❌	❌	✅	4
SinDDM: A Single Image Denoising Diffusion Model	✅	✅	❌	❌	✅	❌	✅	4
SinFusion: Training Diffusion Models on a Single Image or Video	✅	❌	✅	❌	✅	❌	✅	4
Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function	✅	❌	✅	❌	❌	❌	✅	3
Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition	❌	✅	✅	✅	❌	❌	✅	4
Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting	❌	❌	✅	❌	❌	❌	✅	2
Sketched Ridgeless Linear Regression: The Role of Downsampling	❌	✅	❌	✅	✅	❌	✅	4
Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance	✅	❌	❌	❌	❌	❌	❌	1
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability	✅	❌	❌	❌	❌	❌	❌	1
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals	✅	✅	✅	✅	✅	❌	✅	6
Slot-VAE: Object-Centric Scene Generation with Slot Attention	❌	❌	✅	❌	❌	❌	✅	2
SlotGAT: Slot-based Message Passing for Heterogeneous Graphs	✅	✅	✅	✅	✅	✅	✅	7
Smart Initial Basis Selection for Linear Programs	✅	✅	✅	✅	✅	✅	✅	7
Smooth Non-stationary Bandits	✅	❌	❌	❌	❌	❌	✅	2
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning	❌	✅	✅	❌	✅	❌	✅	4
Solving High-Dimensional PDEs with Latent Spectral Models	❌	✅	✅	❌	✅	❌	✅	4
Solving Linear Programs with Fast Online Learning Algorithms	✅	❌	✅	❌	❌	✅	✅	4
SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference	✅	✅	✅	❌	✅	✅	✅	6
Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach	✅	❌	❌	❌	❌	❌	✅	2
SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot	✅	✅	✅	✅	✅	❌	✅	6
SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge	✅	✅	✅	✅	❌	❌	✅	5
Spatial Implicit Neural Representations for Global-Scale Species Mapping	❌	✅	✅	❌	✅	✅	✅	5
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation	✅	✅	❌	✅	✅	✅	✅	6
Special Properties of Gradient Descent with Large Learning Rates	✅	❌	✅	❌	❌	❌	✅	3
Specializing Smaller Language Models towards Multi-Step Reasoning	❌	✅	✅	✅	❌	❌	✅	4
Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary	✅	❌	✅	❌	✅	❌	✅	4
SpeedDETR: Speed-aware Transformers for End-to-end Object Detection	✅	✅	✅	❌	✅	❌	✅	5
Speeding Up Bellman Ford via Minimum Violation Permutations	✅	❌	✅	❌	❌	❌	✅	3
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere	❌	✅	✅	✅	✅	✅	✅	6
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes	❌	✅	✅	✅	✅	❌	✅	5
SpotEM: Efficient Video Search for Episodic Memory	❌	✅	✅	✅	❌	❌	✅	4
Spurious Valleys and Clustering Behavior of Neural Networks	❌	❌	❌	❌	❌	❌	✅	1
Stabilizing GANs’ Training with Brownian Motion Controller	❌	❌	✅	✅	✅	❌	✅	4
Stabilizing Transformer Training by Preventing Attention Entropy Collapse	✅	✅	✅	✅	✅	❌	✅	6
Stable Estimation of Heterogeneous Treatment Effects	✅	✅	✅	✅	✅	✅	✅	7
Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning	❌	❌	✅	✅	❌	❌	✅	3
State and parameter learning with PARIS particle Gibbs	✅	✅	❌	❌	✅	❌	✅	4
Statistical Foundations of Prior-Data Fitted Networks	❌	✅	❌	❌	❌	✅	✅	3
Statistical Indistinguishability of Learning Algorithms	✅	❌	❌	❌	❌	❌	❌	1
Statistical Inference and A/B Testing for First-Price Pacing Equilibria	✅	❌	❌	❌	❌	❌	✅	2
Statistical Inference on Multi-armed Bandits with Delayed Feedback	❌	✅	❌	❌	❌	❌	✅	2
Statistical Learning under Heterogeneous Distribution Shift	❌	❌	✅	❌	❌	❌	✅	2
Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
Stochastic Gradient Descent under Markovian Sampling Schemes	✅	❌	❌	❌	❌	❌	✅	2
