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 Learning Representations (ICLR) - 2023

Website:

Venue	Year	Papers	Reproducibility Score Reproducibility Score based on Gundersen et al. (2025)	Documentation Score Global mean is the average score over the seven reproducibility variables for empirical research papers.	% Empirical Percentage of papers that are empirical research vs theoretical research	% Industry Percentage of empirical research papers with at least one author from Industry	Website
ICLR	2023	1573	0.66	4.29	96.82%	51.48%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games	✅	❌	❌	❌	❌	❌	❌	1
$\Lambda$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells	❌	✅	✅	✅	✅	❌	✅	5
$\mathcal{O}$-GNN: incorporating ring priors into molecular modeling	❌	✅	✅	✅	❌	❌	✅	4
$\mathrm{SE}(3)$-Equivariant Attention Networks for Shape Reconstruction in Function Space	❌	❌	✅	❌	❌	❌	✅	2
$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference	❌	✅	✅	❌	❌	❌	✅	3
(Certified!!) Adversarial Robustness for Free!	✅	✅	✅	✅	✅	❌	✅	6
3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction	✅	✅	✅	❌	✅	❌	✅	5
3D Segmenter: 3D Transformer based Semantic Segmentation via 2D Panoramic Distillation	❌	✅	✅	✅	✅	❌	✅	5
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation	❌	✅	✅	✅	✅	❌	✅	5
3D generation on ImageNet	❌	✅	✅	❌	✅	❌	✅	4
A CMDP-within-online framework for Meta-Safe Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification	✅	✅	✅	✅	❌	❌	✅	5
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias	❌	✅	✅	✅	❌	❌	✅	4
A Control-Centric Benchmark for Video Prediction	❌	✅	✅	✅	✅	❌	✅	5
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data	❌	✅	✅	❌	✅	❌	✅	4
A Differential Geometric View and Explainability of GNN on Evolving Graphs	✅	❌	✅	❌	❌	❌	✅	3
A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming	✅	✅	✅	✅	✅	✅	✅	7
A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis	❌	✅	✅	❌	❌	❌	✅	3
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
A General Rank Preserving Framework for Asymmetric Image Retrieval	✅	❌	✅	✅	✅	❌	✅	5
A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps	✅	✅	✅	❌	✅	❌	✅	5
A Higher Precision Algorithm for Computing the $1$-Wasserstein Distance	❌	❌	✅	❌	✅	❌	❌	2
A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond	✅	✅	✅	❌	❌	❌	✅	4
A Kernel Perspective of Skip Connections in Convolutional Networks	❌	❌	✅	❌	❌	❌	✅	2
A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation	❌	❌	✅	❌	✅	❌	✅	3
A Learning Based Hypothesis Test for Harmful Covariate Shift	✅	✅	✅	✅	❌	❌	✅	5
A Message Passing Perspective on Learning Dynamics of Contrastive Learning	❌	✅	✅	❌	❌	❌	✅	3
A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics	❌	✅	✅	✅	✅	❌	✅	5
A Mixture-of-Expert Approach to RL-based Dialogue Management	❌	❌	✅	❌	❌	❌	✅	2
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning	❌	✅	✅	✅	✅	❌	✅	5
A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification	✅	✅	✅	❌	✅	❌	✅	5
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment	✅	❌	✅	❌	❌	❌	✅	3
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
A Non-monotonic Self-terminating Language Model	❌	✅	✅	❌	❌	❌	✅	3
A Primal-Dual Framework for Transformers and Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
A Self-Attention Ansatz for Ab-initio Quantum Chemistry	❌	✅	✅	❌	✅	❌	✅	4
A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search	✅	✅	✅	✅	✅	❌	✅	6
A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles	✅	✅	✅	❌	✅	❌	✅	5
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks	✅	✅	❌	❌	❌	❌	✅	3
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy	✅	❌	✅	✅	❌	❌	✅	4
A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation	❌	✅	✅	✅	✅	❌	✅	5
A Theoretical Framework for Inference and Learning in Predictive Coding Networks	❌	✅	✅	❌	❌	❌	✅	3
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity	✅	❌	✅	✅	❌	❌	✅	4
A Theory of Dynamic Benchmarks	✅	❌	✅	❌	❌	❌	✅	3
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers	❌	❌	✅	✅	❌	❌	✅	3
A Unified Algebraic Perspective on Lipschitz Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games	✅	✅	✅	❌	❌	❌	✅	4
A Unified Framework for Soft Threshold Pruning	✅	✅	✅	❌	❌	❌	✅	4
A VAE for Transformers with Nonparametric Variational Information Bottleneck	❌	✅	✅	✅	✅	❌	✅	5
A View From Somewhere: Human-Centric Face Representations	❌	✅	✅	✅	✅	❌	✅	5
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?	❌	✅	✅	✅	❌	❌	✅	4
A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet	✅	✅	✅	✅	❌	✅	✅	6
A law of adversarial risk, interpolation, and label noise	❌	❌	✅	❌	❌	❌	✅	2
