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) - 2022

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	2022	1233	0.58	3.97	92.94%	42.84%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
$p$-Laplacian Based Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
(Non-)Convergence Results for Predictive Coding Networks	❌	❌	❌	❌	❌	❌	❌	0
3D Infomax improves GNNs for Molecular Property Prediction	❌	✅	✅	✅	✅	❌	✅	5
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design	❌	✅	✅	✅	❌	❌	✅	4
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation	✅	✅	✅	❌	✅	✅	✅	6
A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks	❌	✅	✅	❌	✅	❌	✅	4
A Closer Look at Smoothness in Domain Adversarial Training	✅	✅	✅	✅	✅	❌	✅	6
A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation	✅	❌	✅	❌	❌	✅	✅	4
A Consistent and Efficient Evaluation Strategy for Attribution Methods	❌	✅	✅	❌	✅	❌	✅	4
A Context-Integrated Transformer-Based Neural Network for Auction Design	✅	✅	❌	❌	❌	❌	✅	3
A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1	✅	❌	❌	❌	❌	❌	❌	1
A Convergent and Dimension-Independent Min-Max Optimization Algorithm	✅	❌	✅	❌	✅	❌	✅	4
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications	❌	✅	✅	✅	✅	❌	✅	5
A Difference Standardization Method for Mutual Transfer Learning	✅	❌	✅	✅	✅	❌	✅	5
A Differential Entropy Estimator for Training Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
A Dynamical System Perspective for Lipschitz Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
A Framework for Learning to Request Rich and Contextually Useful Information from Humans	❌	✅	✅	✅	❌	❌	✅	4
A Functional Information Perspective on Model Interpretation	❌	✅	✅	✅	❌	❌	❌	3
A General Recipe for Likelihood-free Bayesian Optimization	❌	✅	✅	❌	❌	❌	✅	3
A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines	✅	❌	✅	❌	❌	❌	✅	3
A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs	❌	❌	✅	✅	❌	❌	✅	3
A Joint Exponential Mechanism For Differentially Private Top-$k$	✅	✅	✅	❌	❌	❌	✅	4
A Langevin-like Sampler for Discrete Distributions	✅	✅	✅	✅	❌	❌	✅	5
A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving	✅	❌	✅	❌	✅	❌	✅	4
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes	❌	✅	✅	❌	❌	❌	✅	3
A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace Sampling	✅	✅	✅	❌	❌	❌	✅	4
A Modern Self-Referential Weight Matrix That Learns to Modify Itself	❌	✅	✅	✅	✅	❌	✅	5
A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity	✅	❌	✅	❌	❌	❌	❌	2
A Natural Actor-Critic Framework for Zero-Sum Markov Games	✅	❌	✅	❌	❌	❌	✅	3
A Neural Tangent Kernel Perspective of GANs	❌	✅	✅	❌	✅	✅	✅	5
A New Perspective on the Effects of Spectrum in Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
A Parametric Class of Approximate Gradient Updates for Policy Optimization	❌	❌	✅	❌	❌	❌	✅	2
A Psychological Theory of Explainability	❌	✅	✅	✅	❌	❌	❌	3
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources	✅	✅	✅	❌	❌	❌	❌	3
A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds	❌	❌	❌	❌	❌	❌	❌	0
A Regret Minimization Approach to Multi-Agent Control	✅	❌	❌	❌	❌	❌	✅	2
A Resilient Distributed Boosting Algorithm	✅	❌	❌	❌	❌	❌	❌	1
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions	❌	✅	✅	❌	❌	❌	❌	2
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games	✅	❌	❌	❌	❌	❌	❌	1
A Simple Guard for Learned Optimizers	✅	❌	✅	✅	✅	✅	✅	6
A Simple Reward-free Approach to Constrained Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
A Simple Unified Framework for High Dimensional Bandit Problems	✅	❌	❌	❌	❌	❌	❌	1
A Simple yet Universal Strategy for Online Convex Optimization	✅	❌	❌	❌	❌	❌	✅	2
A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization	✅	❌	✅	❌	✅	❌	✅	4
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
A Statistical Manifold Framework for Point Cloud Data	❌	✅	✅	✅	❌	❌	✅	4
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms	❌	❌	❌	❌	❌	❌	✅	1
A Study of Face Obfuscation in ImageNet	❌	✅	✅	✅	✅	❌	✅	5
A Study on the Ramanujan Graph Property of Winning Lottery Tickets	✅	❌	✅	❌	❌	❌	✅	3
A Temporal-Difference Approach to Policy Gradient Estimation	✅	✅	✅	❌	❌	❌	✅	4
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization	✅	✅	❌	❌	❌	❌	✅	3
A Theoretical Comparison of Graph Neural Network Extensions	❌	❌	❌	❌	❌	❌	❌	0
A Tighter Analysis of Spectral Clustering, and Beyond	❌	✅	✅	❌	✅	❌	❌	3
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources	✅	✅	✅	✅	✅	❌	✅	6
A Unified View on PAC-Bayes Bounds for Meta-Learning	❌	❌	✅	❌	❌	❌	✅	2
A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
A data-driven approach for learning to control computers	❌	❌	✅	❌	❌	❌	✅	2
A deep convolutional neural network that is invariant to time rescaling	❌	❌	✅	❌	❌	❌	✅	2
A new similarity measure for covariate shift with applications to nonparametric regression	❌	❌	❌	❌	❌	❌	❌	0
A query-optimal algorithm for finding counterfactuals	✅	❌	❌	❌	❌	❌	❌	1
A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing	❌	✅	✅	✅	❌	❌	✅	4
AGNAS: Attention-Guided Micro and Macro-Architecture Search	✅	✅	✅	✅	✅	❌	✅	6
ASAP.SGD: Instance-based Adaptiveness to Staleness in Asynchronous SGD	✅	✅	✅	❌	✅	❌	✅	5
Accelerated Federated Learning with Decoupled Adaptive Optimization	✅	❌	✅	❌	✅	❌	✅	4
Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis	✅	✅	❌	❌	❌	❌	✅	3
Accelerated, Optimal and Parallel: Some results on model-based stochastic optimization	❌	❌	❌	❌	❌	❌	✅	1
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders	✅	✅	✅	✅	✅	❌	✅	6
Accelerating Shapley Explanation via Contributive Cooperator Selection	✅	✅	✅	✅	✅	❌	✅	6
Accurate Quantization of Measures via Interacting Particle-based Optimization	✅	✅	❌	❌	❌	❌	✅	3
Achieving Fairness at No Utility Cost via Data Reweighing with Influence	✅	✅	✅	✅	❌	✅	✅	6
Achieving Minimax Rates in Pool-Based Batch Active Learning	✅	❌	❌	❌	❌	❌	❌	1
Action-Sufficient State Representation Learning for Control with Structural Constraints	✅	❌	✅	❌	❌	❌	✅	3
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets	✅	✅	✅	❌	❌	❌	✅	4
Active Multi-Task Representation Learning	✅	❌	✅	❌	❌	❌	❌	2
Active Nearest Neighbor Regression Through Delaunay Refinement	✅	✅	✅	❌	✅	❌	✅	5
Active Sampling for Min-Max Fairness	✅	✅	✅	✅	❌	❌	✅	5
Active fairness auditing	✅	❌	✅	❌	❌	❌	❌	2
ActiveHedge: Hedge meets Active Learning	✅	❌	❌	❌	❌	❌	✅	2
Actor-Critic based Improper Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems	✅	❌	✅	❌	❌	❌	✅	3
AdaGrad Avoids Saddle Points	❌	❌	❌	❌	❌	❌	❌	0
Adapting k-means Algorithms for Outliers	✅	❌	✅	❌	❌	❌	✅	3
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning	✅	❌	✅	❌	✅	❌	✅	4
Adapting to Mixing Time in Stochastic Optimization with Markovian Data	✅	❌	❌	❌	❌	❌	✅	2
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction	✅	❌	✅	❌	❌	❌	✅	3
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits	✅	❌	❌	❌	❌	❌	❌	1
Adaptive Conformal Predictions for Time Series	✅	✅	❌	✅	❌	❌	✅	4
Adaptive Data Analysis with Correlated Observations	✅	❌	❌	❌	❌	❌	❌	1
Adaptive Gaussian Process Change Point Detection	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Model Design for Markov Decision Process	✅	❌	❌	❌	❌	❌	✅	2
Adaptive Random Walk Gradient Descent for Decentralized Optimization	✅	❌	✅	❌	❌	❌	✅	3
Adaptive Second Order Coresets for Data-efficient Machine Learning	✅	✅	✅	❌	✅	❌	✅	5
Additive Gaussian Processes Revisited	✅	✅	✅	✅	❌	❌	✅	5
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning	❌	✅	✅	❌	❌	✅	✅	4
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests	✅	✅	✅	❌	✅	✅	✅	6
Adversarial Attacks on Gaussian Process Bandits	❌	✅	✅	❌	❌	✅	✅	4
Adversarial Masking for Self-Supervised Learning	❌	❌	✅	❌	❌	❌	✅	2
Adversarial Robustness against Multiple and Single $l_p$-Threat Models via Quick Fine-Tuning of Robust Classifiers	❌	✅	✅	❌	✅	❌	✅	4
Adversarial Vulnerability of Randomized Ensembles	✅	✅	✅	❌	✅	❌	✅	5
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization	❌	❌	✅	❌	❌	❌	✅	2
Adversarially Trained Actor Critic for Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Adversarially trained neural representations are already as robust as biological neural representations	❌	❌	✅	❌	❌	❌	✅	2
Agnostic Learnability of Halfspaces via Logistic Loss	❌	❌	❌	❌	❌	❌	❌	0
Algorithms for the Communication of Samples	✅	❌	❌	❌	❌	❌	✅	2
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution	❌	✅	✅	❌	✅	✅	✅	5
An Analytical Update Rule for General Policy Optimization	❌	❌	❌	❌	❌	❌	❌	0
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings	❌	✅	❌	❌	❌	❌	✅	2
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks	❌	✅	✅	❌	❌	❌	✅	3
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming	✅	✅	✅	❌	❌	❌	✅	4
An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn	❌	❌	✅	❌	❌	❌	✅	2
An Intriguing Property of Geophysics Inversion	❌	❌	✅	✅	✅	❌	✅	4
An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees	✅	✅	✅	❌	❌	❌	✅	4
Analysis of Stochastic Processes through Replay Buffers	✅	❌	❌	❌	❌	❌	❌	1
Analyzing and Mitigating Interference in Neural Architecture Search	❌	❌	✅	✅	✅	❌	✅	4
Anarchic Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Antibody-Antigen Docking and Design via Hierarchical Structure Refinement	❌	✅	✅	❌	❌	❌	✅	3
Anticorrelated Noise Injection for Improved Generalization	❌	❌	✅	❌	❌	❌	✅	2
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology	❌	✅	✅	✅	✅	❌	✅	5
Anytime Information Cascade Popularity Prediction via Self-Exciting Processes	❌	✅	✅	✅	✅	✅	❌	5
Approximate Bayesian Computation with Domain Expert in the Loop	✅	✅	❌	❌	❌	❌	✅	3
Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets	✅	✅	✅	❌	❌	✅	✅	5
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics	❌	✅	✅	❌	❌	❌	✅	3
Architecture Agnostic Federated Learning for Neural Networks	✅	❌	✅	✅	❌	❌	✅	4
Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language	❌	✅	✅	✅	✅	❌	✅	5
Asymptotically-Optimal Gaussian Bandits with Side Observations	✅	❌	❌	❌	❌	❌	❌	1
Attentional Meta-learners for Few-shot Polythetic Classification	✅	✅	✅	✅	❌	❌	✅	5
Augment with Care: Contrastive Learning for Combinatorial Problems	❌	✅	✅	✅	❌	❌	✅	4
AutoIP: A United Framework to Integrate Physics into Gaussian Processes	❌	❌	✅	❌	❌	✅	✅	3
AutoSNN: Towards Energy-Efficient Spiking Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Auxiliary Learning with Joint Task and Data Scheduling	✅	✅	✅	✅	❌	❌	✅	5
BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression	✅	✅	✅	✅	❌	❌	✅	5
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation	❌	✅	✅	✅	❌	❌	✅	4
BabelTower: Learning to Auto-parallelized Program Translation	❌	❌	✅	✅	✅	❌	✅	4
Balancing Discriminability and Transferability for Source-Free Domain Adaptation	✅	❌	✅	❌	❌	❌	✅	3
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration Complexity	✅	✅	✅	❌	✅	❌	✅	5
Batched Dueling Bandits	✅	❌	✅	❌	✅	❌	✅	4
Bayesian Continuous-Time Tucker Decomposition	✅	❌	✅	✅	❌	❌	✅	4
Bayesian Deep Embedding Topic Meta-Learner	✅	❌	✅	✅	❌	❌	✅	4
Bayesian Imitation Learning for End-to-End Mobile Manipulation	❌	❌	❌	❌	❌	❌	✅	1
Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense	✅	❌	✅	❌	❌	❌	✅	3
Bayesian Model Selection, the Marginal Likelihood, and Generalization	❌	❌	✅	✅	❌	❌	✅	3
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations	✅	❌	✅	✅	❌	❌	✅	4
Bayesian Nonparametrics for Offline Skill Discovery	✅	✅	✅	❌	❌	❌	✅	4
Bayesian Optimization for Distributionally Robust Chance-constrained Problem	✅	❌	❌	❌	❌	❌	✅	2
Bayesian Optimization under Stochastic Delayed Feedback	✅	✅	✅	✅	❌	❌	✅	5
Be Like Water: Adaptive Floating Point for Machine Learning	❌	❌	✅	❌	❌	❌	✅	2
Being Properly Improper	✅	✅	✅	❌	✅	❌	✅	5
Benchmarking and Analyzing Point Cloud Classification under Corruptions	❌	✅	✅	❌	❌	❌	✅	3