Stochastic Gradient Descent-Induced Drift of Representation in a Two-Layer Neural Network	❌	❌	❌	❌	❌	❌	✅	1
Stochastic Gradient Succeeds for Bandits	✅	❌	❌	❌	❌	❌	✅	2
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels	✅	✅	✅	❌	✅	❌	✅	5
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies	✅	❌	✅	❌	❌	❌	✅	3
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks	✅	✅	✅	❌	❌	❌	✅	4
Strategic Classification with Unknown User Manipulations	✅	❌	❌	❌	❌	❌	❌	1
Stratified Adversarial Robustness with Rejection	✅	✅	✅	✅	✅	❌	✅	6
Streaming Active Learning with Deep Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Streaming Submodular Maximization with Differential Privacy	✅	✅	✅	❌	✅	❌	✅	5
StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes	❌	✅	✅	✅	✅	✅	✅	6
Structural Re-weighting Improves Graph Domain Adaptation	✅	✅	✅	✅	❌	❌	✅	5
Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs	✅	❌	✅	✅	❌	✅	✅	5
Structure-informed Language Models Are Protein Designers	✅	❌	✅	✅	✅	❌	✅	5
Structured Cooperative Learning with Graphical Model Priors	✅	✅	✅	✅	❌	❌	✅	5
StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis	❌	✅	✅	❌	✅	❌	✅	4
Subequivariant Graph Reinforcement Learning in 3D Environments	❌	✅	✅	❌	❌	❌	✅	3
Submodular Order Functions and Assortment Optimization	✅	❌	❌	❌	❌	❌	❌	1
Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation	❌	❌	✅	✅	❌	❌	✅	3
Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions	✅	✅	✅	❌	❌	❌	✅	4
Subset-Based Instance Optimality in Private Estimation	✅	❌	❌	❌	❌	❌	❌	1
Superhuman Fairness	✅	✅	✅	❌	❌	❌	✅	4
Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization	✅	✅	✅	❌	✅	❌	✅	5
Supported Trust Region Optimization for Offline Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems	✅	❌	✅	❌	✅	❌	✅	4
SurProGenes: Survival Risk-Ordered Representation of Cancer Patients and Genes for the Identification of Prognostic Genes	✅	✅	✅	❌	❌	❌	✅	4
Surface Snapping Optimization Layer for Single Image Object Shape Reconstruction	❌	❌	✅	❌	✅	❌	❌	2
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Symmetry-Aware Robot Design with Structured Subgroups	✅	✅	✅	❌	✅	❌	✅	5
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning	❌	✅	✅	✅	❌	❌	✅	4
Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data	❌	✅	✅	✅	✅	❌	✅	5
Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models	✅	❌	✅	❌	❌	❌	✅	3
Synthetic data for model selection	❌	❌	✅	✅	❌	❌	✅	3
System Identification of Neural Systems: If We Got It Right, Would We Know?	❌	❌	✅	✅	❌	✅	✅	4
TAN Without a Burn: Scaling Laws of DP-SGD	❌	✅	✅	❌	✅	❌	✅	4
TGRL: An Algorithm for Teacher Guided Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
TIDE: Time Derivative Diffusion for Deep Learning on Graphs	❌	✅	✅	✅	✅	❌	✅	5
TIPS: Topologically Important Path Sampling for Anytime Neural Networks	✅	❌	✅	❌	✅	❌	✅	4
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation	✅	✅	✅	✅	✅	❌	✅	6
TRAK: Attributing Model Behavior at Scale	✅	✅	✅	✅	✅	❌	✅	6
TabDDPM: Modelling Tabular Data with Diffusion Models	❌	✅	✅	✅	✅	✅	✅	6
TabLeak: Tabular Data Leakage in Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Taming graph kernels with random features	✅	❌	✅	❌	❌	❌	✅	3
Target-Aware Generative Augmentations for Single-Shot Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Target-based Surrogates for Stochastic Optimization	✅	✅	✅	❌	✅	❌	✅	5