A new characterization of the edge of stability based on a sharpness measure aware of batch gradient distribution	❌	✅	✅	❌	❌	❌	✅	3
A probabilistic framework for task-aligned intra- and inter-area neural manifold estimation	❌	✅	✅	✅	❌	❌	✅	4
A theoretical study of inductive biases in contrastive learning	❌	❌	✅	❌	❌	❌	✅	2
A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.	❌	✅	✅	❌	✅	❌	✅	4
AANG : Automating Auxiliary Learning	✅	✅	✅	✅	✅	❌	✅	6
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks	❌	✅	✅	✅	✅	✅	✅	6
AE-FLOW: Autoencoders with Normalizing Flows for Medical Images Anomaly Detection	❌	❌	✅	✅	❌	❌	✅	3
AGRO: Adversarial discovery of error-prone Groups for Robust Optimization	✅	✅	✅	✅	❌	❌	✅	5
AIM: Adapting Image Models for Efficient Video Action Recognition	✅	✅	✅	✅	✅	❌	✅	6
Accelerated Single-Call Methods for Constrained Min-Max Optimization	❌	✅	❌	❌	✅	✅	✅	4
Accelerating Guided Diffusion Sampling with Splitting Numerical Methods	✅	❌	✅	❌	✅	❌	✅	4
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time	✅	✅	✅	❌	❌	❌	✅	4
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference	✅	✅	✅	❌	❌	❌	✅	4
Accurate Image Restoration with Attention Retractable Transformer	❌	✅	✅	❌	✅	❌	✅	4
Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats	❌	✅	✅	❌	❌	❌	✅	3
Achieve the Minimum Width of Neural Networks for Universal Approximation	❌	❌	❌	❌	❌	❌	❌	0
Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits	✅	❌	✅	❌	❌	❌	✅	3
Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation	✅	❌	❌	❌	❌	❌	✅	2
Actionable Neural Representations: Grid Cells from Minimal Constraints	❌	✅	❌	❌	❌	❌	✅	2
Active Image Indexing	✅	✅	✅	❌	❌	❌	✅	4
Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation	✅	✅	✅	✅	✅	✅	✅	7
Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning	✅	✅	✅	✅	✅	❌	✅	6
Adaptive Optimization in the $\infty$-Width Limit	✅	❌	❌	❌	❌	❌	✅	2
Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data	✅	✅	✅	✅	❌	❌	✅	5
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation	✅	✅	✅	✅	✅	✅	✅	7
Advancing Radiograph Representation Learning with Masked Record Modeling	❌	✅	✅	✅	✅	✅	✅	6
Adversarial Attacks on Adversarial Bandits	❌	❌	❌	❌	❌	❌	✅	1
Adversarial Diversity in Hanabi	✅	✅	✅	❌	❌	❌	✅	4
Adversarial Imitation Learning with Preferences	✅	❌	✅	❌	❌	❌	✅	3
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks	❌	✅	✅	✅	✅	❌	✅	5
Agent-based Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Agnostic Learning of General ReLU Activation Using Gradient Descent	✅	❌	❌	❌	❌	❌	❌	1
Agree to Disagree: Diversity through Disagreement for Better Transferability	✅	✅	✅	✅	✅	❌	✅	6
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness	❌	✅	✅	✅	❌	❌	✅	4
Almost Linear Constant-Factor Sketching for $\ell_1$ and Logistic Regression	✅	✅	✅	❌	❌	❌	✅	4
Alternating Differentiation for Optimization Layers	✅	✅	✅	❌	✅	❌	✅	5
Amortised Invariance Learning for Contrastive Self-Supervision	✅	❌	✅	✅	✅	❌	✅	5
An Adaptive Policy to Employ Sharpness-Aware Minimization	✅	❌	✅	✅	❌	❌	✅	4
An Additive Instance-Wise Approach to Multi-class Model Interpretation	❌	✅	✅	✅	❌	❌	✅	4
An Equal-Size Hard EM Algorithm for Diverse Dialogue Generation	❌	✅	✅	✅	✅	❌	✅	5
An Exact Poly-Time Membership-Queries Algorithm for Extracting a Three-Layer ReLU Network	✅	❌	❌	❌	❌	❌	❌	1
An Extensible Multi-modal Multi-task Object Dataset with Materials	❌	❌	✅	✅	✅	❌	✅	4
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion	❌	✅	✅	❌	✅	❌	✅	4
An efficient encoder-decoder architecture with top-down attention for speech separation	❌	✅	✅	✅	✅	❌	✅	5
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning	✅	✅	✅	❌	❌	❌	✅	4
Analogy-Forming Transformers for Few-Shot 3D Parsing	✅	✅	✅	✅	✅	❌	✅	6
Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel	❌	✅	✅	✅	✅	❌	✅	5
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections	✅	✅	✅	❌	❌	❌	❌	3
Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions	❌	✅	✅	✅	✅	✅	✅	6
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks	❌	✅	✅	✅	✅	❌	✅	5
Any-scale Balanced Samplers for Discrete Space	✅	❌	✅	❌	✅	✅	✅	5
AnyDA: Anytime Domain Adaptation	✅	✅	✅	✅	✅	❌	✅	6
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent	✅	❌	✅	✅	✅	❌	✅	5
Approximate Nearest Neighbor Search through Modern Error-Correcting Codes	✅	✅	✅	❌	❌	❌	✅	4
Approximate Vanishing Ideal Computations at Scale	✅	✅	✅	✅	✅	❌	✅	6
Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks	❌	❌	❌	❌	❌	❌	❌	0
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations	✅	❌	✅	❌	❌	❌	✅	3
Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing	❌	✅	✅	❌	✅	❌	✅	4