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint	❌	❌	✅	❌	❌	❌	✅	2
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features	✅	✅	✅	❌	❌	❌	❌	3
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity	✅	❌	✅	❌	❌	❌	❌	2
Biased Gradient Estimate with Drastic Variance Reduction for Meta Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Biological Sequence Design with GFlowNets	✅	✅	✅	✅	❌	❌	✅	5
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Bit Prioritization in Variational Autoencoders via Progressive Coding	❌	❌	✅	❌	❌	❌	✅	2
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization	✅	❌	✅	❌	❌	❌	✅	3
Black-Box Tuning for Language-Model-as-a-Service	❌	✅	✅	✅	✅	❌	✅	5
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning	✅	❌	❌	❌	✅	❌	✅	3
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness	✅	✅	✅	❌	✅	❌	✅	5
Boosting Graph Structure Learning with Dummy Nodes	✅	✅	✅	✅	✅	✅	✅	7
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization	✅	✅	✅	❌	❌	❌	✅	4
Bounding Training Data Reconstruction in Private (Deep) Learning	✅	✅	✅	❌	❌	❌	✅	4
Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis	❌	❌	❌	❌	❌	❌	❌	0
Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding	❌	✅	✅	✅	✅	❌	✅	5
Branching Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities	❌	✅	✅	✅	✅	❌	✅	5
Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits	✅	❌	❌	❌	❌	❌	❌	1
Bregman Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Bregman Power k-Means for Clustering Exponential Family Data	✅	✅	✅	❌	❌	❌	✅	4
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes	✅	✅	✅	❌	❌	❌	✅	4
Building Robust Ensembles via Margin Boosting	✅	✅	✅	❌	✅	❌	✅	5
Burst-Dependent Plasticity and Dendritic Amplification Support Target-Based Learning and Hierarchical Imitation Learning	❌	✅	❌	❌	❌	❌	✅	2
ButterflyFlow: Building Invertible Layers with Butterfly Matrices	❌	❌	✅	❌	✅	❌	✅	3
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums	✅	✅	✅	❌	❌	❌	✅	4
C-algebra Net: A New Approach Generalizing Neural Network Parameters to C-algebra	❌	✅	✅	❌	❌	❌	✅	3
C-MinHash: Improving Minwise Hashing with Circulant Permutation	✅	❌	✅	❌	❌	❌	✅	3
CITRIS: Causal Identifiability from Temporal Intervened Sequences	❌	✅	✅	❌	✅	❌	✅	4
COAT: Measuring Object Compositionality in Emergent Representations	❌	❌	✅	❌	❌	❌	✅	2
COLA: Consistent Learning with Opponent-Learning Awareness	❌	❌	❌	❌	❌	❌	✅	1
Calibrated Learning to Defer with One-vs-All Classifiers	❌	✅	✅	✅	❌	❌	✅	4
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation	✅	❌	✅	✅	❌	❌	✅	4
Cascaded Gaps: Towards Logarithmic Regret for Risk-Sensitive Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Causal Conceptions of Fairness and their Consequences	✅	✅	❌	❌	❌	❌	✅	3
Causal Dynamics Learning for Task-Independent State Abstraction	❌	❌	❌	✅	❌	❌	✅	2
Causal Imitation Learning under Temporally Correlated Noise	✅	✅	✅	❌	❌	❌	✅	4
Causal Inference Through the Structural Causal Marginal Problem	❌	✅	❌	❌	❌	✅	✅	3
Causal Transformer for Estimating Counterfactual Outcomes	✅	✅	✅	✅	✅	❌	✅	6
Causal structure-based root cause analysis of outliers	❌	✅	✅	❌	❌	❌	✅	3
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference	✅	✅	✅	✅	❌	❌	✅	5
CerDEQ: Certifiable Deep Equilibrium Model	❌	❌	✅	❌	✅	❌	✅	3
Certified Adversarial Robustness Under the Bounded Support Set	✅	❌	✅	❌	✅	❌	✅	4
Certified Neural Network Watermarks with Randomized Smoothing	✅	❌	✅	❌	❌	❌	✅	3
Certified Robustness Against Natural Language Attacks by Causal Intervention	✅	✅	✅	❌	✅	❌	✅	5
Certifying Out-of-Domain Generalization for Blackbox Functions	❌	✅	✅	❌	❌	❌	❌	2
Channel Importance Matters in Few-Shot Image Classification	❌	❌	✅	✅	❌	❌	✅	3
Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Choosing Answers in Epsilon-Best-Answer Identification for Linear Bandits	✅	✅	❌	❌	❌	✅	✅	4
Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding	✅	✅	✅	❌	✅	❌	✅	5
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments	❌	✅	✅	❌	❌	❌	✅	3
Closed-Form Diffeomorphic Transformations for Time Series Alignment	❌	✅	✅	✅	✅	❌	✅	5
Co-training Improves Prompt-based Learning for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets	✅	✅	✅	✅	✅	✅	✅	7
Coin Flipping Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs	❌	❌	✅	✅	✅	✅	✅	5
Combining Diverse Feature Priors	✅	✅	✅	✅	✅	❌	✅	6
Communicating via Markov Decision Processes	✅	✅	✅	❌	❌	✅	✅	5
Communication-Efficient Adaptive Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Communication-efficient Distributed Learning for Large Batch Optimization	✅	❌	✅	❌	✅	❌	✅	4
Composing Partial Differential Equations with Physics-Aware Neural Networks	❌	✅	❌	✅	✅	❌	✅	4
Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning	❌	✅	✅	✅	❌	❌	✅	4
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data	✅	✅	✅	❌	✅	❌	✅	5
Conditional GANs with Auxiliary Discriminative Classifier	❌	✅	✅	❌	❌	❌	✅	3
Confidence Score for Source-Free Unsupervised Domain Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Conformal Prediction Sets with Limited False Positives	✅	✅	✅	✅	❌	❌	✅	5
Congested Bandits: Optimal Routing via Short-term Resets	✅	❌	❌	❌	❌	❌	✅	2
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation	❌	❌	✅	❌	❌	❌	✅	2
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures	❌	❌	❌	❌	✅	❌	✅	2
Consistent Polyhedral Surrogates for Top-k Classification and Variants	❌	❌	❌	❌	❌	❌	✅	1
Constants Matter: The Performance Gains of Active Learning	✅	❌	❌	❌	❌	❌	✅	2
Constrained Discrete Black-Box Optimization using Mixed-Integer Programming	✅	❌	✅	✅	✅	✅	✅	6
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks	✅	❌	✅	❌	✅	❌	✅	4
Constrained Offline Policy Optimization	✅	❌	❌	❌	❌	❌	❌	1
Constrained Optimization with Dynamic Bound-scaling for Effective NLP Backdoor Defense	✅	✅	✅	❌	✅	❌	✅	5
Constrained Variational Policy Optimization for Safe Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Constraint-based graph network simulator	✅	❌	✅	✅	❌	❌	✅	4
Content Addressable Memory Without Catastrophic Forgetting by Heteroassociation with a Fixed Scaffold	❌	✅	✅	❌	❌	❌	✅	3
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers	❌	✅	✅	✅	❌	❌	✅	4
Context-Aware Drift Detection	✅	✅	✅	✅	❌	❌	✅	5
Contextual Bandits with Large Action Spaces: Made Practical	✅	✅	✅	❌	✅	❌	❌	4
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces	✅	✅	✅	❌	❌	❌	❌	3
Contextual Information-Directed Sampling	❌	❌	❌	❌	❌	❌	✅	1
Continual Learning via Sequential Function-Space Variational Inference	❌	✅	✅	✅	❌	❌	✅	4
Continual Learning with Guarantees via Weight Interval Constraints	✅	✅	✅	✅	❌	❌	✅	5
Continual Repeated Annealed Flow Transport Monte Carlo	✅	✅	✅	✅	✅	❌	✅	6
Continuous Control with Action Quantization from Demonstrations	❌	✅	✅	❌	❌	❌	✅	3
Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems	❌	❌	❌	❌	❌	❌	❌	0
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations	❌	✅	✅	✅	✅	❌	✅	5
Contrastive Learning with Boosted Memorization	✅	✅	✅	✅	❌	❌	✅	5
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness	❌	✅	✅	✅	✅	✅	✅	6
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Controlling Conditional Language Models without Catastrophic Forgetting	✅	✅	✅	❌	✅	❌	✅	5
Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness	✅	❌	✅	❌	❌	❌	✅	3
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering	✅	✅	✅	❌	❌	✅	✅	5
Convergence of Invariant Graph Networks	❌	❌	❌	❌	❌	❌	✅	1
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime	❌	❌	❌	❌	❌	❌	❌	0
Convergence of Uncertainty Sampling for Active Learning	✅	❌	✅	❌	❌	❌	❌	2
Convolutional and Residual Networks Provably Contain Lottery Tickets	✅	✅	✅	❌	✅	❌	✅	5
Cooperative Online Learning in Stochastic and Adversarial MDPs	✅	❌	❌	❌	❌	❌	❌	1
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms	✅	❌	❌	❌	❌	❌	✅	2
Coordinated Double Machine Learning	✅	✅	✅	✅	❌	❌	✅	5
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations	✅	✅	✅	✅	✅	❌	✅	6
Correlated Quantization for Distributed Mean Estimation and Optimization	✅	✅	✅	❌	❌	❌	✅	4
Correlation Clustering via Strong Triadic Closure Labeling: Fast Approximation Algorithms and Practical Lower Bounds	✅	✅	✅	❌	✅	❌	✅	5
Counterfactual Prediction for Outcome-Oriented Treatments	✅	❌	✅	❌	❌	❌	✅	3
Counterfactual Transportability: A Formal Approach	✅	❌	❌	❌	❌	❌	❌	1
Cross-Space Active Learning on Graph Convolutional Networks	✅	❌	❌	❌	❌	❌	❌	1
CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer	✅	✅	✅	❌	✅	❌	✅	5
Curriculum Reinforcement Learning via Constrained Optimal Transport	✅	✅	❌	❌	✅	✅	✅	5
Cycle Representation Learning for Inductive Relation Prediction	❌	✅	✅	✅	✅	❌	✅	5
DAVINZ: Data Valuation using Deep Neural Networks at Initialization	✅	❌	✅	✅	✅	❌	✅	5
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
DNA: Domain Generalization with Diversified Neural Averaging	✅	✅	✅	✅	✅	✅	✅	7
DNNR: Differential Nearest Neighbors Regression	✅	✅	✅	✅	✅	❌	✅	6
DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks	✅	❌	✅	❌	✅	✅	✅	5
DRIBO: Robust Deep Reinforcement Learning via Multi-View Information Bottleneck	✅	✅	✅	✅	✅	✅	✅	7
DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting	❌	✅	✅	✅	✅	❌	✅	5
Data Augmentation as Feature Manipulation	❌	❌	✅	❌	❌	❌	✅	2
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)	❌	❌	✅	❌	❌	❌	✅	2
Data Scaling Laws in NMT: The Effect of Noise and Architecture	❌	❌	✅	❌	✅	❌	✅	3
Data-Efficient Double-Win Lottery Tickets from Robust Pre-training	❌	✅	✅	❌	❌	❌	✅	3
Data-SUITE: Data-centric identification of in-distribution incongruous examples	✅	✅	✅	✅	✅	❌	✅	6
Datamodels: Understanding Predictions with Data and Data with Predictions	❌	❌	✅	✅	✅	❌	✅	4
Dataset Condensation via Efficient Synthetic-Data Parameterization	✅	✅	✅	❌	✅	❌	✅	5
Dataset Condensation with Contrastive Signals	✅	✅	✅	❌	❌	❌	✅	4
De novo mass spectrometry peptide sequencing with a transformer model	❌	✅	✅	✅	✅	❌	✅	5
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps	❌	✅	✅	✅	❌	❌	✅	4
Decentralized Online Convex Optimization in Networked Systems	✅	❌	❌	❌	❌	❌	❌	1
Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm	✅	✅	✅	✅	❌	❌	✅	5
Decision-Focused Learning: Through the Lens of Learning to Rank	✅	✅	✅	✅	❌	❌	✅	5
Decomposing Temporal High-Order Interactions via Latent ODEs	✅	❌	✅	❌	❌	❌	✅	3
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Deduplicating Training Data Mitigates Privacy Risks in Language Models	❌	✅	✅	❌	❌	❌	❌	2
Deep Causal Metric Learning	✅	✅	✅	✅	❌	❌	✅	5
Deep Hierarchy in Bandits	✅	❌	✅	❌	❌	❌	✅	3
Deep Network Approximation in Terms of Intrinsic Parameters	❌	❌	✅	❌	❌	❌	✅	2
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry	✅	✅	✅	❌	❌	✅	✅	5
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Deep Probability Estimation	✅	✅	✅	✅	❌	❌	❌	4
Deep Reference Priors: What is the best way to pretrain a model?	✅	✅	✅	❌	❌	❌	✅	4
Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm	✅	❌	✅	❌	❌	❌	✅	3
Deep Squared Euclidean Approximation to the Levenshtein Distance for DNA Storage	❌	❌	✅	❌	❌	❌	✅	2
Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection	✅	✅	✅	✅	✅	❌	✅	6
Deep and Flexible Graph Neural Architecture Search	✅	✅	✅	✅	✅	✅	✅	7
Deep equilibrium networks are sensitive to initialization statistics	❌	❌	✅	❌	✅	❌	✅	3
Deep symbolic regression for recurrence prediction	❌	❌	✅	✅	✅	❌	✅	4
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale	❌	✅	✅	✅	✅	❌	✅	5
Delay-Adaptive Step-sizes for Asynchronous Learning	✅	❌	✅	❌	❌	❌	✅	3
Delayed Reinforcement Learning by Imitation	✅	❌	✅	✅	❌	❌	✅	4
Deletion Robust Submodular Maximization over Matroids	✅	❌	✅	❌	❌	❌	✅	3
Demystifying the Adversarial Robustness of Random Transformation Defenses	✅	✅	✅	✅	✅	❌	✅	6