Task-Specific Skill Localization in Fine-tuned Language Models	❌	✅	✅	✅	❌	❌	✅	4
Task-specific experimental design for treatment effect estimation	✅	❌	✅	✅	✅	❌	✅	5
Taxonomy-Structured Domain Adaptation	✅	✅	✅	❌	✅	❌	✅	5
Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization	✅	❌	✅	❌	✅	❌	❌	3
Temporal Label Smoothing for Early Event Prediction	✅	✅	✅	❌	✅	✅	✅	6
Temporally Consistent Transformers for Video Generation	❌	❌	✅	❌	✅	❌	✅	3
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems	✅	❌	❌	❌	❌	❌	❌	1
Tensor Gaussian Process with Contraction for Multi-Channel Imaging Analysis	✅	✅	❌	❌	❌	❌	✅	3
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization	✅	❌	✅	✅	❌	❌	✅	4
Test-time Adaptation with Slot-Centric Models	❌	✅	✅	❌	✅	❌	✅	4
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise	❌	✅	✅	✅	✅	❌	✅	5
Text-To-4D Dynamic Scene Generation	❌	❌	✅	✅	✅	❌	✅	4
Text-To-Concept (and Back) via Cross-Model Alignment	❌	❌	✅	❌	❌	✅	✅	3
The Acquisition of Physical Knowledge in Generative Neural Networks	❌	❌	❌	✅	✅	❌	✅	3
The Benefits of Mixup for Feature Learning	❌	❌	✅	❌	❌	❌	✅	2
The Benefits of Model-Based Generalization in Reinforcement Learning	❌	✅	❌	❌	❌	❌	✅	2
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond	✅	❌	❌	❌	❌	❌	✅	2
The Catalog Problem: Clustering and Ordering Variable-Sized Sets	✅	✅	✅	✅	✅	✅	✅	7
The Computational Complexity of Concise Hypersphere Classification	❌	❌	❌	❌	❌	❌	❌	0
The Dormant Neuron Phenomenon in Deep Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick	✅	❌	✅	✅	✅	❌	✅	5
The Fast Johnson-Lindenstrauss Transform Is Even Faster	❌	❌	❌	❌	❌	❌	❌	0
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning	❌	✅	✅	✅	❌	❌	✅	4
The Hessian perspective into the Nature of Convolutional Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
The Ideal Continual Learner: An Agent That Never Forgets	❌	❌	❌	❌	❌	❌	❌	0
The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics	❌	❌	❌	❌	❌	❌	✅	1
The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent	❌	❌	❌	❌	❌	❌	✅	1
The Monge Gap: A Regularizer to Learn All Transport Maps	✅	✅	✅	❌	❌	❌	✅	4
The Numerical Stability of Hyperbolic Representation Learning	❌	✅	✅	❌	❌	❌	✅	3
The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation	❌	❌	❌	❌	❌	❌	❌	0
The Persistent Laplacian for Data Science: Evaluating Higher-Order Persistent Spectral Representations of Data	❌	✅	✅	❌	✅	❌	✅	4
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization	✅	❌	❌	❌	❌	❌	✅	2
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing	❌	❌	✅	❌	❌	❌	✅	2
The Power of Uniform Sampling for k-Median	❌	❌	✅	❌	✅	❌	❌	2
The Price of Differential Privacy under Continual Observation	✅	❌	❌	❌	❌	❌	❌	1
The Regret of Exploration and the Control of Bad Episodes in Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning	✅	✅	✅	✅	❌	❌	✅	5
The SSL Interplay: Augmentations, Inductive Bias, and Generalization	❌	❌	✅	❌	❌	❌	✅	2
The Saddle-Point Method in Differential Privacy	✅	✅	❌	❌	❌	❌	✅	3
The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation	✅	❌	✅	❌	❌	❌	✅	3
The Statistical Scope of Multicalibration	✅	❌	❌	❌	❌	❌	❌	1
The Test of Tests: A Framework for Differentially Private Hypothesis Testing	✅	✅	❌	❌	❌	❌	✅	3