Are More Layers Beneficial to Graph Transformers?	❌	✅	✅	❌	❌	❌	✅	3
Artificial Neuronal Ensembles with Learned Context Dependent Gating	❌	❌	✅	❌	✅	❌	✅	3
Ask Me Anything: A simple strategy for prompting language models	✅	✅	✅	✅	✅	❌	❌	5
Associative Memory Augmented Asynchronous Spatiotemporal Representation Learning for Event-based Perception	✅	❌	✅	✅	✅	❌	✅	5
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making	✅	❌	❌	❌	❌	❌	❌	1
Asynchronous Distributed Bilevel Optimization	✅	✅	✅	❌	❌	❌	✅	4
Asynchronous Gradient Play in Zero-Sum Multi-agent Games	✅	❌	❌	❌	❌	❌	✅	2
AudioGen: Textually Guided Audio Generation	❌	❌	✅	❌	✅	❌	✅	3
Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps	✅	✅	✅	✅	✅	❌	✅	6
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation	✅	✅	✅	❌	✅	✅	✅	6
Auto-Encoding Goodness of Fit	✅	✅	✅	✅	❌	❌	✅	5
AutoGT: Automated Graph Transformer Architecture Search	✅	✅	✅	✅	❌	❌	✅	5
AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?	❌	✅	✅	✅	❌	❌	✅	4
Automated Data Augmentations for Graph Classification	✅	✅	✅	✅	❌	❌	✅	5
Automatic Chain of Thought Prompting in Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
Automating Nearest Neighbor Search Configuration with Constrained Optimization	✅	❌	✅	✅	✅	❌	✅	5
Autoregressive Conditional Neural Processes	✅	✅	✅	✅	✅	❌	✅	6
Average Sensitivity of Decision Tree Learning	✅	✅	✅	❌	❌	❌	✅	4
Avoiding spurious correlations via logit correction	✅	✅	✅	✅	❌	❌	✅	5
BALTO: fast tensor program optimization with diversity-based active learning	✅	❌	✅	❌	✅	❌	✅	4
BAYES RISK CTC: CONTROLLABLE CTC ALIGNMENT IN SEQUENCE-TO-SEQUENCE TASKS	❌	✅	✅	✅	✅	❌	✅	5
BC-IRL: Learning Generalizable Reward Functions from Demonstrations	✅	❌	❌	❌	✅	❌	✅	3
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion	❌	✅	✅	✅	❌	❌	✅	4
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection	❌	✅	✅	✅	✅	❌	✅	5
BSTT: A Bayesian Spatial-Temporal Transformer for Sleep Staging	❌	✅	✅	✅	❌	❌	✅	4
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning	✅	✅	✅	❌	❌	❌	✅	4
Backpropagation through Combinatorial Algorithms: Identity with Projection Works	❌	✅	✅	✅	❌	✅	✅	5
Backstepping Temporal Difference Learning	✅	❌	✅	❌	❌	❌	✅	3
Bag of Tricks for Unsupervised Text-to-Speech	✅	❌	✅	✅	✅	❌	✅	5
Basic Binary Convolution Unit for Binarized Image Restoration Network	❌	✅	✅	❌	✅	❌	✅	4
Batch Multivalid Conformal Prediction	✅	✅	✅	✅	❌	❌	✅	5
Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images	❌	✅	✅	✅	❌	❌	✅	4
Bayesian Oracle for bounding information gain in neural encoding models	❌	❌	✅	✅	❌	❌	✅	3
Become a Proficient Player with Limited Data through Watching Pure Videos	✅	✅	✅	❌	❌	❌	✅	4
Behavior Prior Representation learning for Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Behavior Proximal Policy Optimization	✅	✅	✅	❌	❌	❌	✅	4
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition	❌	✅	✅	❌	✅	✅	✅	5
Benchmarking Constraint Inference in Inverse Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware	❌	❌	✅	❌	❌	✅	✅	3
Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models	❌	❌	✅	✅	❌	❌	✅	3
Better Generative Replay for Continual Federated Learning	❌	✅	✅	❌	❌	❌	✅	3
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation	❌	❌	✅	✅	✅	❌	✅	4
Betty: An Automatic Differentiation Library for Multilevel Optimization	✅	✅	✅	✅	❌	❌	✅	5
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD	❌	❌	❌	❌	❌	❌	❌	0
Beyond calibration: estimating the grouping loss of modern neural networks	❌	✅	✅	✅	❌	✅	✅	5
Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients	✅	✅	❌	❌	✅	❌	✅	4
Bias Propagation in Federated Learning	❌	✅	✅	✅	✅	❌	✅	5
Bidirectional Language Models Are Also Few-shot Learners	❌	❌	✅	❌	✅	❌	✅	3
BigVGAN: A Universal Neural Vocoder with Large-Scale Training	❌	✅	✅	✅	✅	❌	✅	5
Binding Language Models in Symbolic Languages	❌	✅	✅	❌	❌	❌	✅	3
Bispectral Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Bit-Pruning: A Sparse Multiplication-Less Dot-Product	❌	✅	✅	❌	❌	❌	✅	3
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts	✅	✅	✅	✅	❌	❌	❌	4
Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference	✅	❌	✅	❌	✅	❌	✅	4
Blurring Diffusion Models	✅	❌	✅	❌	❌	❌	✅	3
Boosting Adversarial Transferability using Dynamic Cues	❌	✅	✅	✅	✅	❌	✅	5
Boosting Causal Discovery via Adaptive Sample Reweighting	✅	✅	✅	❌	✅	❌	✅	5
Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks	✅	✅	✅	❌	✅	❌	✅	5
Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs	❌	✅	✅	✅	❌	❌	✅	4
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint	✅	✅	✅	❌	✅	❌	✅	5