Denoised MDPs: Learning World Models Better Than the World Itself	✅	✅	✅	✅	✅	❌	✅	6
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations	✅	✅	✅	✅	❌	❌	✅	5
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Describing Differences between Text Distributions with Natural Language	❌	✅	✅	❌	❌	❌	✅	3
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization	❌	✅	✅	✅	✅	❌	✅	5
Detached Error Feedback for Distributed SGD with Random Sparsification	✅	❌	✅	✅	✅	❌	✅	5
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them	❌	❌	✅	❌	❌	❌	❌	1
Detecting Corrupted Labels Without Training a Model to Predict	✅	✅	✅	❌	❌	❌	✅	4
Dialog Inpainting: Turning Documents into Dialogs	❌	❌	✅	✅	✅	❌	✅	4
Difference Advantage Estimation for Multi-Agent Policy Gradients	✅	❌	✅	❌	❌	❌	✅	3
Differentiable Top-k Classification Learning	❌	✅	✅	❌	❌	❌	✅	3
Differentially Private Approximate Quantiles	✅	✅	✅	❌	✅	❌	✅	5
Differentially Private Community Detection for Stochastic Block Models	✅	❌	✅	❌	❌	✅	✅	4
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization	✅	✅	✅	❌	✅	❌	✅	5
Differentially Private Maximal Information Coefficients	❌	✅	✅	❌	❌	❌	✅	3
Diffusion Models for Adversarial Purification	❌	❌	✅	✅	✅	❌	✅	4
Diffusion bridges vector quantized variational autoencoders	✅	❌	✅	❌	✅	❌	✅	4
Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization	✅	❌	❌	❌	❌	❌	❌	1
Direct Behavior Specification via Constrained Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Directed Acyclic Transformer for Non-Autoregressive Machine Translation	✅	✅	✅	✅	✅	❌	✅	6
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training	✅	✅	✅	❌	❌	❌	✅	4
Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning	✅	✅	❌	❌	❌	❌	✅	3
Discrete Probabilistic Inverse Optimal Transport	✅	❌	✅	❌	❌	✅	✅	4
Discrete Tree Flows via Tree-Structured Permutations	✅	❌	✅	✅	✅	❌	✅	5
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations	✅	✅	✅	✅	✅	❌	✅	6
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring	✅	❌	✅	❌	❌	❌	✅	3
Disentangling Disease-related Representation from Obscure for Disease Prediction	❌	❌	✅	✅	❌	❌	✅	3
Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning	✅	❌	✅	❌	✅	✅	✅	5
Distinguishing rule and exemplar-based generalization in learning systems	❌	✅	✅	✅	❌	❌	✅	4
Distribution Regression with Sliced Wasserstein Kernels	✅	✅	✅	✅	❌	❌	✅	5
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Distributionally Robust $Q$-Learning	✅	❌	❌	❌	❌	❌	✅	2
Distributionally-Aware Kernelized Bandit Problems for Risk Aversion	✅	✅	❌	✅	✅	❌	✅	5
Divergence-Regularized Multi-Agent Actor-Critic	✅	❌	✅	❌	✅	❌	✅	4
Diversified Adversarial Attacks based on Conjugate Gradient Method	✅	✅	✅	✅	✅	❌	✅	6
Do Differentiable Simulators Give Better Policy Gradients?	❌	❌	❌	❌	❌	❌	✅	1
Do More Negative Samples Necessarily Hurt In Contrastive Learning?	❌	❌	✅	❌	❌	❌	✅	2
Does the Data Induce Capacity Control in Deep Learning?	❌	✅	✅	✅	❌	❌	✅	4
Domain Adaptation for Time Series Forecasting via Attention Sharing	✅	❌	✅	✅	❌	❌	✅	4
Double Sampling Randomized Smoothing	✅	✅	✅	❌	❌	❌	✅	4
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning	✅	✅	❌	✅	❌	❌	✅	4
DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations	❌	✅	✅	❌	✅	❌	✅	4
Dual Decomposition of Convex Optimization Layers for Consistent Attention in Medical Images	❌	✅	✅	✅	✅	❌	✅	5
Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification	❌	✅	✅	✅	❌	❌	✅	4
DynaMixer: A Vision MLP Architecture with Dynamic Mixing	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Regret of Online Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Dynamic Topic Models for Temporal Document Networks	✅	❌	✅	✅	✅	❌	✅	5
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning	❌	✅	✅	❌	✅	✅	✅	5
Easy Variational Inference for Categorical Models via an Independent Binary Approximation	✅	✅	✅	❌	❌	❌	✅	4
Efficient Approximate Inference for Stationary Kernel on Frequency Domain	✅	✅	✅	✅	✅	✅	✅	7
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing	✅	✅	✅	❌	✅	❌	✅	5
Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity	✅	✅	✅	❌	❌	❌	✅	4
Efficient Learning for AlphaZero via Path Consistency	✅	✅	✅	❌	✅	❌	✅	5
Efficient Learning of CNNs using Patch Based Features	✅	✅	✅	❌	❌	❌	✅	4
Efficient Low Rank Convex Bounds for Pairwise Discrete Graphical Models	❌	✅	✅	❌	✅	✅	✅	5
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation	✅	❌	❌	❌	❌	❌	✅	2
Efficient Online ML API Selection for Multi-Label Classification Tasks	✅	✅	✅	✅	✅	❌	✅	6
Efficient PAC Learning from the Crowd with Pairwise Comparisons	✅	❌	❌	❌	❌	❌	❌	1
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach	✅	✅	❌	❌	❌	❌	✅	3
Efficient Representation Learning via Adaptive Context Pooling	❌	❌	✅	✅	✅	❌	✅	4
Efficient Test-Time Model Adaptation without Forgetting	✅	✅	✅	✅	✅	❌	✅	6
Efficient Variance Reduction for Meta-learning	✅	❌	✅	❌	❌	❌	✅	3
Efficiently Learning the Topology and Behavior of a Networked Dynamical System Via Active Queries	✅	✅	✅	❌	✅	❌	✅	5
End-to-End Balancing for Causal Continuous Treatment-Effect Estimation	✅	❌	✅	✅	✅	❌	✅	5
Entropic Causal Inference: Graph Identifiability	✅	❌	✅	❌	❌	❌	✅	3
Entropic Gromov-Wasserstein between Gaussian Distributions	❌	✅	❌	❌	❌	❌	✅	2
EqR: Equivariant Representations for Data-Efficient Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction	❌	✅	✅	✅	✅	❌	✅	5
Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent	✅	❌	✅	❌	❌	❌	✅	3
Equivariance versus Augmentation for Spherical Images	❌	✅	✅	✅	✅	❌	✅	5
Equivariant Diffusion for Molecule Generation in 3D	✅	❌	✅	✅	✅	❌	✅	5
Equivariant Priors for compressed sensing with unknown orientation	✅	❌	✅	✅	❌	❌	✅	4
Equivariant Quantum Graph Circuits	❌	❌	❌	❌	❌	❌	✅	1
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass	✅	✅	✅	✅	❌	❌	✅	5
Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network	✅	❌	✅	✅	✅	✅	✅	6
Estimating and Penalizing Induced Preference Shifts in Recommender Systems	✅	❌	❌	✅	✅	✅	✅	5
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models	✅	✅	✅	❌	✅	❌	✅	5
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing	❌	❌	❌	❌	❌	❌	✅	1
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses	❌	✅	✅	❌	✅	❌	✅	4
Evolving Curricula with Regret-Based Environment Design	✅	✅	✅	✅	✅	❌	✅	6
Exact Learning of Preference Structure: Single-peaked Preferences and Beyond	❌	❌	❌	❌	❌	❌	✅	1
Exact Optimal Accelerated Complexity for Fixed-Point Iterations	❌	❌	❌	❌	❌	❌	✅	1
Examining Scaling and Transfer of Language Model Architectures for Machine Translation	❌	❌	✅	✅	❌	❌	✅	3
Exploiting Independent Instruments: Identification and Distribution Generalization	✅	✅	✅	❌	❌	❌	✅	4
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups	❌	✅	✅	✅	✅	❌	✅	5
Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling	✅	✅	✅	❌	✅	❌	✅	5
Exploring the Gap between Collapsed & Whitened Features in Self-Supervised Learning	✅	❌	✅	✅	❌	❌	✅	4
Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control	✅	✅	✅	❌	❌	❌	✅	4
Extended Unconstrained Features Model for Exploring Deep Neural Collapse	❌	❌	✅	❌	❌	❌	✅	2
Extracting Latent State Representations with Linear Dynamics from Rich Observations	❌	❌	✅	❌	❌	❌	✅	2
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting	❌	✅	✅	✅	✅	✅	✅	6
FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers	✅	❌	✅	❌	❌	❌	✅	3
FOCUS: Familiar Objects in Common and Uncommon Settings	❌	✅	✅	❌	❌	❌	✅	3
Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data	❌	❌	✅	❌	❌	❌	✅	2
Fair Generalized Linear Models with a Convex Penalty	✅	✅	✅	❌	❌	❌	✅	4
Fair Representation Learning through Implicit Path Alignment	✅	❌	✅	✅	❌	❌	✅	4
Fair and Fast k-Center Clustering for Data Summarization	✅	❌	✅	❌	✅	✅	✅	5
Fairness Interventions as (Dis)Incentives for Strategic Manipulation	❌	❌	✅	❌	❌	❌	✅	2
Fairness with Adaptive Weights	✅	❌	✅	✅	❌	❌	❌	3
Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models	❌	❌	❌	❌	❌	❌	✅	1
Fast Composite Optimization and Statistical Recovery in Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions	✅	✅	✅	✅	✅	✅	✅	7
Fast Finite Width Neural Tangent Kernel	❌	✅	✅	❌	✅	✅	✅	5
Fast Lossless Neural Compression with Integer-Only Discrete Flows	✅	✅	✅	❌	✅	✅	✅	6
Fast Population-Based Reinforcement Learning on a Single Machine	✅	✅	✅	❌	✅	❌	✅	5
Fast Provably Robust Decision Trees and Boosting	✅	❌	✅	✅	✅	❌	✅	5
Fast Relative Entropy Coding with A* coding	✅	✅	✅	❌	❌	❌	✅	4
Fast and Provable Nonconvex Tensor RPCA	✅	❌	✅	❌	✅	✅	✅	5
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack	✅	✅	✅	❌	✅	✅	✅	6
Fast rates for noisy interpolation require rethinking the effect of inductive bias	❌	✅	✅	❌	❌	❌	✅	3
Fast-Rate PAC-Bayesian Generalization Bounds for Meta-Learning	✅	❌	✅	❌	❌	❌	✅	3
Faster Algorithms for Learning Convex Functions	✅	✅	✅	✅	✅	✅	✅	7
Faster Fundamental Graph Algorithms via Learned Predictions	✅	❌	✅	❌	❌	❌	✅	3
Faster Privacy Accounting via Evolving Discretization	✅	❌	❌	❌	❌	❌	✅	2
Fat–Tailed Variational Inference with Anisotropic Tail Adaptive Flows	❌	✅	✅	❌	✅	✅	✅	5
Feature Learning and Signal Propagation in Deep Neural Networks	✅	❌	✅	✅	❌	❌	✅	4
Feature Space Particle Inference for Neural Network Ensembles	✅	✅	✅	❌	✅	❌	✅	5
Feature and Parameter Selection in Stochastic Linear Bandits	✅	❌	✅	❌	❌	❌	✅	3
Feature selection using e-values	✅	✅	✅	✅	✅	❌	✅	6
FedNL: Making Newton-Type Methods Applicable to Federated Learning	✅	❌	✅	❌	❌	❌	✅	3
FedNest: Federated Bilevel, Minimax, and Compositional Optimization	✅	✅	✅	✅	❌	❌	✅	5
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale	✅	✅	✅	✅	✅	✅	✅	7
Federated Learning with Label Distribution Skew via Logits Calibration	✅	❌	✅	❌	✅	❌	✅	4
Federated Learning with Partial Model Personalization	✅	✅	✅	✅	❌	❌	✅	5
Federated Learning with Positive and Unlabeled Data	✅	❌	✅	❌	❌	❌	✅	3
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms	✅	❌	✅	❌	✅	✅	✅	5
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling	✅	❌	❌	❌	❌	❌	❌	1
Fenrir: Physics-Enhanced Regression for Initial Value Problems	❌	✅	✅	❌	❌	❌	✅	3
Fictitious Play and Best-Response Dynamics in Identical Interest and Zero-Sum Stochastic Games	✅	❌	❌	❌	❌	❌	❌	1
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming	❌	❌	✅	✅	❌	❌	✅	3
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily	✅	✅	✅	✅	✅	❌	✅	6
Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications	✅	❌	✅	✅	✅	❌	✅	5
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach	✅	❌	❌	❌	❌	❌	❌	1
Fisher SAM: Information Geometry and Sharpness Aware Minimisation	✅	❌	✅	❌	✅	❌	✅	4
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification	✅	✅	✅	✅	✅	❌	✅	6
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization	✅	✅	✅	✅	✅	❌	✅	6
Flashlight: Enabling Innovation in Tools for Machine Learning	✅	✅	✅	✅	✅	✅	✅	7
Flow-Guided Sparse Transformer for Video Deblurring	❌	✅	✅	❌	✅	❌	✅	4
Flow-based Recurrent Belief State Learning for POMDPs	✅	❌	✅	❌	❌	❌	✅	3
Flowformer: Linearizing Transformers with Conservation Flows	✅	✅	✅	❌	✅	❌	✅	5
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension	❌	❌	❌	❌	❌	❌	✅	1
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria	❌	✅	✅	❌	✅	❌	✅	4
Forget-free Continual Learning with Winning Subnetworks	✅	✅	✅	✅	✅	❌	✅	6
Forward Operator Estimation in Generative Models with Kernel Transfer Operators	✅	✅	✅	❌	✅	❌	✅	5
Fourier Learning with Cyclical Data	✅	✅	✅	❌	❌	❌	✅	4
Framework for Evaluating Faithfulness of Local Explanations	✅	❌	✅	✅	❌	❌	✅	4
FriendlyCore: Practical Differentially Private Aggregation	✅	❌	✅	❌	✅	❌	✅	4
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses	✅	❌	✅	❌	❌	❌	✅	3
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model	✅	✅	✅	✅	❌	❌	✅	5
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers	✅	✅	✅	✅	✅	❌	✅	6