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
The Unreasonable Effectiveness of Few-shot Learning for Machine Translation	❌	❌	✅	✅	❌	✅	✅	4
The Value of Out-of-Distribution Data	❌	✅	✅	✅	❌	❌	✅	4
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms	✅	✅	✅	❌	❌	❌	✅	4
The Wisdom of Hindsight Makes Language Models Better Instruction Followers	✅	✅	✅	❌	❌	❌	✅	4
The case for 4-bit precision: k-bit Inference Scaling Laws	❌	❌	✅	❌	✅	❌	✅	3
Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables	❌	❌	❌	❌	❌	❌	❌	0
Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming	✅	✅	✅	❌	❌	❌	✅	4
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting	✅	❌	✅	✅	❌	❌	✅	4
Theory on Forgetting and Generalization of Continual Learning	❌	❌	✅	❌	❌	❌	✅	2
Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits	✅	✅	✅	❌	❌	❌	✅	4
Thompson Sampling with Diffusion Generative Prior	✅	❌	✅	✅	✅	❌	✅	5
Thompson Sampling with Less Exploration is Fast and Optimal	✅	❌	❌	❌	✅	❌	✅	3
Tied-Augment: Controlling Representation Similarity Improves Data Augmentation	✅	✅	✅	✅	✅	❌	✅	6
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations	✅	✅	✅	❌	✅	❌	✅	5
Tight Data Access Bounds for Private Top-$k$ Selection	✅	❌	❌	❌	❌	❌	❌	1
Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits	✅	✅	❌	❌	✅	❌	✅	4
Tight and fast generalization error bound of graph embedding in metric space	❌	❌	❌	❌	❌	❌	❌	0
Tighter Analysis for ProxSkip	✅	❌	❌	❌	❌	❌	✅	2
Tighter Bounds on the Expressivity of Transformer Encoders	❌	❌	❌	❌	❌	❌	❌	0
Tighter Information-Theoretic Generalization Bounds from Supersamples	❌	❌	✅	❌	✅	❌	✅	3
Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond	✅	❌	❌	❌	❌	❌	❌	1
Tilted Sparse Additive Models	✅	❌	✅	✅	❌	❌	✅	4
Topological Point Cloud Clustering	✅	✅	❌	❌	❌	❌	✅	3
Topological Singularity Detection at Multiple Scales	✅	✅	✅	❌	❌	❌	✅	4
Topologically Faithful Image Segmentation via Induced Matching of Persistence Barcodes	✅	✅	✅	✅	✅	❌	✅	6
Total Variation Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Toward Efficient Gradient-Based Value Estimation	✅	❌	✅	❌	❌	❌	✅	3
Toward Large Kernel Models	✅	✅	✅	❌	✅	❌	✅	5
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering	❌	✅	✅	✅	✅	❌	✅	5
Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten	✅	❌	✅	✅	❌	❌	✅	4
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models	✅	✅	✅	✅	✅	❌	✅	6
Towards Constituting Mathematical Structures for Learning to Optimize	❌	✅	✅	❌	✅	✅	✅	5
Towards Controlled Data Augmentations for Active Learning	✅	✅	✅	❌	❌	❌	✅	4
Towards Deep Attention in Graph Neural Networks: Problems and Remedies	❌	✅	✅	✅	❌	❌	✅	4
Towards Explaining Distribution Shifts	✅	✅	✅	❌	❌	❌	✅	4
Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks	❌	❌	✅	❌	✅	❌	✅	3
Towards Omni-generalizable Neural Methods for Vehicle Routing Problems	✅	✅	✅	✅	✅	✅	✅	7
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes	✅	✅	✅	❌	❌	❌	✅	4
Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver	❌	❌	❌	❌	✅	❌	✅	2
Towards Reliable Neural Specifications	✅	❌	✅	❌	✅	❌	✅	4
Towards Robust Graph Incremental Learning on Evolving Graphs	✅	✅	✅	✅	✅	❌	✅	6
Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data	✅	❌	✅	❌	❌	❌	✅	3
Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks	✅	✅	✅	✅	✅	❌	✅	6