Brain-like representational straightening of natural movies in robust feedforward neural networks	❌	✅	✅	❌	❌	❌	❌	2
BrainBERT: Self-supervised representation learning for intracranial recordings	✅	✅	❌	✅	❌	❌	✅	4
Breaking Correlation Shift via Conditional Invariant Regularizer	✅	❌	✅	✅	❌	❌	✅	4
Bridge the Inference Gaps of Neural Processes via Expectation Maximization	✅	✅	✅	❌	✅	❌	✅	5
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes	✅	✅	✅	✅	❌	❌	✅	5
Bridging the Gap to Real-World Object-Centric Learning	❌	✅	✅	✅	✅	✅	✅	6
Broken Neural Scaling Laws	❌	✅	✅	❌	✅	❌	✅	4
Budgeted Training for Vision Transformer	❌	❌	✅	❌	✅	❌	✅	3
Building Normalizing Flows with Stochastic Interpolants	❌	❌	✅	❌	✅	❌	✅	3
Building a Subspace of Policies for Scalable Continual Learning	✅	✅	✅	❌	✅	❌	✅	5
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning	✅	✅	✅	✅	✅	✅	✅	7
CASR: Generating Complex Sequences with Autoregressive Self-Boost Refinement	✅	✅	✅	✅	✅	❌	✅	6
CFlowNets: Continuous Control with Generative Flow Networks	✅	✅	✅	❌	❌	❌	✅	4
CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning	✅	✅	✅	❌	✅	✅	✅	6
CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks	✅	✅	✅	✅	✅	❌	✅	6
CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Alignment	❌	✅	✅	✅	✅	❌	✅	5
CLIPSep: Learning Text-queried Sound Separation with Noisy Unlabeled Videos	❌	✅	✅	❌	❌	❌	✅	3
CO3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving	✅	❌	✅	❌	❌	❌	✅	3
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations	✅	✅	❌	❌	✅	❌	✅	4
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition	✅	✅	✅	❌	❌	❌	✅	4
CUTS: Neural Causal Discovery from Irregular Time-Series Data	✅	✅	✅	❌	✅	❌	✅	5
Calibrating Sequence likelihood Improves Conditional Language Generation	✅	❌	✅	✅	❌	❌	✅	4
Calibrating Transformers via Sparse Gaussian Processes	❌	✅	✅	✅	✅	❌	✅	5
Calibrating the Rigged Lottery: Making All Tickets Reliable	✅	✅	✅	❌	❌	❌	✅	4
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems	✅	✅	✅	✅	❌	❌	✅	5
Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories	✅	✅	✅	❌	❌	❌	✅	4
Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study	✅	❌	✅	❌	❌	❌	✅	3
Can CNNs Be More Robust Than Transformers?	❌	✅	✅	❌	✅	❌	✅	4
Can Neural Networks Learn Implicit Logic from Physical Reasoning?	❌	❌	❌	❌	❌	❌	❌	0
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN?	❌	❌	✅	❌	✅	✅	✅	4
Can We Find Nash Equilibria at a Linear Rate in Markov Games?	✅	❌	❌	❌	❌	❌	✅	2
Can discrete information extraction prompts generalize across language models?	❌	✅	✅	❌	❌	❌	✅	3
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries	✅	✅	✅	❌	✅	❌	✅	5
Capturing the Motion of Every Joint: 3D Human Pose and Shape Estimation with Independent Tokens	❌	✅	✅	❌	✅	❌	✅	4
Causal Balancing for Domain Generalization	✅	✅	✅	✅	✅	❌	✅	6
Causal Confusion and Reward Misidentification in Preference-Based Reward Learning	✅	✅	❌	✅	❌	❌	✅	4
Causal Estimation for Text Data with (Apparent) Overlap Violations	❌	✅	❌	✅	❌	❌	✅	3
Causal Imitation Learning via Inverse Reinforcement Learning	✅	✅	✅	❌	❌	❌	❌	3
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning	❌	✅	✅	❌	❌	❌	✅	3
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems	✅	✅	✅	❌	✅	✅	✅	6
Causality Compensated Attention for Contextual Biased Visual Recognition	❌	❌	✅	✅	❌	❌	✅	3
Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication	✅	✅	✅	❌	✅	❌	✅	5
Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation	✅	❌	✅	✅	✅	❌	✅	5
Certified Training: Small Boxes are All You Need	❌	✅	✅	❌	❌	❌	❌	2
Characteristic Neural Ordinary Differential Equation	✅	✅	✅	❌	✅	❌	✅	5
Characterizing intrinsic compositionality in transformers with Tree Projections	✅	❌	✅	✅	❌	❌	✅	4
Characterizing the Influence of Graph Elements	❌	✅	✅	✅	❌	❌	❌	3
Characterizing the spectrum of the NTK via a power series expansion	❌	✅	✅	❌	❌	❌	✅	3
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization	❌	✅	✅	✅	❌	❌	✅	4
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning	✅	❌	❌	✅	✅	❌	✅	4
ChiroDiff: Modelling chirographic data with Diffusion Models	❌	✅	✅	✅	❌	❌	✅	4
ChordMixer: A Scalable Neural Attention Model for Sequences with Different Length	❌	✅	✅	✅	✅	❌	✅	5
Choreographer: Learning and Adapting Skills in Imagination	✅	✅	✅	✅	✅	❌	✅	6
CircNet: Meshing 3D Point Clouds with Circumcenter Detection	❌	✅	✅	❌	❌	❌	✅	3
CktGNN: Circuit Graph Neural Network for Electronic Design Automation	❌	✅	✅	❌	✅	❌	✅	4
Classically Approximating Variational Quantum Machine Learning with Random Fourier Features	✅	✅	✅	❌	❌	❌	✅	4
Clean-image Backdoor: Attacking Multi-label Models with Poisoned Labels Only	✅	❌	✅	❌	❌	❌	❌	2