From data to functa: Your data point is a function and you can treat it like one	✅	❌	✅	❌	❌	❌	✅	3
Frustratingly Easy Transferability Estimation	✅	✅	✅	❌	✅	❌	✅	5
Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis	❌	❌	❌	❌	❌	❌	❌	0
Function-space Inference with Sparse Implicit Processes	❌	✅	✅	✅	✅	❌	✅	5
Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions	✅	✅	❌	✅	❌	❌	✅	4
Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses	✅	✅	✅	❌	❌	❌	✅	4
G$^2$CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters	❌	❌	✅	✅	✅	❌	✅	4
G-Mixup: Graph Data Augmentation for Graph Classification	✅	✅	✅	✅	❌	❌	✅	5
GACT: Activation Compressed Training for Generic Network Architectures	✅	❌	✅	❌	✅	✅	✅	5
GALAXY: Graph-based Active Learning at the Extreme	✅	✅	✅	❌	❌	❌	✅	4
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts	❌	❌	✅	✅	✅	❌	✅	4
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing	❌	❌	✅	❌	✅	❌	✅	3
Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers	❌	✅	✅	✅	✅	❌	✅	5
Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification	❌	✅	✅	✅	✅	❌	✅	5
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications	❌	✅	✅	❌	✅	❌	✅	4
GenLabel: Mixup Relabeling using Generative Models	✅	✅	✅	✅	✅	❌	✅	6
General-purpose, long-context autoregressive modeling with Perceiver AR	❌	✅	✅	✅	✅	❌	✅	5
Generalised Policy Improvement with Geometric Policy Composition	✅	❌	❌	❌	❌	❌	✅	2
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers	✅	❌	✅	❌	✅	❌	✅	4
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling	✅	❌	❌	❌	❌	❌	✅	2
Generalization and Robustness Implications in Object-Centric Learning	❌	✅	✅	✅	✅	❌	✅	5
Generalized Beliefs for Cooperative AI	❌	✅	✅	❌	✅	❌	✅	4
Generalized Data Distribution Iteration	✅	❌	✅	❌	✅	❌	✅	4
Generalized Federated Learning via Sharpness Aware Minimization	✅	❌	✅	✅	✅	❌	✅	5
Generalized Leverage Scores: Geometric Interpretation and Applications	✅	❌	✅	❌	❌	❌	✅	3
Generalized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce Model	❌	✅	❌	❌	❌	❌	✅	2
Generalized Strategic Classification and the Case of Aligned Incentives	✅	✅	✅	❌	❌	❌	✅	4
Generalizing Gaussian Smoothing for Random Search	❌	❌	✅	❌	✅	❌	✅	3
Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder	✅	❌	✅	✅	❌	❌	✅	4
Generalizing to New Physical Systems via Context-Informed Dynamics Model	✅	✅	✅	❌	✅	✅	✅	6
Generating 3D Molecules for Target Protein Binding	❌	✅	✅	❌	❌	❌	❌	2
Generating Distributional Adversarial Examples to Evade Statistical Detectors	❌	❌	✅	❌	❌	❌	✅	2
Generative Coarse-Graining of Molecular Conformations	❌	✅	✅	✅	❌	❌	✅	4
Generative Cooperative Networks for Natural Language Generation	✅	❌	✅	❌	✅	❌	✅	4
Generative Flow Networks for Discrete Probabilistic Modeling	✅	✅	✅	✅	❌	❌	✅	5
Generative Modeling for Multi-task Visual Learning	✅	✅	✅	✅	❌	❌	✅	5
Generative Trees: Adversarial and Copycat	✅	❌	✅	✅	✅	✅	✅	6
Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more	✅	✅	✅	❌	❌	❌	✅	4
Geometric Multimodal Contrastive Representation Learning	❌	✅	✅	❌	❌	❌	✅	3
Global Optimization Networks	❌	✅	✅	✅	❌	❌	✅	4
Global Optimization of K-Center Clustering	✅	✅	✅	❌	❌	✅	✅	5
Goal Misgeneralization in Deep Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Going Deeper into Permutation-Sensitive Graph Neural Networks	❌	✅	✅	✅	✅	✅	✅	6
Gradient Based Clustering	❌	❌	✅	❌	❌	❌	✅	2
Gradient Descent on Neurons and its Link to Approximate Second-order Optimization	✅	✅	✅	❌	❌	❌	✅	4
Gradient-Free Method for Heavily Constrained Nonconvex Optimization	✅	❌	❌	✅	✅	❌	✅	4
Graph Neural Architecture Search Under Distribution Shifts	✅	❌	✅	✅	✅	❌	✅	5
Graph-Coupled Oscillator Networks	❌	✅	✅	✅	✅	❌	✅	5
GraphFM: Improving Large-Scale GNN Training via Feature Momentum	✅	✅	✅	✅	✅	❌	✅	6
Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Greedy when Sure and Conservative when Uncertain about the Opponents	✅	✅	✅	❌	❌	❌	✅	4
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance	✅	❌	✅	✅	✅	❌	✅	5
H-Consistency Bounds for Surrogate Loss Minimizers	❌	❌	❌	❌	❌	❌	❌	0
Hardness and Algorithms for Robust and Sparse Optimization	✅	❌	❌	❌	❌	❌	❌	1
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning	❌	✅	✅	✅	❌	❌	✅	4
Hermite Polynomial Features for Private Data Generation	❌	✅	✅	❌	✅	✅	✅	5
Hessian-Free High-Resolution Nesterov Acceleration For Sampling	✅	❌	✅	❌	❌	❌	✅	3
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models.	❌	✅	✅	✅	❌	❌	✅	4
High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails	✅	❌	❌	❌	❌	❌	❌	1
Hindering Adversarial Attacks with Implicit Neural Representations	✅	❌	✅	❌	❌	❌	✅	3
History Compression via Language Models in Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
HousE: Knowledge Graph Embedding with Householder Parameterization	✅	✅	✅	✅	❌	❌	✅	5
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models	❌	✅	✅	✅	❌	❌	✅	4
How Powerful are Spectral Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
How Tempering Fixes Data Augmentation in Bayesian Neural Networks	❌	❌	✅	❌	✅	❌	✅	3
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity	✅	❌	✅	❌	✅	❌	✅	4
How to Leverage Unlabeled Data in Offline Reinforcement Learning	❌	❌	✅	❌	✅	❌	✅	3
How to Stay Curious while avoiding Noisy TVs using Aleatoric Uncertainty Estimation	❌	✅	✅	❌	✅	❌	✅	4
How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection	✅	✅	✅	❌	✅	❌	✅	5
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective	✅	✅	✅	✅	✅	❌	✅	6
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
HyperImpute: Generalized Iterative Imputation with Automatic Model Selection	✅	✅	✅	❌	✅	❌	✅	5
HyperPrompt: Prompt-based Task-Conditioning of Transformers	❌	❌	✅	✅	❌	❌	✅	3
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning	❌	✅	✅	❌	❌	❌	✅	3
IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data	❌	❌	✅	✅	✅	❌	✅	4
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages	❌	✅	✅	✅	✅	❌	✅	5
Identifiability Conditions for Domain Adaptation	✅	❌	✅	✅	❌	❌	✅	4
Identification of Linear Non-Gaussian Latent Hierarchical Structure	✅	✅	✅	❌	❌	❌	❌	3
Identity-Disentangled Adversarial Augmentation for Self-supervised Learning	❌	✅	✅	✅	✅	✅	✅	6
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging	✅	✅	✅	✅	❌	❌	✅	5
Imitation Learning by Estimating Expertise of Demonstrators	❌	✅	✅	❌	✅	❌	✅	4
Implicit Bias of Linear Equivariant Networks	❌	✅	✅	❌	❌	❌	✅	3
Implicit Bias of the Step Size in Linear Diagonal Neural Networks	❌	❌	❌	❌	❌	❌	✅	1
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization	❌	❌	✅	✅	❌	❌	✅	3
Importance Weighted Kernel Bayes’ Rule	✅	❌	✅	✅	❌	❌	✅	4
Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters	❌	❌	❌	❌	❌	❌	✅	1
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation	❌	❌	✅	❌	❌	❌	✅	2
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning	✅	❌	❌	❌	❌	❌	❌	1
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP	✅	❌	❌	❌	❌	❌	❌	1
Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data	✅	❌	❌	❌	❌	❌	❌	1
Improved Regret for Differentially Private Exploration in Linear MDP	✅	❌	❌	❌	❌	❌	❌	1
Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images	✅	✅	✅	❌	❌	❌	✅	4
Improving Adversarial Robustness via Mutual Information Estimation	✅	✅	✅	✅	❌	❌	✅	5
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation	✅	✅	✅	✅	✅	✅	✅	7
Improving Language Models by Retrieving from Trillions of Tokens	✅	❌	✅	✅	❌	❌	✅	4
Improving Mini-batch Optimal Transport via Partial Transportation	✅	✅	✅	✅	✅	❌	✅	6
Improving Out-of-Distribution Robustness via Selective Augmentation	✅	✅	✅	✅	❌	❌	✅	5
Improving Policy Optimization with Generalist-Specialist Learning	✅	❌	✅	❌	❌	❌	✅	3
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification	✅	❌	✅	❌	❌	❌	✅	3
Improving Screening Processes via Calibrated Subset Selection	✅	✅	✅	❌	❌	❌	✅	4
Improving Task-free Continual Learning by Distributionally Robust Memory Evolution	✅	❌	✅	✅	❌	❌	✅	4
Improving Transformers with Probabilistic Attention Keys	❌	✅	✅	✅	✅	❌	✅	5
In defense of dual-encoders for neural ranking	❌	❌	✅	✅	❌	❌	✅	3
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence	✅	❌	✅	❌	❌	❌	✅	3
Individual Preference Stability for Clustering	✅	✅	✅	❌	❌	❌	✅	4
Individual Reward Assisted Multi-Agent Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Inducing Causal Structure for Interpretable Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Inductive Biases and Variable Creation in Self-Attention Mechanisms	❌	❌	❌	✅	✅	❌	✅	3
Inductive Matrix Completion: No Bad Local Minima and a Fast Algorithm	✅	✅	❌	❌	❌	✅	✅	4
Inferring Cause and Effect in the Presence of Heteroscedastic Noise	✅	✅	✅	❌	✅	❌	✅	5
Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems	✅	❌	❌	❌	✅	❌	❌	2
Information Discrepancy in Strategic Learning	✅	✅	✅	❌	❌	❌	✅	4
Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity	✅	❌	❌	❌	✅	❌	✅	3
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators	❌	✅	✅	❌	✅	❌	✅	4
Input Dependent Sparse Gaussian Processes	✅	✅	✅	❌	✅	✅	✅	6
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing	❌	❌	✅	❌	✅	✅	✅	4
Instance Dependent Regret Analysis of Kernelized Bandits	✅	❌	❌	❌	❌	❌	❌	1
Instrumental Variable Regression with Confounder Balancing	✅	✅	✅	✅	✅	✅	✅	7
Interactive Correlation Clustering with Existential Cluster Constraints	✅	❌	✅	✅	❌	✅	✅	5
Interactive Inverse Reinforcement Learning for Cooperative Games	✅	✅	❌	❌	✅	✅	✅	5
Interactively Learning Preference Constraints in Linear Bandits	✅	✅	✅	❌	❌	❌	✅	4
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings	✅	✅	✅	❌	✅	✅	✅	6
Interpretable Off-Policy Learning via Hyperbox Search	✅	✅	✅	✅	✅	✅	✅	7
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism	❌	✅	✅	✅	✅	❌	✅	5
Interventional Contrastive Learning with Meta Semantic Regularizer	✅	❌	✅	✅	❌	❌	✅	4
Intriguing Properties of Input-Dependent Randomized Smoothing	✅	❌	✅	❌	❌	❌	✅	3
Invariant Ancestry Search	✅	✅	✅	❌	❌	❌	✅	4
Inverse Contextual Bandits: Learning How Behavior Evolves over Time	✅	✅	✅	❌	❌	❌	✅	4
Investigating Generalization by Controlling Normalized Margin	✅	✅	✅	❌	❌	❌	✅	4
Investigating Why Contrastive Learning Benefits Robustness against Label Noise	❌	❌	✅	❌	✅	❌	✅	3
Iterative Double Sketching for Faster Least-Squares Optimization	✅	❌	❌	❌	❌	✅	✅	3
Iterative Hard Thresholding with Adaptive Regularization: Sparser Solutions Without Sacrificing Runtime	✅	✅	✅	❌	✅	✅	✅	6
It’s Raw! Audio Generation with State-Space Models	❌	❌	✅	✅	✅	❌	✅	4
Kernel Methods for Radial Transformed Compositional Data with Many Zeros	❌	❌	✅	❌	❌	❌	✅	2
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games	✅	❌	✅	❌	❌	❌	✅	3
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots	✅	❌	✅	❌	✅	❌	✅	4
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs	❌	✅	✅	✅	❌	❌	✅	4
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations	❌	✅	✅	✅	✅	❌	✅	5
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics	❌	❌	✅	✅	✅	✅	✅	5
LCANets: Lateral Competition Improves Robustness Against Corruption and Attack	❌	❌	✅	✅	✅	✅	✅	5
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood	✅	✅	✅	❌	❌	❌	✅	4
LIMO: Latent Inceptionism for Targeted Molecule Generation	✅	✅	✅	✅	✅	✅	✅	7
LSB: Local Self-Balancing MCMC in Discrete Spaces	✅	✅	✅	❌	❌	❌	✅	4
Label Ranking through Nonparametric Regression	✅	✅	✅	✅	❌	❌	❌	4
Label-Descriptive Patterns and Their Application to Characterizing Classification Errors	✅	✅	✅	✅	✅	✅	✅	7
Label-Free Explainability for Unsupervised Models	✅	✅	✅	✅	✅	✅	✅	7
Lagrangian Method for Q-Function Learning (with Applications to Machine Translation)	✅	✅	✅	❌	✅	❌	✅	5
Langevin Monte Carlo for Contextual Bandits	✅	✅	✅	❌	✅	❌	✅	5
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents	✅	✅	✅	❌	❌	❌	✅	4