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning	✅	✅	✅	❌	✅	❌	✅	5
Towards Theoretical Understanding of Inverse Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Towards Trustworthy Explanation: On Causal Rationalization	✅	✅	✅	✅	✅	❌	✅	6
Towards Unbiased Training in Federated Open-world Semi-supervised Learning	✅	❌	✅	✅	✅	❌	✅	5
Towards Understanding Ensemble Distillation in Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Towards Understanding Generalization of Graph Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
Towards Understanding Generalization of Macro-AUC in Multi-label Learning	❌	✅	✅	✅	✅	❌	✅	5
Towards Understanding and Improving GFlowNet Training	❌	✅	✅	❌	❌	❌	✅	3
Towards Understanding and Reducing Graph Structural Noise for GNNs	✅	✅	✅	✅	❌	❌	✅	5
Towards a Persistence Diagram that is Robust to Noise and Varied Densities	❌	✅	✅	✅	✅	❌	✅	5
Towards a better understanding of representation dynamics under TD-learning	❌	❌	✅	❌	❌	✅	✅	3
Towards credible visual model interpretation with path attribution	✅	❌	✅	✅	✅	❌	✅	5
Tractable Control for Autoregressive Language Generation	✅	✅	✅	✅	✅	❌	✅	6
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts	✅	❌	❌	❌	❌	❌	✅	2
Trainability, Expressivity and Interpretability in Gated Neural ODEs	❌	❌	✅	✅	❌	✅	✅	4
Training Deep Surrogate Models with Large Scale Online Learning	❌	✅	✅	✅	✅	❌	✅	5
Training Normalizing Flows from Dependent Data	❌	✅	✅	✅	✅	✅	✅	6
Training-Free Neural Active Learning with Initialization-Robustness Guarantees	✅	✅	✅	❌	❌	❌	✅	4
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving	✅	✅	✅	✅	❌	❌	✅	5
Transformed Distribution Matching for Missing Value Imputation	✅	✅	✅	✅	❌	❌	✅	5
Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization	✅	❌	❌	✅	✅	✅	❌	4
Transformers Learn In-Context by Gradient Descent	❌	✅	❌	✅	❌	❌	✅	3
Transformers Meet Directed Graphs	✅	✅	✅	✅	✅	❌	✅	6
Transformers as Algorithms: Generalization and Stability in In-context Learning	❌	✅	❌	❌	❌	❌	✅	2
Trapdoor Normalization with Irreversible Ownership Verification	✅	❌	✅	❌	✅	❌	✅	4
Traversing Between Modes in Function Space for Fast Ensembling	✅	✅	✅	✅	✅	✅	✅	7
Trompt: Towards a Better Deep Neural Network for Tabular Data	❌	❌	✅	❌	❌	❌	✅	2
Truncating Trajectories in Monte Carlo Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
Trustworthy Policy Learning under the Counterfactual No-Harm Criterion	❌	❌	✅	✅	❌	❌	✅	3
Tuning Computer Vision Models With Task Rewards	✅	✅	✅	✅	❌	❌	✅	5
Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning	✅	✅	✅	✅	✅	❌	✅	6
Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy	✅	❌	✅	❌	❌	❌	✅	3
Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective	❌	❌	❌	❌	❌	❌	❌	0
UMD: Unsupervised Model Detection for X2X Backdoor Attacks	✅	✅	✅	✅	✅	❌	✅	6
UPSCALE: Unconstrained Channel Pruning	✅	✅	✅	✅	✅	❌	✅	6
UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers	✅	✅	✅	❌	❌	❌	✅	4
Uncertain Evidence in Probabilistic Models and Stochastic Simulators	❌	❌	✅	❌	❌	❌	✅	2
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning	✅	✅	✅	✅	❌	❌	✅	5
Uncertainty Estimation for Molecules: Desiderata and Methods	❌	✅	✅	✅	❌	❌	✅	4
Unconstrained Online Learning with Unbounded Losses	✅	❌	❌	❌	❌	❌	❌	1