Clifford Neural Layers for PDE Modeling	✅	✅	❌	❌	✅	❌	✅	4
CoRTX: Contrastive Framework for Real-time Explanation	✅	✅	✅	✅	✅	❌	✅	6
Code Translation with Compiler Representations	❌	❌	✅	❌	✅	❌	✅	3
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code	❌	❌	✅	✅	✅	❌	✅	4
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis	❌	✅	✅	❌	✅	❌	✅	4
CodeT: Code Generation with Generated Tests	❌	✅	✅	❌	❌	❌	✅	3
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers	❌	✅	✅	❌	✅	❌	✅	4
Collaborative Pure Exploration in Kernel Bandit	✅	❌	❌	❌	✅	❌	✅	3
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Combinatorial Pure Exploration of Causal Bandits	✅	❌	❌	❌	❌	❌	❌	1
Combinatorial-Probabilistic Trade-Off: P-Values of Community Properties Test in the Stochastic Block Models	❌	❌	❌	❌	❌	❌	✅	1
Competitive Physics Informed Networks	❌	✅	✅	✅	✅	❌	✅	5
Complexity-Based Prompting for Multi-step Reasoning	❌	✅	✅	✅	❌	❌	✅	4
Composing Ensembles of Pre-trained Models via Iterative Consensus	❌	❌	✅	❌	✅	❌	✅	3
Composing Task Knowledge With Modular Successor Feature Approximators	❌	❌	✅	❌	❌	❌	✅	2
Composite Slice Transformer: An Efficient Transformer with Composition of Multi-Scale Multi-Range Attentions	❌	❌	✅	✅	✅	❌	✅	4
Compositional Law Parsing with Latent Random Functions	❌	✅	✅	✅	✅	❌	✅	5
Compositional Prompt Tuning with Motion Cues for Open-vocabulary Video Relation Detection	❌	✅	✅	✅	❌	❌	✅	4
Compositional Semantic Parsing with Large Language Models	❌	❌	✅	✅	❌	❌	✅	3
Compositional Task Representations for Large Language Models	❌	✅	✅	✅	❌	❌	✅	4
Compositionality with Variation Reliably Emerges in Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Compressing multidimensional weather and climate data into neural networks	❌	✅	✅	❌	✅	❌	✅	4
Computational Language Acquisition with Theory of Mind	❌	✅	✅	✅	❌	❌	✅	4
Computing all Optimal Partial Transports	❌	✅	✅	❌	✅	❌	✅	4
Concept Gradient: Concept-based Interpretation Without Linear Assumption	❌	✅	✅	✅	❌	❌	✅	4
Concept-level Debugging of Part-Prototype Networks	✅	✅	✅	❌	✅	❌	✅	5
Conditional Antibody Design as 3D Equivariant Graph Translation	❌	✅	✅	✅	✅	❌	✅	5
Conditional Positional Encodings for Vision Transformers	✅	✅	✅	✅	✅	❌	✅	6
Confidence Estimation Using Unlabeled Data	✅	❌	✅	✅	❌	❌	✅	4
Confidence-Based Feature Imputation for Graphs with Partially Known Features	✅	✅	✅	✅	✅	✅	✅	7
Confidence-Conditioned Value Functions for Offline Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Confidential-PROFITT: Confidential PROof of FaIr Training of Trees	✅	✅	✅	✅	✅	❌	✅	6
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization	✅	✅	✅	❌	❌	❌	✅	4
Consolidator: Mergable Adapter with Group Connections for Visual Adaptation	❌	✅	✅	✅	❌	❌	✅	4
Constraining Representations Yields Models That Know What They Don't Know	✅	❌	✅	✅	❌	❌	✅	4
Constructive TT-representation of the tensors given as index interaction functions with applications	✅	✅	❌	❌	❌	❌	❌	2
Context-enriched molecule representations improve few-shot drug discovery	❌	✅	✅	✅	✅	❌	✅	5
Contextual Convolutional Networks	❌	✅	✅	✅	✅	❌	✅	5
Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining	❌	✅	✅	✅	✅	❌	✅	5
Contextual bandits with concave rewards, and an application to fair ranking	✅	❌	✅	❌	❌	❌	✅	3
Continual Pre-training of Language Models	❌	✅	✅	❌	❌	❌	✅	3
Continual Transformers: Redundancy-Free Attention for Online Inference	❌	✅	✅	✅	✅	❌	✅	5
Continual Unsupervised Disentangling of Self-Organizing Representations	❌	✅	✅	❌	❌	❌	✅	3
Continual evaluation for lifelong learning: Identifying the stability gap	❌	✅	✅	✅	❌	❌	✅	4
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization	✅	❌	❌	❌	❌	❌	✅	2
Continuous PDE Dynamics Forecasting with Implicit Neural Representations	✅	✅	✅	❌	✅	❌	✅	5
Continuous pseudo-labeling from the start	✅	❌	✅	✅	✅	❌	✅	5
Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins	❌	✅	✅	✅	✅	✅	✅	6
Continuous-time identification of dynamic state-space models by deep subspace encoding	❌	✅	✅	✅	❌	❌	✅	4
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond	❌	✅	✅	✅	✅	❌	✅	5
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning	❌	✅	✅	✅	✅	❌	✅	5
Contrastive Audio-Visual Masked Autoencoder	❌	✅	✅	✅	✅	❌	✅	5
Contrastive Corpus Attribution for Explaining Representations	❌	✅	✅	✅	❌	❌	✅	4
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions	❌	❌	✅	✅	❌	❌	✅	3
Contrastive Learning for Unsupervised Domain Adaptation of Time Series	❌	✅	✅	✅	✅	❌	✅	5
Contrastive Meta-Learning for Partially Observable Few-Shot Learning	✅	✅	✅	✅	✅	❌	✅	6
Copy is All You Need	✅	✅	✅	✅	✅	❌	✅	6
Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation	✅	✅	✅	❌	❌	❌	✅	4
Corrupted Image Modeling for Self-Supervised Visual Pre-Training	❌	❌	✅	✅	✅	❌	✅	4
Coupled Multiwavelet Operator Learning for Coupled Differential Equations	❌	✅	✅	❌	✅	❌	✅	4
Coverage-centric Coreset Selection for High Pruning Rates	✅	✅	✅	✅	✅	❌	✅	6
CrAM: A Compression-Aware Minimizer	✅	✅	✅	✅	✅	✅	✅	7
Critic Sequential Monte Carlo	✅	✅	✅	✅	✅	❌	✅	6
Cross-Layer Retrospective Retrieving via Layer Attention	✅	✅	✅	✅	✅	❌	✅	6
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification	❌	✅	✅	❌	❌	❌	✅	3
Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots	❌	✅	✅	❌	✅	❌	✅	4
Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation	❌	❌	✅	✅	✅	❌	✅	4
Cycle-consistent Masked AutoEncoder for Unsupervised Domain Generalization	❌	❌	✅	✅	❌	❌	✅	3
D4AM: A General Denoising Framework for Downstream Acoustic Models	✅	✅	✅	✅	❌	❌	✅	5
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory	✅	❌	❌	❌	✅	❌	✅	3
DAG Learning on the Permutahedron	✅	✅	✅	❌	✅	❌	✅	5
DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks	✅	❌	✅	❌	✅	❌	✅	4
DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity	✅	✅	✅	❌	✅	✅	✅	6
DAVA: Disentangling Adversarial Variational Autoencoder	✅	✅	✅	❌	❌	❌	✅	4
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection	❌	❌	✅	✅	✅	❌	✅	4
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability	❌	✅	✅	✅	❌	❌	✅	4
DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
DELTA: DEGRADATION-FREE FULLY TEST-TIME ADAPTATION	✅	✅	✅	❌	❌	❌	✅	4
DENSE RGB SLAM WITH NEURAL IMPLICIT MAPS	❌	✅	✅	❌	✅	❌	✅	4
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems	❌	✅	✅	❌	✅	✅	✅	5
DFPC: Data flow driven pruning of coupled channels without data.	✅	✅	✅	❌	✅	✅	✅	6
DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline	✅	❌	✅	✅	✅	❌	✅	5
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion	✅	✅	✅	✅	✅	❌	✅	6
DINO as a von Mises-Fisher mixture model	❌	❌	✅	✅	✅	❌	✅	4
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection	❌	❌	✅	✅	✅	❌	✅	4
DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images	✅	✅	✅	❌	❌	❌	✅	4
DamoFD: Digging into Backbone Design on Face Detection	✅	✅	✅	✅	✅	❌	✅	6
Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer	❌	✅	✅	✅	❌	❌	✅	4
Data Valuation Without Training of a Model	❌	✅	✅	✅	✅	❌	✅	5
Data augmentation alone can improve adversarial training	✅	✅	✅	✅	✅	✅	✅	7
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity	✅	✅	✅	❌	❌	❌	✅	4
Dataless Knowledge Fusion by Merging Weights of Language Models	✅	✅	✅	✅	❌	❌	✅	5
Dataset Pruning: Reducing Training Data by Examining Generalization Influence	✅	❌	✅	❌	✅	❌	✅	4
DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics	❌	✅	❌	❌	✅	❌	✅	3
De Novo Molecular Generation via Connection-aware Motif Mining	✅	✅	✅	❌	✅	❌	✅	5
DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing	❌	✅	✅	✅	❌	❌	✅	4
DeCap: Decoding CLIP Latents for Zero-Shot Captioning via Text-Only Training	❌	✅	✅	✅	✅	❌	✅	5
DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases	❌	✅	✅	✅	❌	❌	✅	4
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models	✅	✅	✅	❌	❌	❌	✅	4
Decision S4: Efficient Sequence-Based RL via State Spaces Layers	✅	❌	✅	❌	✅	❌	✅	4
Decision Transformer under Random Frame Dropping	✅	❌	✅	❌	❌	❌	✅	3
Decompose to Generalize: Species-Generalized Animal Pose Estimation	✅	❌	✅	✅	❌	❌	✅	4
Decomposed Prompting: A Modular Approach for Solving Complex Tasks	✅	✅	✅	✅	❌	❌	✅	5
Decompositional Generation Process for Instance-Dependent Partial Label Learning	✅	✅	✅	✅	❌	❌	✅	5
Deconstructing Distributions: A Pointwise Framework of Learning	❌	❌	✅	❌	❌	❌	✅	2
Decoupled Training for Long-Tailed Classification With Stochastic Representations	✅	✅	✅	✅	✅	❌	✅	6
Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths	❌	✅	✅	✅	✅	❌	✅	5
Deep Ensembles for Graphs with Higher-order Dependencies	❌	✅	✅	✅	❌	✅	✅	5
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models	❌	✅	✅	❌	✅	❌	✅	4
Deep Generative Symbolic Regression	✅	✅	✅	✅	✅	❌	✅	6
Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization	✅	✅	✅	✅	❌	❌	✅	5
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?	❌	❌	✅	❌	❌	❌	✅	2
Deep Learning on Implicit Neural Representations of Shapes	❌	✅	✅	✅	✅	❌	✅	5
Deep Ranking Ensembles for Hyperparameter Optimization	✅	✅	✅	✅	❌	❌	✅	5
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis	✅	✅	✅	✅	❌	❌	✅	5
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation	✅	❌	✅	❌	❌	❌	✅	3
Deep Variational Implicit Processes	❌	✅	✅	❌	❌	❌	✅	3
Defending against Adversarial Audio via Diffusion Model	❌	✅	✅	✅	✅	❌	✅	5