Large Batch Experience Replay	✅	✅	✅	❌	✅	❌	✅	5
Large-Scale Graph Neural Architecture Search	✅	✅	✅	✅	✅	✅	✅	7
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence	✅	✅	✅	✅	✅	❌	✅	6
Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression	✅	❌	❌	❌	❌	❌	✅	2
Latent Diffusion Energy-Based Model for Interpretable Text Modelling	✅	✅	✅	❌	❌	❌	✅	4
Latent Outlier Exposure for Anomaly Detection with Contaminated Data	✅	✅	✅	✅	❌	❌	✅	5
Lazy Estimation of Variable Importance for Large Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation	✅	✅	✅	❌	❌	❌	✅	4
Learning Augmented Binary Search Trees	❌	❌	✅	✅	❌	❌	❌	2
Learning Bellman Complete Representations for Offline Policy Evaluation	✅	✅	✅	❌	❌	❌	✅	4
Learning Domain Adaptive Object Detection with Probabilistic Teacher	✅	✅	✅	✅	❌	❌	✅	5
Learning Dynamics and Generalization in Deep Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent	✅	❌	❌	❌	❌	❌	❌	1
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints	✅	❌	❌	❌	❌	❌	✅	2
Learning Iterative Reasoning through Energy Minimization	✅	✅	❌	❌	✅	❌	✅	4
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits	✅	❌	❌	❌	❌	❌	❌	1
Learning Mixtures of Linear Dynamical Systems	✅	❌	✅	❌	❌	❌	✅	3
Learning Multiscale Transformer Models for Sequence Generation	❌	✅	✅	✅	❌	❌	✅	4
Learning Pseudometric-based Action Representations for Offline Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Learning Stable Classifiers by Transferring Unstable Features	❌	✅	✅	✅	✅	❌	✅	5
Learning Stochastic Shortest Path with Linear Function Approximation	✅	❌	❌	❌	❌	❌	✅	2
Learning Symmetric Embeddings for Equivariant World Models	❌	✅	✅	❌	✅	❌	✅	4
Learning fair representation with a parametric integral probability metric	✅	✅	✅	✅	❌	❌	✅	5
Learning from Counterfactual Links for Link Prediction	✅	✅	✅	✅	✅	✅	✅	7
Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation	✅	✅	❌	❌	❌	❌	✅	3
Learning from a Learning User for Optimal Recommendations	✅	❌	❌	❌	❌	❌	✅	2
Learning inverse folding from millions of predicted structures	❌	✅	✅	✅	✅	❌	✅	5
Learning of Cluster-based Feature Importance for Electronic Health Record Time-series	❌	✅	✅	✅	✅	❌	✅	5
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning	❌	❌	✅	✅	✅	✅	✅	5
Learning to Estimate and Refine Fluid Motion with Physical Dynamics	❌	✅	✅	❌	✅	❌	✅	4
Learning to Hash Robustly, Guaranteed	✅	❌	✅	❌	✅	✅	✅	5
Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization	❌	❌	✅	❌	❌	❌	✅	2
Learning to Infer Structures of Network Games	❌	❌	✅	✅	✅	❌	✅	4
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters	✅	✅	✅	✅	❌	❌	✅	5
Learning to Separate Voices by Spatial Regions	✅	❌	✅	✅	✅	❌	✅	5
Learning to Solve PDE-constrained Inverse Problems with Graph Networks	❌	❌	❌	✅	✅	❌	✅	3
Learning-based Optimisation of Particle Accelerators Under Partial Observability Without Real-World Training	❌	❌	❌	❌	✅	❌	✅	2
Least Squares Estimation using Sketched Data with Heteroskedastic Errors	❌	✅	✅	❌	❌	❌	✅	3
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time	✅	❌	✅	❌	❌	❌	✅	3
Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity	✅	✅	❌	❌	❌	❌	✅	3
Lie Point Symmetry Data Augmentation for Neural PDE Solvers	❌	✅	❌	❌	✅	❌	✅	3
Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent	✅	❌	❌	❌	✅	❌	❌	2
Linear Adversarial Concept Erasure	✅	✅	✅	✅	❌	❌	✅	5
Linear Bandit Algorithms with Sublinear Time Complexity	✅	❌	✅	❌	❌	❌	✅	3
Linear Complexity Randomized Self-attention Mechanism	✅	❌	✅	✅	❌	❌	✅	4
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs	✅	✅	✅	❌	✅	❌	✅	5
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness	❌	✅	✅	❌	❌	❌	✅	3
Local Augmentation for Graph Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Local Linear Convergence of Douglas-Rachford for Linear Programming: a Probabilistic Analysis	✅	❌	❌	❌	❌	❌	✅	2
Locally Sparse Neural Networks for Tabular Biomedical Data	✅	❌	✅	✅	✅	❌	✅	5
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets	✅	✅	✅	✅	❌	❌	✅	5
Loss Function Learning for Domain Generalization by Implicit Gradient	✅	❌	✅	✅	✅	❌	✅	5
Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions	✅	✅	✅	❌	✅	✅	✅	6
Low-Precision Stochastic Gradient Langevin Dynamics	✅	❌	✅	❌	❌	❌	✅	3
LyaNet: A Lyapunov Framework for Training Neural ODEs	✅	✅	✅	✅	✅	❌	✅	6
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control	✅	❌	✅	❌	❌	❌	✅	3
MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection	✅	✅	✅	✅	✅	❌	✅	6
MAML and ANIL Provably Learn Representations	❌	❌	❌	❌	❌	❌	✅	1
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer	❌	✅	✅	❌	✅	❌	✅	4
ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases	❌	❌	✅	❌	✅	✅	✅	4
Making Linear MDPs Practical via Contrastive Representation Learning	✅	❌	✅	❌	❌	❌	✅	3
Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization	❌	❌	✅	✅	✅	❌	✅	4
Marginal Tail-Adaptive Normalizing Flows	✅	✅	✅	✅	❌	❌	✅	5
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems	✅	✅	❌	❌	❌	❌	✅	3
Maslow’s Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation	❌	✅	✅	❌	❌	❌	✅	3
Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances	✅	❌	✅	❌	✅	❌	✅	4
Matching Learned Causal Effects of Neural Networks with Domain Priors	✅	✅	✅	✅	✅	❌	✅	6
Matching Normalizing Flows and Probability Paths on Manifolds	❌	❌	✅	❌	❌	❌	✅	2
Matching Structure for Dual Learning	❌	✅	✅	✅	❌	❌	✅	4
Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching	✅	✅	✅	❌	✅	❌	✅	5
Meaningfully debugging model mistakes using conceptual counterfactual explanations	✅	✅	✅	✅	❌	❌	✅	5
Measure Estimation in the Barycentric Coding Model	✅	✅	✅	❌	✅	❌	✅	5
Measuring Representational Robustness of Neural Networks Through Shared Invariances	❌	✅	✅	✅	❌	❌	✅	4
Measuring dissimilarity with diffeomorphism invariance	❌	✅	✅	❌	❌	✅	✅	4
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments	✅	✅	✅	✅	✅	❌	✅	6
MemSR: Training Memory-efficient Lightweight Model for Image Super-Resolution	✅	❌	✅	✅	✅	✅	✅	6
Memory-Based Model Editing at Scale	❌	❌	✅	✅	❌	❌	✅	3
MetAug: Contrastive Learning via Meta Feature Augmentation	✅	❌	✅	❌	❌	❌	✅	3
Meta-Learning Hypothesis Spaces for Sequential Decision-making	❌	❌	✅	✅	❌	❌	✅	3
Metric-Fair Active Learning	✅	❌	❌	❌	❌	❌	✅	2
Metric-Fair Classifier Derandomization	❌	❌	❌	❌	❌	❌	❌	0
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees	✅	✅	✅	✅	❌	❌	✅	5
Minimax M-estimation under Adversarial Contamination	✅	❌	❌	❌	❌	❌	✅	2
Minimizing Control for Credit Assignment with Strong Feedback	✅	✅	✅	✅	❌	❌	✅	5
Minimum Cost Intervention Design for Causal Effect Identification	✅	✅	✅	❌	❌	❌	✅	4
Mirror Learning: A Unifying Framework of Policy Optimisation	❌	✅	❌	❌	❌	❌	❌	1
Mitigating Gender Bias in Face Recognition using the von Mises-Fisher Mixture Model	❌	❌	✅	❌	✅	✅	✅	4
Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization	✅	❌	✅	✅	❌	❌	✅	4
Mitigating Neural Network Overconfidence with Logit Normalization	❌	✅	✅	✅	✅	❌	✅	5
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias	✅	❌	❌	❌	✅	❌	✅	3
Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)	❌	❌	✅	✅	✅	❌	✅	4
Model Agnostic Sample Reweighting for Out-of-Distribution Learning	✅	✅	✅	✅	❌	❌	✅	5
Model Selection in Batch Policy Optimization	✅	❌	❌	❌	❌	❌	✅	2
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time	✅	✅	✅	✅	❌	❌	✅	5
Model-Free Opponent Shaping	✅	❌	✅	❌	❌	❌	✅	3
Model-Value Inconsistency as a Signal for Epistemic Uncertainty	❌	❌	✅	✅	❌	❌	✅	3
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search	✅	✅	✅	✅	✅	❌	✅	6
Modeling Adversarial Noise for Adversarial Training	✅	✅	✅	✅	❌	❌	✅	5
Modeling Irregular Time Series with Continuous Recurrent Units	✅	✅	✅	✅	✅	❌	✅	6
Modeling Strong and Human-Like Gameplay with KL-Regularized Search	✅	❌	✅	✅	❌	❌	✅	4
Modeling Structure with Undirected Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Modular Conformal Calibration	✅	❌	✅	✅	❌	❌	✅	4
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Monarch: Expressive Structured Matrices for Efficient and Accurate Training	✅	✅	✅	✅	✅	❌	✅	6
More Efficient Sampling for Tensor Decomposition With Worst-Case Guarantees	✅	✅	✅	✅	✅	✅	✅	7
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize	❌	✅	✅	❌	✅	❌	✅	4
Multi Resolution Analysis (MRA) for Approximate Self-Attention	✅	✅	✅	❌	✅	❌	✅	5
Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts	❌	✅	✅	✅	✅	❌	✅	5
Multi-Level Branched Regularization for Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Multi-Task Learning as a Bargaining Game	✅	✅	✅	✅	❌	❌	✅	5
Multi-scale Feature Learning Dynamics: Insights for Double Descent	❌	✅	✅	❌	❌	❌	✅	3
Multi-slots Online Matching with High Entropy	✅	❌	❌	❌	❌	❌	✅	2
Multiclass learning with margin: exponential rates with no bias-variance trade-off	❌	❌	❌	❌	❌	❌	❌	0
Multicoated Supermasks Enhance Hidden Networks	❌	✅	✅	✅	❌	❌	✅	4
Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms	✅	❌	❌	❌	❌	❌	✅	2
Multirate Training of Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
N-Penetrate: Active Learning of Neural Collision Handler for Complex 3D Mesh Deformations	✅	❌	✅	✅	✅	❌	✅	5
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning	✅	✅	✅	✅	✅	✅	✅	7
NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks	✅	✅	✅	✅	❌	❌	✅	5
NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework	❌	✅	✅	✅	❌	❌	✅	4
NOMU: Neural Optimization-based Model Uncertainty	✅	✅	✅	✅	❌	❌	✅	5
NP-Match: When Neural Processes meet Semi-Supervised Learning	❌	✅	✅	✅	✅	❌	✅	5
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning	❌	✅	✅	✅	❌	❌	✅	4
Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal Learning of Extensive-Form Games with Imperfect Information	✅	❌	❌	❌	❌	❌	❌	1
Near-optimal rate of consistency for linear models with missing values	❌	✅	✅	❌	❌	❌	✅	3
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Nearly Optimal Catoni’s M-estimator for Infinite Variance	✅	❌	❌	❌	❌	❌	✅	2
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee	✅	❌	❌	❌	❌	❌	❌	1
Nested Bandits	✅	✅	❌	❌	✅	❌	✅	4
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization	✅	✅	✅	✅	❌	✅	✅	6
Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time	✅	❌	✅	❌	❌	❌	✅	3
Neural Implicit Dictionary Learning via Mixture-of-Expert Training	❌	✅	✅	❌	❌	❌	✅	3
Neural Inverse Kinematic	❌	❌	❌	❌	❌	❌	✅	1
Neural Inverse Transform Sampler	✅	✅	✅	❌	✅	❌	✅	5
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps	❌	❌	✅	✅	❌	✅	✅	4
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain	✅	✅	❌	✅	✅	❌	✅	5
Neural Network Poisson Models for Behavioural and Neural Spike Train Data	❌	✅	✅	❌	❌	❌	✅	3
Neural Network Pruning Denoises the Features and Makes Local Connectivity Emerge in Visual Tasks	❌	✅	✅	✅	❌	✅	✅	5
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective	❌	✅	✅	❌	❌	❌	✅	3
Neural Tangent Kernel Analysis of Deep Narrow Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization	❌	✅	✅	❌	❌	❌	✅	3
Neural Tangent Kernel Empowered Federated Learning	❌	✅	✅	❌	❌	❌	✅	3
Neural-Symbolic Models for Logical Queries on Knowledge Graphs	✅	✅	✅	✅	✅	❌	✅	6
NeuralEF: Deconstructing Kernels by Deep Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Neuro-Symbolic Hierarchical Rule Induction	❌	✅	✅	✅	❌	❌	✅	4
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval	❌	✅	✅	✅	✅	❌	✅	5
NeuroFluid: Fluid Dynamics Grounding with Particle-Driven Neural Radiance Fields	❌	✅	❌	❌	❌	❌	✅	2
Neurocoder: General-Purpose Computation Using Stored Neural Programs	❌	❌	✅	❌	✅	❌	✅	3
Neuron Dependency Graphs: A Causal Abstraction of Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Neurotoxin: Durable Backdoors in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
No-Regret Learning in Partially-Informed Auctions	✅	❌	❌	❌	❌	❌	❌	1
No-Regret Learning in Time-Varying Zero-Sum Games	✅	❌	❌	❌	❌	❌	✅	2