Uncovering Adversarial Risks of Test-Time Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Under-Counted Tensor Completion with Neural Incorporation of Attributes	✅	✅	✅	✅	❌	❌	✅	5
Understand and Modularize Generator Optimization in ELECTRA-style Pretraining	❌	✅	✅	✅	✅	❌	✅	5
Understanding Backdoor Attacks through the Adaptability Hypothesis	✅	❌	✅	❌	✅	❌	✅	4
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias	✅	✅	✅	❌	✅	❌	✅	5
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing	❌	❌	❌	❌	❌	❌	✅	1
Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases	❌	✅	✅	✅	✅	✅	✅	6
Understanding Oversquashing in GNNs through the Lens of Effective Resistance	❌	✅	✅	✅	❌	❌	✅	4
Understanding Plasticity in Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Understanding Self-Distillation in the Presence of Label Noise	❌	❌	✅	✅	❌	❌	✅	3
Understanding Self-Predictive Learning for Reinforcement Learning	✅	❌	✅	❌	❌	✅	✅	4
Understanding and Defending Patched-based Adversarial Attacks for Vision Transformer	✅	❌	✅	❌	✅	❌	✅	4
Understanding and Generalizing Contrastive Learning from the Inverse Optimal Transport Perspective	✅	❌	✅	✅	✅	❌	✅	5
Understanding the Complexity Gains of Single-Task RL with a Curriculum	✅	❌	✅	❌	❌	❌	✅	3
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits	✅	✅	✅	❌	❌	❌	✅	4
Understanding the Impact of Adversarial Robustness on Accuracy Disparity	❌	✅	✅	✅	✅	❌	✅	5
Understanding the Role of Feedback in Online Learning with Switching Costs	✅	❌	❌	❌	❌	❌	❌	1
Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data	❌	✅	✅	❌	❌	❌	✅	3
Unifying Molecular and Textual Representations via Multi-task Language Modelling	❌	✅	✅	✅	❌	❌	✅	4
Unifying Nesterov’s Accelerated Gradient Methods for Convex and Strongly Convex Objective Functions	✅	❌	❌	❌	❌	❌	✅	2
Unit Scaling: Out-of-the-Box Low-Precision Training	✅	✅	✅	❌	✅	❌	✅	5
Universal Morphology Control via Contextual Modulation	❌	✅	✅	❌	❌	❌	✅	3
Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data	❌	❌	❌	❌	❌	❌	✅	1
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability	✅	✅	✅	✅	✅	✅	✅	7
Unlocking Slot Attention by Changing Optimal Transport Costs	❌	✅	✅	✅	❌	❌	✅	4
Unscented Autoencoder	❌	✅	✅	✅	❌	✅	✅	5
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting	✅	✅	✅	❌	❌	❌	✅	4
Unsupervised Skill Discovery for Learning Shared Structures across Changing Environments	✅	❌	✅	❌	❌	❌	✅	3
Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features	❌	✅	✅	✅	❌	❌	✅	4
Unveiling the Latent Space Geometry of Push-Forward Generative Models	❌	✅	✅	❌	✅	❌	✅	4
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems	❌	❌	❌	❌	❌	❌	✅	1
User-level Private Stochastic Convex Optimization with Optimal Rates	✅	❌	❌	❌	❌	❌	❌	1
Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies	❌	✅	✅	❌	❌	❌	✅	3
Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy	✅	✅	❌	❌	❌	❌	✅	3
VA-learning as a more efficient alternative to Q-learning	✅	❌	✅	❌	❌	❌	✅	3
VIMA: Robot Manipulation with Multimodal Prompts	✅	✅	✅	✅	✅	✅	✅	7
Variance Control for Distributional Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Variational Autoencoding Neural Operators	❌	❌	✅	❌	✅	❌	✅	3
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills	❌	✅	❌	❌	✅	❌	✅	3
Variational Mixture of HyperGenerators for Learning Distributions over Functions	✅	✅	✅	❌	✅	❌	✅	5