Deja Vu: Continual Model Generalization for Unseen Domains	❌	✅	✅	❌	❌	❌	✅	3
Delving into Semantic Scale Imbalance	✅	❌	✅	✅	✅	❌	✅	5
Denoising Diffusion Error Correction Codes	✅	✅	✅	❌	✅	❌	✅	5
Denoising Diffusion Samplers	✅	❌	✅	❌	✅	❌	✅	4
Denoising Masked Autoencoders Help Robust Classification	❌	✅	✅	✅	❌	❌	✅	4
DensePure: Understanding Diffusion Models for Adversarial Robustness	✅	✅	✅	✅	❌	❌	✅	5
Depth Separation with Multilayer Mean-Field Networks	❌	❌	✅	❌	❌	❌	✅	2
DepthFL : Depthwise Federated Learning for Heterogeneous Clients	✅	❌	✅	❌	❌	❌	✅	3
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling	❌	✅	✅	✅	✅	❌	✅	5
Deterministic training of generative autoencoders using invertible layers	✅	✅	✅	✅	✅	❌	✅	6
DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics	✅	❌	❌	❌	✅	❌	✅	3
DiGress: Discrete Denoising diffusion for graph generation	✅	✅	✅	✅	❌	❌	❌	4
Diagnosing and Rectifying Vision Models using Language	❌	✅	✅	✅	❌	❌	✅	4
Dichotomy of Control: Separating What You Can Control from What You Cannot	✅	✅	✅	❌	✅	❌	✅	5
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking	✅	✅	✅	✅	✅	✅	✅	7
DiffEdit: Diffusion-based semantic image editing with mask guidance	❌	❌	✅	✅	✅	❌	✅	4
DiffMimic: Efficient Motion Mimicking with Differentiable Physics	✅	✅	✅	❌	✅	❌	✅	5
Differentiable Gaussianization Layers for Inverse Problems Regularized by Deep Generative Models	✅	✅	✅	✅	✅	❌	✅	6
Differentiable Mathematical Programming for Object-Centric Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model	✅	❌	❌	❌	❌	❌	❌	1
Differentially Private Adaptive Optimization with Delayed Preconditioners	✅	✅	✅	❌	❌	❌	✅	4
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models	❌	✅	✅	❌	✅	✅	✅	5
DiffusER: Diffusion via Edit-based Reconstruction	❌	❌	✅	✅	✅	❌	✅	4
Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Diffusion Models Already Have A Semantic Latent Space	✅	✅	✅	❌	✅	❌	✅	5
Diffusion Models for Causal Discovery via Topological Ordering	✅	✅	✅	❌	❌	❌	✅	4
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Diffusion Posterior Sampling for General Noisy Inverse Problems	✅	✅	✅	✅	✅	❌	✅	6
Diffusion Probabilistic Fields	✅	❌	✅	❌	✅	❌	✅	4
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem	✅	✅	✅	❌	✅	❌	✅	5
Diffusion-GAN: Training GANs with Diffusion	✅	❌	✅	❌	✅	❌	✅	4
Diffusion-based Image Translation using disentangled style and content representation	✅	✅	✅	❌	✅	❌	✅	5
Dilated convolution with learnable spacings	✅	✅	✅	✅	✅	❌	✅	6
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs	❌	✅	✅	❌	✅	❌	✅	4
Dirichlet-based Uncertainty Calibration for Active Domain Adaptation	✅	✅	✅	✅	✅	❌	✅	6
Discovering Evolution Strategies via Meta-Black-Box Optimization	✅	✅	✅	❌	✅	❌	✅	5
Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data	❌	✅	✅	✅	✅	❌	✅	5
Discovering Informative and Robust Positives for Video Domain Adaptation	✅	❌	✅	❌	✅	❌	✅	4
Discovering Latent Knowledge in Language Models Without Supervision	✅	✅	✅	❌	❌	❌	✅	4
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality	✅	❌	✅	❌	❌	❌	✅	3
Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation	✅	❌	✅	✅	✅	❌	✅	5
Discrete Predictor-Corrector Diffusion Models for Image Synthesis	❌	❌	✅	❌	✅	❌	✅	3
Disentanglement of Correlated Factors via Hausdorff Factorized Support	✅	✅	✅	✅	❌	✅	✅	6
Disentanglement with Biological Constraints: A Theory of Functional Cell Types	❌	✅	✅	❌	❌	❌	✅	3
Disentangling Learning Representations with Density Estimation	❌	✅	✅	✅	✅	❌	✅	5
Disentangling the Mechanisms Behind Implicit Regularization in SGD	❌	✅	✅	❌	✅	❌	✅	4
Disparate Impact in Differential Privacy from Gradient Misalignment	✅	✅	✅	✅	✅	✅	✅	7
Distilling Cognitive Backdoor Patterns within an Image	✅	✅	✅	❌	✅	❌	✅	5
Distilling Model Failures as Directions in Latent Space	❌	✅	✅	✅	✅	✅	✅	6
Distributed Differential Privacy in Multi-Armed Bandits	✅	✅	✅	❌	❌	❌	✅	4
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees	✅	✅	✅	❌	✅	❌	✅	5
Distributional Meta-Gradient Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
Distributionally Robust Post-hoc Classifiers under Prior Shifts	❌	✅	✅	✅	❌	❌	✅	4
Distributionally Robust Recourse Action	✅	✅	✅	❌	❌	✅	✅	5
Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement	✅	✅	✅	❌	❌	❌	✅	4
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors	❌	✅	✅	❌	✅	❌	✅	4
Do We Really Need Complicated Model Architectures For Temporal Networks?	❌	✅	✅	✅	✅	✅	✅	6
DocPrompting: Generating Code by Retrieving the Docs	❌	✅	✅	✅	✅	❌	✅	5
Does Deep Learning Learn to Abstract? A Systematic Probing Framework	❌	✅	✅	✅	✅	❌	✅	5
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?	✅	✅	✅	✅	❌	❌	✅	5