Non-Vacuous Generalisation Bounds for Shallow Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Nonlinear Feature Diffusion on Hypergraphs	✅	✅	✅	✅	❌	❌	✅	5
Nonparametric Embeddings of Sparse High-Order Interaction Events	❌	❌	✅	❌	❌	❌	✅	2
Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition	❌	❌	✅	✅	❌	❌	✅	3
Nonparametric Involutive Markov Chain Monte Carlo	✅	✅	❌	❌	❌	❌	✅	3
Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes	❌	❌	✅	✅	❌	❌	✅	3
Not All Poisons are Created Equal: Robust Training against Data Poisoning	✅	✅	✅	❌	✅	❌	✅	5
NysADMM: faster composite convex optimization via low-rank approximation	✅	❌	✅	❌	✅	❌	✅	4
Nyström Kernel Mean Embeddings	❌	❌	✅	❌	❌	❌	✅	2
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework	❌	✅	✅	✅	❌	❌	✅	4
Object Permanence Emerges in a Random Walk along Memory	✅	✅	✅	✅	❌	❌	✅	5
Off-Policy Evaluation for Large Action Spaces via Embeddings	✅	✅	✅	❌	❌	❌	✅	4
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory	✅	❌	❌	❌	❌	❌	❌	1
Off-Policy Reinforcement Learning with Delayed Rewards	✅	❌	✅	❌	✅	❌	✅	4
Offline Meta-Reinforcement Learning with Online Self-Supervision	✅	❌	✅	❌	❌	❌	✅	3
Offline RL Policies Should Be Trained to be Adaptive	✅	❌	✅	❌	❌	❌	✅	3
Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning	✅	❌	✅	✅	❌	❌	✅	4
On Collective Robustness of Bagging Against Data Poisoning	✅	✅	✅	✅	✅	✅	✅	7
On Convergence of Gradient Descent Ascent: A Tight Local Analysis	❌	❌	✅	❌	❌	❌	✅	2
On Distribution Shift in Learning-based Bug Detectors	❌	✅	✅	✅	✅	❌	✅	5
On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis	❌	❌	✅	❌	❌	❌	✅	2
On Implicit Bias in Overparameterized Bilevel Optimization	✅	❌	✅	❌	✅	✅	✅	5
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
On Last-Iterate Convergence Beyond Zero-Sum Games	❌	❌	✅	❌	❌	❌	✅	2
On Learning Mixture of Linear Regressions in the Non-Realizable Setting	✅	❌	✅	✅	❌	❌	✅	4
On Measuring Causal Contributions via do-interventions	✅	❌	✅	✅	❌	❌	✅	4
On Non-local Convergence Analysis of Deep Linear Networks	❌	❌	❌	❌	❌	❌	✅	1
On Numerical Integration in Neural Ordinary Differential Equations	❌	✅	❌	❌	❌	❌	✅	2
On Transportation of Mini-batches: A Hierarchical Approach	✅	✅	✅	❌	✅	❌	✅	5
On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation	❌	❌	❌	❌	❌	❌	❌	0
On the Adversarial Robustness of Causal Algorithmic Recourse	✅	✅	✅	❌	❌	❌	✅	4
On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming	✅	❌	❌	❌	❌	❌	✅	2
On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum	✅	❌	✅	✅	✅	❌	✅	5
On the Convergence of the Shapley Value in Parametric Bayesian Learning Games	❌	✅	✅	❌	❌	❌	✅	3
On the Difficulty of Defending Self-Supervised Learning against Model Extraction	✅	❌	✅	❌	✅	❌	✅	4
On the Effects of Artificial Data Modification	❌	✅	✅	❌	✅	❌	✅	4
On the Equivalence Between Temporal and Static Equivariant Graph Representations	❌	✅	✅	✅	✅	❌	✅	5
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions	✅	❌	❌	❌	❌	❌	❌	1
On the Finite-Time Performance of the Knowledge Gradient Algorithm	✅	❌	❌	❌	❌	❌	✅	2
On the Generalization Analysis of Adversarial Learning	❌	❌	❌	❌	❌	❌	❌	0
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces	✅	❌	❌	❌	❌	❌	✅	2
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games	❌	❌	❌	❌	❌	❌	❌	0
On the Learning of Non-Autoregressive Transformers	❌	❌	✅	❌	✅	❌	✅	3
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features	❌	✅	✅	✅	❌	❌	✅	4
On the Practicality of Deterministic Epistemic Uncertainty	❌	❌	✅	✅	✅	✅	✅	5
On the Robustness of CountSketch to Adaptive Inputs	✅	✅	❌	❌	❌	❌	✅	3
On the Role of Discount Factor in Offline Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs	✅	❌	❌	❌	❌	❌	❌	1
On the Statistical Benefits of Curriculum Learning	✅	❌	❌	❌	❌	❌	✅	2
On the Surrogate Gap between Contrastive and Supervised Losses	❌	✅	✅	✅	✅	✅	✅	6
One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes	✅	❌	✅	❌	✅	❌	✅	4
One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams	✅	✅	✅	❌	✅	❌	✅	5
Online Active Regression	✅	❌	✅	❌	✅	❌	✅	4
Online Algorithms with Multiple Predictions	✅	❌	❌	❌	❌	❌	❌	1
Online Balanced Experimental Design	✅	❌	❌	❌	✅	❌	✅	3
Online Continual Learning through Mutual Information Maximization	✅	✅	✅	❌	❌	❌	✅	4
Online Decision Transformer	✅	❌	✅	❌	❌	❌	✅	3
Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards	✅	❌	❌	❌	❌	❌	✅	2
Online Learning for Min Sum Set Cover and Pandora’s Box	✅	❌	❌	❌	❌	❌	❌	1
Online Learning with Knapsacks: the Best of Both Worlds	✅	❌	❌	❌	❌	❌	❌	1
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback	✅	❌	❌	❌	✅	❌	✅	3
Online and Consistent Correlation Clustering	✅	✅	✅	❌	✅	❌	✅	5
Only tails matter: Average-Case Universality and Robustness in the Convex Regime	✅	❌	✅	❌	❌	❌	✅	3
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets	✅	✅	✅	✅	✅	❌	✅	6
Optimal Algorithms for Mean Estimation under Local Differential Privacy	✅	❌	❌	❌	❌	❌	❌	1
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization	✅	❌	✅	❌	❌	❌	✅	3
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training	❌	❌	✅	❌	✅	❌	✅	3
Optimal Clustering with Noisy Queries via Multi-Armed Bandit	✅	❌	❌	❌	❌	❌	❌	1
Optimal Estimation of Policy Gradient via Double Fitted Iteration	✅	❌	❌	❌	❌	❌	❌	1
Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits	✅	❌	❌	❌	❌	❌	✅	2
Optimally Controllable Perceptual Lossy Compression	❌	✅	✅	❌	❌	❌	✅	3
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer	✅	✅	✅	❌	❌	❌	✅	4
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training	✅	❌	✅	❌	✅	❌	✅	4
Optimization-Induced Graph Implicit Nonlinear Diffusion	❌	✅	✅	✅	❌	❌	✅	4
Optimizing Sequential Experimental Design with Deep Reinforcement Learning	❌	✅	❌	❌	✅	❌	✅	3
Optimizing Tensor Network Contraction Using Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering	✅	✅	✅	✅	✅	❌	✅	6
Order Constraints in Optimal Transport	✅	✅	✅	✅	✅	❌	✅	6
Out-of-Distribution Detection with Deep Nearest Neighbors	✅	✅	✅	✅	❌	❌	✅	5
Overcoming Oscillations in Quantization-Aware Training	✅	✅	✅	✅	❌	❌	✅	5
PAC-Bayesian Bounds on Rate-Efficient Classifiers	❌	✅	✅	✅	❌	❌	✅	4
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning	✅	❌	✅	❌	❌	❌	✅	3
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs	✅	✅	✅	✅	✅	❌	✅	6
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation	✅	✅	✅	❌	❌	❌	✅	4
PDE-Based Optimal Strategy for Unconstrained Online Learning	✅	✅	✅	❌	❌	❌	✅	4
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs	❌	❌	✅	✅	✅	❌	✅	4
PINs: Progressive Implicit Networks for Multi-Scale Neural Representations	❌	❌	✅	✅	❌	❌	✅	3
PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information	✅	✅	✅	✅	✅	❌	✅	6
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance	✅	✅	✅	✅	✅	❌	✅	6
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration	✅	❌	✅	❌	✅	❌	✅	4
POEM: Out-of-Distribution Detection with Posterior Sampling	✅	✅	✅	❌	✅	✅	✅	6
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging	✅	✅	✅	❌	✅	❌	✅	5
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding	✅	✅	✅	❌	❌	❌	✅	4
Parametric Visual Program Induction with Function Modularization	✅	❌	✅	❌	✅	❌	❌	3
Parsimonious Learning-Augmented Caching	✅	❌	✅	❌	❌	❌	✅	3
Partial Counterfactual Identification from Observational and Experimental Data	✅	❌	✅	❌	❌	❌	✅	3
Partial Label Learning via Label Influence Function	✅	❌	✅	✅	❌	❌	✅	4
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition	✅	✅	✅	✅	❌	❌	✅	5
Partial disentanglement for domain adaptation	✅	❌	✅	❌	❌	❌	✅	3
Particle Transformer for Jet Tagging	❌	✅	✅	✅	❌	❌	✅	4
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules	❌	❌	✅	✅	❌	❌	✅	3
Path-Gradient Estimators for Continuous Normalizing Flows	✅	✅	✅	❌	✅	❌	✅	5
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning	✅	✅	✅	❌	✅	❌	✅	5
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning	❌	✅	✅	❌	✅	❌	✅	4
Permutation Search of Tensor Network Structures via Local Sampling	✅	✅	✅	❌	❌	❌	✅	4
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Personalized Federated Learning through Local Memorization	✅	✅	✅	✅	❌	❌	✅	5
Personalized Federated Learning via Variational Bayesian Inference	✅	❌	✅	✅	✅	❌	✅	5
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets	✅	❌	❌	❌	❌	❌	❌	1
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity	✅	❌	❌	❌	❌	❌	❌	1
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification	✅	✅	✅	❌	❌	❌	✅	4
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization	✅	✅	✅	✅	❌	❌	✅	5
Planning with Diffusion for Flexible Behavior Synthesis	✅	✅	✅	❌	❌	✅	✅	5
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks	❌	✅	✅	❌	✅	✅	✅	5
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations	✅	✅	✅	❌	❌	❌	✅	4
PoF: Post-Training of Feature Extractor for Improving Generalization	✅	❌	✅	✅	✅	❌	✅	5
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets	❌	✅	✅	✅	✅	✅	✅	6
Policy Diagnosis via Measuring Role Diversity in Cooperative Multi-agent RL	❌	❌	✅	❌	❌	❌	✅	2
Policy Gradient Method For Robust Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Popular decision tree algorithms are provably noise tolerant	✅	❌	❌	❌	❌	❌	❌	1
Position Prediction as an Effective Pretraining Strategy	✅	❌	✅	✅	✅	❌	✅	5
Power-Law Escape Rate of SGD	❌	❌	✅	❌	❌	❌	✅	2
Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering	✅	✅	✅	❌	✅	✅	✅	6
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization	✅	✅	✅	✅	✅	❌	✅	6
Predicting Out-of-Distribution Error with the Projection Norm	✅	✅	✅	✅	❌	❌	✅	5
Principal Component Flows	✅	✅	✅	❌	✅	❌	✅	5
Principled Knowledge Extrapolation with GANs	✅	❌	✅	❌	✅	❌	✅	4
Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt	✅	✅	✅	✅	❌	❌	✅	5
Privacy for Free: How does Dataset Condensation Help Privacy?	❌	❌	✅	❌	❌	✅	✅	3
Private Adaptive Optimization with Side information	✅	✅	✅	✅	❌	❌	✅	5
Private Streaming SCO in $\ell_p$ geometry with Applications in High Dimensional Online Decision Making	✅	✅	❌	❌	❌	❌	✅	3
Private frequency estimation via projective geometry	❌	✅	❌	❌	✅	✅	✅	4
Private optimization in the interpolation regime: faster rates and hardness results	✅	❌	❌	❌	❌	❌	❌	1
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning	✅	✅	✅	✅	✅	❌	✅	6
Probabilistic Bilevel Coreset Selection	✅	❌	✅	✅	❌	❌	✅	4
Probabilistic ODE Solutions in Millions of Dimensions	❌	✅	✅	❌	❌	❌	✅	3
Probabilistically Robust Learning: Balancing Average and Worst-case Performance	✅	✅	✅	✅	✅	❌	✅	6
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training	✅	✅	✅	❌	❌	❌	✅	4
Prompting Decision Transformer for Few-Shot Policy Generalization	✅	❌	✅	❌	❌	❌	✅	3
Prototype Based Classification from Hierarchy to Fairness	❌	✅	✅	❌	❌	❌	✅	3
Prototype-Anchored Learning for Learning with Imperfect Annotations	✅	❌	✅	✅	❌	❌	✅	4
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out	✅	❌	❌	❌	❌	❌	✅	2
Provable Domain Generalization via Invariant-Feature Subspace Recovery	✅	✅	✅	✅	❌	❌	✅	5
Provable Reinforcement Learning with a Short-Term Memory	✅	❌	❌	❌	❌	❌	❌	1
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance	✅	✅	✅	✅	✅	❌	✅	6
Provably Adversarially Robust Nearest Prototype Classifiers	✅	✅	✅	❌	❌	❌	❌	3
Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Proving Theorems using Incremental Learning and Hindsight Experience Replay	✅	❌	✅	❌	✅	✅	✅	5
ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally!	✅	✅	✅	❌	✅	❌	✅	5
Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization	✅	✅	✅	❌	❌	❌	✅	4
Proximal Exploration for Model-guided Protein Sequence Design	✅	✅	✅	❌	❌	❌	✅	4
Proximal and Federated Random Reshuffling	✅	✅	✅	❌	❌	❌	✅	4
Public Data-Assisted Mirror Descent for Private Model Training	✅	✅	✅	✅	❌	❌	✅	5
Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images	✅	✅	✅	✅	❌	❌	✅	5