Variational Open-Domain Question Answering	❌	✅	✅	✅	✅	✅	✅	6
Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization	❌	✅	✅	❌	✅	❌	✅	4
Vector Quantized Wasserstein Auto-Encoder	✅	❌	✅	❌	✅	❌	✅	4
Vector-Valued Control Variates	✅	✅	✅	❌	❌	❌	✅	4
VectorMapNet: End-to-end Vectorized HD Map Learning	✅	❌	✅	✅	✅	❌	✅	5
Vertical Federated Graph Neural Network for Recommender System	✅	✅	✅	✅	✅	❌	✅	6
Von Mises Mixture Distributions for Molecular Conformation Generation	❌	✅	✅	❌	✅	❌	✅	4
WL meet VC	❌	✅	✅	❌	✅	❌	✅	4
Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap	❌	❌	❌	❌	❌	❌	✅	1
Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes	✅	✅	✅	❌	❌	❌	✅	4
Weakly Supervised Regression with Interval Targets	❌	❌	✅	✅	❌	❌	✅	3
Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees	✅	✅	✅	❌	❌	❌	✅	4
Weighted Sampling without Replacement for Deep Top-$k$ Classification	❌	❌	✅	✅	✅	❌	✅	4
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality	✅	❌	❌	❌	❌	❌	✅	2
What Can Be Learnt With Wide Convolutional Neural Networks?	❌	✅	✅	❌	✅	✅	✅	5
What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings	✅	✅	✅	✅	✅	❌	✅	6
What can online reinforcement learning with function approximation benefit from general coverage conditions?	✅	❌	❌	❌	❌	❌	❌	1
What do CNNs Learn in the First Layer and Why? A Linear Systems Perspective	❌	✅	✅	❌	❌	❌	❌	2
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?	✅	✅	✅	❌	✅	❌	✅	5
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction	❌	✅	✅	❌	❌	❌	✅	3
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations	❌	❌	✅	✅	✅	❌	✅	4
When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis	❌	✅	✅	✅	❌	❌	✅	4
When do Minimax-fair Learning and Empirical Risk Minimization Coincide?	❌	✅	✅	❌	✅	❌	✅	4
When does Privileged information Explain Away Label Noise?	❌	✅	✅	✅	❌	❌	✅	4
When is Realizability Sufficient for Off-Policy Reinforcement Learning?	❌	❌	❌	❌	❌	❌	❌	0
Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression	❌	❌	✅	❌	❌	❌	✅	2
Which Invariance Should We Transfer? A Causal Minimax Learning Approach	✅	✅	✅	✅	✅	✅	✅	7
Which Tricks are Important for Learning to Rank?	❌	❌	✅	✅	❌	❌	✅	3
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?	✅	❌	✅	✅	✅	❌	✅	5
Who Needs to Know? Minimal Knowledge for Optimal Coordination	✅	❌	✅	❌	❌	❌	✅	3
Whose Opinions Do Language Models Reflect?	❌	✅	✅	❌	❌	❌	✅	3
Why Is Public Pretraining Necessary for Private Model Training?	❌	❌	✅	✅	❌	❌	✅	3
Why Random Pruning Is All We Need to Start Sparse	❌	✅	✅	✅	✅	❌	✅	5
Why Target Networks Stabilise Temporal Difference Methods	❌	❌	✅	❌	❌	❌	✅	2
Why do Nearest Neighbor Language Models Work?	❌	✅	✅	✅	❌	❌	✅	4
Why does Throwing Away Data Improve Worst-Group Error?	❌	✅	✅	❌	❌	❌	✅	3
Width and Depth Limits Commute in Residual Networks	❌	❌	❌	❌	❌	❌	✅	1
Wrapped Cauchy Distributed Angular Softmax for Long-Tailed Visual Recognition	✅	✅	✅	❌	❌	❌	✅	4
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion	❌	✅	✅	✅	❌	❌	✅	4
XTab: Cross-table Pretraining for Tabular Transformers	❌	✅	✅	✅	✅	❌	✅	5
dugMatting: Decomposed-Uncertainty-Guided Matting	✅	✅	✅	❌	✅	❌	✅	5
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video	❌	✅	✅	✅	✅	❌	✅	5
simple diffusion: End-to-end diffusion for high resolution images	✅	❌	✅	❌	✅	❌	✅	4
spred: Solving L1 Penalty with SGD	✅	✅	✅	✅	❌	❌	✅	5