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features	✅	✅	✅	✅	✅	✅	✅	7
Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding	❌	✅	✅	❌	❌	❌	✅	3
Quantifying and Learning Linear Symmetry-Based Disentanglement	❌	✅	✅	✅	✅	❌	✅	5
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra	✅	❌	✅	❌	✅	❌	✅	4
Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization	✅	✅	✅	❌	❌	❌	✅	4
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization	✅	✅	✅	❌	❌	❌	✅	4
REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer	✅	✅	✅	❌	❌	❌	✅	4
ROCK: Causal Inference Principles for Reasoning about Commonsense Causality	❌	✅	✅	✅	❌	❌	✅	4
RUMs from Head-to-Head Contests	✅	❌	✅	✅	✅	❌	✅	5
Random Forest Density Estimation	✅	❌	✅	✅	❌	❌	✅	4
Random Gegenbauer Features for Scalable Kernel Methods	❌	❌	✅	✅	❌	❌	✅	3
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression	❌	✅	✅	✅	✅	❌	✅	5
Re-evaluating Word Mover’s Distance	❌	✅	✅	✅	✅	❌	✅	5
Reachability Constrained Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series	❌	✅	✅	✅	✅	❌	✅	5
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs	❌	✅	✅	❌	✅	❌	✅	4
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks	✅	✅	✅	❌	❌	❌	✅	4
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models	✅	✅	❌	❌	❌	✅	✅	4
Region-Based Semantic Factorization in GANs	❌	✅	✅	❌	✅	❌	✅	4
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Regret Minimization with Performative Feedback	✅	❌	❌	❌	❌	❌	❌	1
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency	✅	❌	❌	❌	❌	❌	❌	1
Reinforcement Learning with Action-Free Pre-Training from Videos	❌	✅	✅	❌	✅	❌	✅	4
Removing Batch Normalization Boosts Adversarial Training	❌	✅	✅	✅	✅	❌	✅	5
Representation Topology Divergence: A Method for Comparing Neural Network Representations.	✅	✅	✅	❌	❌	❌	✅	4
Residual-Based Sampling for Online Outlier-Robust PCA	✅	❌	❌	❌	❌	❌	✅	2
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems	✅	❌	✅	❌	❌	❌	✅	3
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^-7/4)$ Complexity	✅	❌	✅	❌	❌	❌	✅	3
Rethinking Attention-Model Explainability through Faithfulness Violation Test	❌	✅	✅	❌	❌	❌	❌	2
Rethinking Fano’s Inequality in Ensemble Learning	❌	✅	✅	✅	✅	✅	✅	6
Rethinking Graph Neural Networks for Anomaly Detection	❌	✅	✅	✅	✅	❌	✅	5
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems	✅	✅	✅	❌	✅	❌	✅	5
Retrieval-Augmented Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval	✅	❌	✅	❌	✅	❌	✅	4
Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer	✅	✅	✅	✅	✅	❌	✅	6
Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees	✅	❌	✅	❌	❌	❌	✅	3
Reverse Engineering the Neural Tangent Kernel	❌	✅	✅	✅	❌	❌	✅	4
Revisiting Consistency Regularization for Deep Partial Label Learning	✅	❌	✅	❌	✅	❌	✅	4
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework	❌	❌	✅	❌	✅	❌	✅	3
Revisiting End-to-End Speech-to-Text Translation From Scratch	❌	✅	✅	✅	❌	❌	✅	4
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?	✅	✅	✅	✅	❌	✅	✅	6
Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness	✅	❌	❌	❌	❌	❌	❌	1
Revisiting Some Common Practices in Cooperative Multi-Agent Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization	✅	✅	✅	✅	✅	❌	✅	6
Revisiting the Effects of Stochasticity for Hamiltonian Samplers	❌	❌	✅	❌	✅	❌	✅	3
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Rich Feature Construction for the Optimization-Generalization Dilemma	✅	✅	✅	✅	❌	❌	✅	5
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests	❌	✅	✅	❌	❌	❌	✅	3
Ripple Attention for Visual Perception with Sub-quadratic Complexity	✅	❌	✅	✅	✅	❌	✅	5
Risk-Averse No-Regret Learning in Online Convex Games	✅	❌	❌	❌	❌	❌	✅	2
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data	❌	✅	✅	✅	❌	❌	✅	4
Robust Counterfactual Explanations for Tree-Based Ensembles	✅	❌	✅	❌	❌	❌	✅	3
Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum	✅	✅	✅	❌	✅	❌	✅	5
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees	✅	❌	✅	✅	❌	❌	✅	4
Robust Group Synchronization via Quadratic Programming	✅	✅	✅	❌	❌	❌	✅	4
Robust Imitation Learning against Variations in Environment Dynamics	✅	✅	✅	✅	❌	❌	✅	5
Robust Kernel Density Estimation with Median-of-Means principle	❌	✅	✅	❌	❌	❌	✅	3
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile	✅	✅	✅	✅	✅	❌	✅	6
Robust Models Are More Interpretable Because Attributions Look Normal	❌	✅	✅	❌	✅	✅	✅	5
Robust Multi-Objective Bayesian Optimization Under Input Noise	❌	✅	✅	❌	✅	✅	✅	5
Robust Policy Learning over Multiple Uncertainty Sets	✅	✅	✅	❌	❌	❌	✅	4
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning	✅	✅	❌	❌	❌	❌	✅	3
Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive Learning	✅	✅	✅	❌	❌	❌	✅	4
Robust Training of Neural Networks Using Scale Invariant Architectures	✅	❌	✅	❌	❌	❌	✅	3
Robust Training under Label Noise by Over-parameterization	✅	✅	✅	✅	✅	✅	✅	7
Robust alignment of cross-session recordings of neural population activity by behaviour via unsupervised domain adaptation	❌	❌	✅	✅	❌	❌	✅	3
Robustness Implies Generalization via Data-Dependent Generalization Bounds	❌	❌	✅	✅	❌	❌	✅	3
Robustness Verification for Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition	❌	✅	✅	✅	❌	❌	✅	4
Robustness in Multi-Objective Submodular Optimization: a Quantile Approach	✅	❌	✅	❌	❌	❌	❌	2
Role-based Multiplex Network Embedding	✅	❌	✅	❌	❌	❌	✅	3
Rotting Infinitely Many-Armed Bandits	✅	✅	❌	❌	❌	❌	✅	3
SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation	✅	✅	✅	✅	❌	❌	✅	5
SDQ: Stochastic Differentiable Quantization with Mixed Precision	✅	❌	✅	✅	✅	❌	✅	5
SE(3) Equivariant Graph Neural Networks with Complete Local Frames	✅	❌	✅	✅	✅	❌	✅	5
SPDY: Accurate Pruning with Speedup Guarantees	✅	✅	✅	✅	✅	✅	✅	7
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators	❌	✅	✅	✅	✅	❌	✅	5
SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization	✅	✅	✅	✅	❌	❌	✅	5
Safe Exploration for Efficient Policy Evaluation and Comparison	✅	❌	✅	❌	❌	❌	✅	3
Safe Learning in Tree-Form Sequential Decision Making: Handling Hard and Soft Constraints	✅	❌	✅	❌	❌	❌	✅	3
Sample Efficient Learning of Predictors that Complement Humans	✅	✅	✅	✅	❌	❌	✅	5
Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis	✅	❌	❌	❌	❌	❌	✅	2
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost	✅	❌	❌	❌	❌	❌	❌	1
Sanity Simulations for Saliency Methods	❌	✅	✅	✅	✅	❌	✅	5
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation	✅	✅	✅	❌	❌	✅	✅	5
Scalable Computation of Causal Bounds	✅	❌	❌	❌	❌	❌	❌	1
Scalable Deep Gaussian Markov Random Fields for General Graphs	❌	✅	✅	✅	❌	❌	✅	4
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games	✅	✅	❌	❌	❌	❌	✅	3
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation	✅	✅	✅	❌	❌	❌	✅	4
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes	✅	✅	✅	✅	❌	❌	✅	5
Scalable Spike-and-Slab	✅	✅	✅	✅	✅	❌	✅	6
Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times	✅	❌	✅	❌	❌	❌	✅	3
Scaling Out-of-Distribution Detection for Real-World Settings	❌	✅	✅	✅	❌	❌	✅	4
Scaling Structured Inference with Randomization	✅	✅	✅	❌	✅	❌	✅	5
Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework	✅	✅	✅	❌	✅	❌	✅	5
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models	✅	✅	✅	❌	❌	❌	✅	4
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems	✅	✅	✅	❌	✅	❌	✅	5
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations	✅	✅	✅	✅	✅	✅	✅	7
Searching for BurgerFormer with Micro-Meso-Macro Space Design	❌	✅	✅	✅	✅	❌	✅	5
Secure Distributed Training at Scale	✅	✅	✅	❌	✅	❌	✅	5
Secure Quantized Training for Deep Learning	✅	✅	✅	✅	✅	❌	✅	6
Selective Network Linearization for Efficient Private Inference	✅	✅	✅	✅	❌	❌	✅	5
Selective Regression under Fairness Criteria	✅	✅	✅	❌	❌	❌	✅	4
Self-Organized Polynomial-Time Coordination Graphs	✅	✅	✅	❌	✅	❌	✅	5
Self-Supervised Models of Audio Effectively Explain Human Cortical Responses to Speech	❌	❌	✅	✅	❌	✅	✅	4
Self-Supervised Representation Learning via Latent Graph Prediction	✅	✅	✅	✅	✅	✅	✅	7
Self-conditioning Pre-Trained Language Models	✅	✅	✅	❌	✅	❌	✅	5
Self-supervised Models are Good Teaching Assistants for Vision Transformers	❌	✅	✅	✅	❌	❌	✅	4
Self-supervised learning with random-projection quantizer for speech recognition	❌	❌	✅	❌	❌	❌	✅	2
Selling Data To a Machine Learner: Pricing via Costly Signaling	❌	❌	❌	❌	❌	❌	✅	1
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests	✅	✅	✅	❌	❌	❌	✅	4
Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound	✅	❌	✅	❌	❌	❌	✅	3
Set Based Stochastic Subsampling	✅	❌	✅	❌	❌	❌	✅	3
Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets	❌	✅	✅	❌	✅	❌	✅	4
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning	✅	✅	✅	❌	❌	❌	✅	4
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood	✅	❌	❌	❌	❌	❌	✅	2
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Short-Term Plasticity Neurons Learning to Learn and Forget	✅	✅	✅	✅	❌	❌	✅	5
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters	❌	✅	✅	✅	✅	❌	✅	5
Shuffle Private Linear Contextual Bandits	✅	✅	❌	❌	❌	❌	✅	3
Simple and near-optimal algorithms for hidden stratification and multi-group learning	✅	❌	❌	❌	❌	❌	❌	1
Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games	✅	❌	✅	❌	✅	❌	✅	4
Simultaneous Graph Signal Clustering and Graph Learning	✅	✅	✅	❌	❌	❌	✅	4
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback	✅	❌	❌	❌	❌	❌	❌	1
Sketching Algorithms and Lower Bounds for Ridge Regression	✅	❌	❌	❌	❌	❌	✅	2
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks	❌	✅	✅	✅	✅	❌	✅	5
Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification	❌	✅	✅	✅	✅	❌	✅	5
Smoothed Adaptive Weighting for Imbalanced Semi-Supervised Learning: Improve Reliability Against Unknown Distribution Data	✅	✅	✅	❌	✅	✅	✅	6
Smoothed Adversarial Linear Contextual Bandits with Knapsacks	✅	❌	❌	❌	❌	❌	❌	1
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals	✅	✅	✅	✅	❌	❌	✅	5
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation	❌	✅	✅	❌	✅	❌	✅	4
Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation	✅	❌	✅	❌	✅	✅	✅	5
SpaceMAP: Visualizing High-Dimensional Data by Space Expansion	✅	❌	✅	✅	✅	❌	✅	5
Sparse Double Descent: Where Network Pruning Aggravates Overfitting	❌	✅	✅	❌	❌	❌	✅	3
Sparse Invariant Risk Minimization	✅	❌	✅	❌	❌	❌	✅	3
Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation	❌	❌	❌	❌	❌	❌	✅	1
Sparsity in Partially Controllable Linear Systems	✅	❌	❌	❌	❌	❌	✅	2
Spatial-Channel Token Distillation for Vision MLPs	✅	❌	✅	❌	✅	❌	❌	3
Spectral Representation of Robustness Measures for Optimization Under Input Uncertainty	✅	✅	✅	❌	❌	❌	✅	4
SpeqNets: Sparsity-aware permutation-equivariant graph networks	✅	✅	✅	✅	✅	✅	✅	7
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics	❌	❌	✅	❌	✅	❌	✅	3
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels	❌	✅	✅	✅	❌	❌	✅	4
Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning	✅	❌	❌	❌	❌	❌	❌	1
Stable Conformal Prediction Sets	✅	✅	✅	❌	❌	❌	✅	4
Staged Training for Transformer Language Models	✅	✅	✅	❌	❌	❌	✅	4
State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks	❌	❌	✅	✅	✅	❌	✅	4
Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert	❌	❌	❌	❌	❌	❌	✅	1
Steerable 3D Spherical Neurons	❌	✅	✅	✅	❌	❌	✅	4
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models	✅	❌	❌	❌	✅	❌	✅	3
Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function	✅	❌	✅	❌	❌	❌	✅	3
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning	✅	✅	✅	❌	❌	❌	✅	4
Stochastic Reweighted Gradient Descent	✅	❌	✅	❌	❌	❌	✅	3
Stochastic Rising Bandits	✅	✅	✅	❌	❌	❌	✅	4
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification	❌	✅	✅	✅	❌	❌	✅	4
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses	❌	❌	✅	❌	✅	❌	✅	3
Strategic Representation	✅	❌	❌	❌	❌	❌	❌	1
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk	✅	❌	✅	❌	❌	❌	✅	3
Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints	✅	❌	✅	❌	❌	❌	✅	3
Streaming Algorithms for High-Dimensional Robust Statistics	✅	❌	❌	❌	❌	❌	❌	1
Streaming Algorithms for Support-Aware Histograms	✅	❌	✅	❌	❌	❌	✅	3
Streaming Inference for Infinite Feature Models	❌	❌	✅	❌	❌	❌	❌	1
StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models	❌	❌	✅	✅	✅	❌	✅	4
Structural Entropy Guided Graph Hierarchical Pooling	✅	✅	✅	✅	❌	❌	✅	5
Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation	✅	✅	❌	✅	✅	✅	✅	6
Structure-Aware Transformer for Graph Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Structure-preserving GANs	❌	❌	✅	✅	❌	✅	✅	4
Structured Stochastic Gradient MCMC	✅	✅	✅	✅	❌	❌	✅	5
Style Equalization: Unsupervised Learning of Controllable Generative Sequence Models	❌	✅	✅	✅	✅	❌	✅	5
Sublinear-Time Clustering Oracle for Signed Graphs	✅	✅	✅	❌	✅	❌	✅	5
Subspace Learning for Effective Meta-Learning	✅	❌	✅	✅	❌	❌	✅	4
Supervised Learning with General Risk Functionals	❌	❌	✅	✅	❌	❌	✅	3
Supervised Off-Policy Ranking	✅	✅	✅	✅	✅	❌	✅	6
Surrogate Likelihoods for Variational Annealed Importance Sampling	✅	❌	✅	❌	✅	❌	✅	4
Symmetric Machine Theory of Mind	✅	✅	❌	❌	✅	❌	✅	4
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm	❌	❌	✅	✅	❌	❌	✅	3
TACTiS: Transformer-Attentional Copulas for Time Series	❌	✅	✅	✅	✅	❌	✅	5
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification	✅	❌	✅	✅	❌	❌	✅	4
TPC: Transformation-Specific Smoothing for Point Cloud Models	❌	✅	✅	❌	❌	❌	❌	2
TSPipe: Learn from Teacher Faster with Pipelines	❌	✅	✅	❌	✅	❌	✅	4
TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm	✅	❌	❌	❌	❌	❌	✅	2
Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology	❌	❌	✅	✅	✅	❌	✅	4
Tackling covariate shift with node-based Bayesian neural networks	❌	✅	✅	❌	✅	❌	✅	4
Task-aware Privacy Preservation for Multi-dimensional Data	✅	✅	✅	❌	✅	❌	✅	5
Tell me why! Explanations support learning relational and causal structure	❌	❌	❌	❌	✅	✅	✅	3
Temporal Difference Learning for Model Predictive Control	✅	✅	✅	❌	✅	❌	✅	5
Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing	❌	✅	✅	✅	❌	❌	✅	4
The Algebraic Path Problem for Graph Metrics	❌	❌	❌	❌	❌	❌	❌	0
The CLRS Algorithmic Reasoning Benchmark	✅	✅	✅	✅	✅	❌	✅	6
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
The Complexity of k-Means Clustering when Little is Known	❌	❌	❌	❌	❌	❌	❌	0
The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention	❌	✅	✅	✅	❌	❌	✅	4
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
The Geometry of Robust Value Functions	❌	❌	❌	❌	❌	❌	❌	0
The Importance of Non-Markovianity in Maximum State Entropy Exploration	❌	❌	✅	❌	❌	❌	✅	2
The Infinite Contextual Graph Markov Model	✅	✅	✅	✅	❌	❌	✅	5
The Multivariate Community Hawkes Model for Dependent Relational Events in Continuous-time Networks	✅	✅	✅	❌	❌	❌	✅	4
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks	❌	✅	✅	✅	❌	❌	✅	4
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation	✅	❌	❌	❌	❌	❌	✅	2
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces	✅	❌	❌	❌	❌	❌	❌	1
The Primacy Bias in Deep Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
The Role of Deconfounding in Meta-learning	✅	❌	✅	✅	❌	❌	✅	4
The State of Sparse Training in Deep Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
The Teaching Dimension of Regularized Kernel Learners	❌	✅	✅	❌	❌	❌	✅	3
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control	❌	✅	✅	❌	✅	❌	✅	4
The dynamics of representation learning in shallow, non-linear autoencoders	❌	✅	✅	❌	❌	❌	✅	3
The power of first-order smooth optimization for black-box non-smooth problems	❌	✅	✅	❌	✅	✅	✅	5
Thompson Sampling for (Combinatorial) Pure Exploration	✅	❌	❌	❌	❌	❌	✅	2
Thompson Sampling for Robust Transfer in Multi-Task Bandits	✅	✅	❌	❌	❌	❌	✅	3
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points	❌	❌	✅	❌	❌	❌	✅	2
Thresholded Lasso Bandit	✅	✅	✅	❌	❌	❌	✅	4
Tight and Robust Private Mean Estimation with Few Users	✅	❌	❌	❌	❌	❌	❌	1
Time Is MattEr: Temporal Self-supervision for Video Transformers	❌	✅	✅	✅	❌	❌	✅	4
To Smooth or Not? When Label Smoothing Meets Noisy Labels	❌	✅	✅	❌	❌	❌	✅	3
Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning	❌	✅	✅	✅	✅	✅	✅	6
Topology-aware Generalization of Decentralized SGD	❌	✅	✅	✅	✅	❌	✅	5
Toward Compositional Generalization in Object-Oriented World Modeling	❌	✅	❌	❌	✅	❌	✅	3
Towards Coherent and Consistent Use of Entities in Narrative Generation	❌	❌	✅	✅	✅	❌	✅	4
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods	✅	✅	✅	✅	❌	❌	✅	5
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent	❌	✅	✅	❌	❌	❌	✅	3
Towards Scaling Difference Target Propagation by Learning Backprop Targets	✅	✅	✅	❌	❌	❌	✅	4
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs	❌	✅	✅	❌	✅	✅	✅	5
Towards Understanding Sharpness-Aware Minimization	❌	✅	✅	❌	✅	❌	✅	4
Towards Uniformly Superhuman Autonomy via Subdominance Minimization	✅	❌	❌	❌	❌	❌	❌	1
Towards understanding how momentum improves generalization in deep learning	❌	❌	✅	❌	❌	❌	✅	2
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems	❌	✅	✅	❌	❌	❌	✅	3
Tractable Uncertainty for Structure Learning	❌	✅	❌	❌	❌	❌	✅	2
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four	❌	❌	✅	❌	❌	❌	✅	2
Training Discrete Deep Generative Models via Gapped Straight-Through Estimator	✅	✅	✅	✅	✅	❌	✅	6
Training OOD Detectors in their Natural Habitats	✅	✅	✅	✅	✅	❌	✅	6
Training Your Sparse Neural Network Better with Any Mask	❌	✅	✅	❌	❌	❌	✅	3
Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval	❌	❌	✅	✅	✅	❌	✅	4
Transfer Learning In Differential Privacy’s Hybrid-Model	✅	❌	❌	❌	❌	❌	✅	2
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information	❌	❌	✅	✅	❌	❌	✅	3
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling	❌	✅	✅	❌	✅	❌	✅	4
Transformer Quality in Linear Time	✅	❌	✅	❌	✅	❌	✅	4
Transformers are Meta-Reinforcement Learners	✅	✅	✅	❌	❌	❌	✅	4
Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots	✅	❌	✅	❌	❌	❌	✅	3
Translatotron 2: High-quality direct speech-to-speech translation with voice preservation	❌	✅	✅	✅	❌	❌	✅	4
UAST: Uncertainty-Aware Siamese Tracking	✅	❌	✅	✅	✅	✅	✅	6
UNIREX: A Unified Learning Framework for Language Model Rationale Extraction	❌	❌	✅	✅	❌	❌	✅	3
Unaligned Supervision for Automatic Music Transcription in The Wild	✅	✅	✅	✅	✅	❌	✅	6
Uncertainty Modeling in Generative Compressed Sensing	✅	✅	✅	❌	✅	❌	✅	5
UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees	✅	✅	❌	❌	❌	❌	✅	3
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy	✅	❌	✅	✅	❌	❌	✅	4
Understanding Contrastive Learning Requires Incorporating Inductive Biases	❌	❌	✅	✅	❌	❌	✅	3
Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information	✅	✅	✅	❌	❌	❌	✅	4
Understanding Doubly Stochastic Clustering	❌	❌	❌	❌	❌	❌	✅	1
Understanding Gradient Descent on the Edge of Stability in Deep Learning	✅	❌	✅	❌	❌	❌	✅	3
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond	❌	✅	✅	✅	❌	❌	✅	4
Understanding Instance-Level Impact of Fairness Constraints	❌	✅	✅	❌	✅	❌	✅	4
Understanding Policy Gradient Algorithms: A Sensitivity-Based Approach	❌	❌	❌	❌	❌	❌	✅	1
Understanding Robust Generalization in Learning Regular Languages	❌	❌	❌	✅	❌	❌	✅	2
Understanding Robust Overfitting of Adversarial Training and Beyond	✅	✅	✅	❌	❌	❌	✅	4
Understanding The Robustness in Vision Transformers	❌	✅	✅	✅	❌	❌	✅	4
Understanding and Improving Knowledge Graph Embedding for Entity Alignment	✅	✅	✅	✅	✅	❌	❌	5
Understanding the unstable convergence of gradient descent	❌	❌	✅	❌	❌	❌	✅	2
UniRank: Unimodal Bandit Algorithms for Online Ranking	✅	❌	✅	❌	❌	❌	❌	2
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces	❌	❌	✅	❌	❌	❌	✅	2
Unified Scaling Laws for Routed Language Models	❌	✅	❌	❌	✅	✅	✅	4
Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models	❌	✅	✅	❌	❌	❌	✅	3
Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows	❌	❌	❌	❌	❌	❌	❌	0
Universal and data-adaptive algorithms for model selection in linear contextual bandits	✅	❌	❌	❌	❌	❌	❌	1
Universality of Winning Tickets: A Renormalization Group Perspective	❌	❌	✅	❌	❌	❌	✅	2
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers	❌	❌	✅	❌	✅	❌	✅	3
Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology	❌	✅	✅	✅	✅	❌	✅	5
Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors	❌	✅	✅	❌	✅	❌	✅	4
Unsupervised Image Representation Learning with Deep Latent Particles	✅	✅	✅	✅	❌	❌	✅	5
Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion	❌	❌	✅	✅	✅	✅	✅	5
Utility Theory for Sequential Decision Making	❌	❌	❌	❌	❌	❌	❌	0
Utilizing Expert Features for Contrastive Learning of Time-Series Representations	❌	✅	✅	✅	❌	❌	✅	4
VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix	✅	✅	✅	❌	✅	❌	✅	5
VLUE: A Multi-Task Multi-Dimension Benchmark for Evaluating Vision-Language Pre-training	❌	✅	✅	✅	✅	❌	✅	5
Validating Causal Inference Methods	❌	❌	✅	❌	❌	❌	✅	2
Value Function based Difference-of-Convex Algorithm for Bilevel Hyperparameter Selection Problems	✅	✅	✅	✅	✅	❌	✅	6
VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis	❌	✅	✅	✅	✅	❌	✅	5
VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty	❌	❌	✅	✅	❌	❌	✅	3
Variational Feature Pyramid Networks	❌	❌	✅	✅	✅	❌	✅	4
Variational Inference for Infinitely Deep Neural Networks	✅	✅	✅	✅	❌	✅	✅	6
Variational Inference with Locally Enhanced Bounds for Hierarchical Models	❌	❌	✅	❌	❌	❌	✅	2
Variational Mixtures of ODEs for Inferring Cellular Gene Expression Dynamics	❌	✅	✅	❌	✅	❌	✅	4
Variational On-the-Fly Personalization	✅	❌	✅	✅	✅	❌	✅	5
Variational Sparse Coding with Learned Thresholding	✅	✅	✅	✅	✅	✅	✅	7
Variational Wasserstein gradient flow	✅	✅	✅	❌	✅	❌	✅	5
Variational nearest neighbor Gaussian process	❌	✅	✅	✅	✅	❌	✅	5
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences	✅	❌	✅	❌	❌	❌	✅	3
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching	✅	✅	✅	❌	❌	❌	✅	4
ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder	✅	✅	✅	❌	✅	❌	✅	5
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Visual Attention Emerges from Recurrent Sparse Reconstruction	❌	❌	✅	✅	❌	❌	✅	3
Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes	❌	✅	✅	❌	✅	❌	✅	4
Weisfeiler-Lehman Meets Gromov-Wasserstein	✅	✅	✅	❌	❌	❌	✅	4
Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy	✅	✅	❌	❌	❌	❌	✅	3
What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us?	❌	❌	✅	❌	✅	❌	✅	3
What Dense Graph Do You Need for Self-Attention?	✅	✅	✅	❌	✅	❌	✅	5
What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?	❌	✅	✅	❌	✅	❌	✅	4
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee	✅	✅	✅	✅	❌	❌	✅	5
When Are Linear Stochastic Bandits Attackable?	✅	❌	❌	❌	❌	❌	✅	2
When and How Mixup Improves Calibration	✅	❌	✅	❌	✅	❌	✅	4
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error	❌	❌	❌	❌	❌	✅	✅	2
Why the Rich Get Richer? On the Balancedness of Random Partition Models	❌	✅	✅	❌	✅	❌	✅	4
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling	❌	✅	✅	❌	❌	❌	✅	3
Wide Neural Networks Forget Less Catastrophically	❌	❌	✅	✅	❌	❌	✅	3
Winning the Lottery Ahead of Time: Efficient Early Network Pruning	✅	✅	✅	❌	✅	❌	✅	5
XAI for Transformers: Better Explanations through Conservative Propagation	❌	✅	✅	❌	❌	❌	✅	3
You Only Cut Once: Boosting Data Augmentation with a Single Cut	❌	✅	✅	❌	❌	❌	✅	3
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for Everyone	❌	✅	✅	✅	✅	❌	✅	5
Zero-Shot Reward Specification via Grounded Natural Language	❌	❌	❌	❌	❌	❌	✅	1
Zero-shot AutoML with Pretrained Models	❌	✅	✅	✅	✅	❌	✅	5
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language	❌	✅	✅	✅	❌	❌	✅	4
pathGCN: Learning General Graph Spatial Operators from Paths	❌	❌	✅	✅	✅	❌	✅	4