Does Zero-Shot Reinforcement Learning Exist?	✅	✅	✅	❌	❌	❌	✅	4
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach	✅	❌	✅	✅	✅	❌	✅	5
Domain Generalization via Heckman-type Selection Models	✅	✅	✅	✅	❌	❌	✅	5
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation	❌	✅	✅	❌	❌	❌	✅	3
Don’t fear the unlabelled: safe semi-supervised learning via debiasing	❌	✅	✅	✅	❌	❌	✅	4
Don’t forget the nullspace! Nullspace occupancy as a mechanism for out of distribution failure	✅	❌	✅	✅	❌	❌	✅	4
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness	❌	✅	✅	✅	✅	❌	✅	5
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs	❌	✅	✅	✅	❌	✅	✅	5
DreamFusion: Text-to-3D using 2D Diffusion	✅	❌	✅	❌	✅	❌	✅	4
DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training	❌	✅	✅	✅	✅	✅	✅	6
Dual Algorithmic Reasoning	✅	❌	✅	✅	❌	❌	✅	4
Dual Diffusion Implicit Bridges for Image-to-Image Translation	✅	✅	✅	❌	❌	❌	❌	3
Dual Student Networks for Data-Free Model Stealing	✅	❌	✅	❌	❌	❌	✅	3
DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Manipulation	❌	❌	✅	❌	✅	❌	✅	3
DySR: Adaptive Super-Resolution via Algorithm and System Co-design	✅	✅	✅	❌	✅	❌	✅	5
DynaMS: Dyanmic Margin Selection for Efficient Deep Learning	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting	✅	✅	✅	❌	❌	❌	✅	4
E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking	✅	❌	✅	✅	❌	❌	✅	4
EA-HAS-Bench: Energy-aware Hyperparameter and Architecture Search Benchmark	✅	✅	✅	✅	✅	❌	✅	6
EAGLE: Large-scale Learning of Turbulent Fluid Dynamics with Mesh Transformers	❌	❌	✅	✅	✅	❌	✅	4
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data	✅	✅	✅	❌	✅	❌	✅	5
ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation	✅	✅	✅	❌	✅	❌	✅	5
ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret	✅	✅	✅	❌	❌	✅	✅	5
ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure	✅	✅	✅	✅	✅	❌	✅	6
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model	✅	❌	✅	❌	✅	❌	✅	4
EVA3D: Compositional 3D Human Generation from 2D Image Collections	❌	✅	✅	❌	❌	❌	❌	2
EVC: Towards Real-Time Neural Image Compression with Mask Decay	❌	✅	✅	❌	✅	✅	✅	5
Easy Differentially Private Linear Regression	✅	✅	✅	❌	❌	❌	✅	4
Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis	❌	❌	✅	❌	✅	❌	✅	3
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks	✅	✅	✅	✅	✅	❌	✅	6
Editing models with task arithmetic	❌	✅	✅	✅	❌	❌	✅	4
Effective Self-supervised Pre-training on Low-compute Networks without Distillation	❌	✅	✅	✅	❌	❌	✅	4
Effective passive membership inference attacks in federated learning against overparameterized models	❌	❌	✅	✅	❌	❌	✅	3
Effectively Modeling Time Series with Simple Discrete State Spaces	✅	✅	✅	✅	✅	❌	✅	6
Effects of Graph Convolutions in Multi-layer Networks	❌	❌	✅	❌	✅	❌	✅	3
Efficient Attention via Control Variates	✅	✅	✅	✅	✅	❌	✅	6
Efficient Certified Training and Robustness Verification of Neural ODEs	❌	✅	✅	❌	✅	✅	✅	5
Efficient Conditionally Invariant Representation Learning	✅	✅	✅	✅	❌	❌	✅	5
Efficient Deep Reinforcement Learning Requires Regulating Overfitting	✅	✅	✅	✅	❌	❌	✅	5
Efficient Discrete Multi Marginal Optimal Transport Regularization	✅	✅	✅	✅	✅	❌	✅	6
Efficient Edge Inference by Selective Query	✅	✅	✅	✅	✅	❌	✅	6
Efficient Federated Domain Translation	✅	❌	✅	❌	✅	❌	✅	4
Efficient Model Updates for Approximate Unlearning of Graph-Structured Data	✅	✅	✅	✅	✅	❌	✅	6
Efficient Offline Policy Optimization with a Learned Model	✅	✅	✅	❌	✅	❌	✅	5
Efficient Planning in a Compact Latent Action Space	✅	✅	✅	❌	✅	❌	✅	5
Efficient approximation of neural population structure and correlations with probabilistic circuits	❌	✅	✅	✅	❌	❌	✅	4
Efficient recurrent architectures through activity sparsity and sparse back-propagation through time	❌	✅	✅	❌	❌	❌	✅	3
Efficiently Computing Nash Equilibria in Adversarial Team Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Efficiently Controlling Multiple Risks with Pareto Testing	✅	✅	✅	✅	❌	❌	✅	5
Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement	❌	✅	✅	✅	✅	❌	✅	5
Emergence of Maps in the Memories of Blind Navigation Agents	❌	❌	✅	❌	❌	❌	✅	2
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task	✅	✅	✅	✅	❌	❌	✅	5
Empowering Graph Representation Learning with Test-Time Graph Transformation	✅	✅	✅	✅	✅	❌	✅	6
Empowering Networks With Scale and Rotation Equivariance Using A Similarity Convolution	✅	❌	✅	❌	❌	❌	✅	3
Encoding Recurrence into Transformers	❌	❌	✅	✅	✅	❌	✅	4
Energy-Based Test Sample Adaptation for Domain Generalization	✅	✅	✅	✅	✅	❌	✅	6
Energy-Inspired Self-Supervised Pretraining for Vision Models	✅	❌	✅	✅	❌	❌	✅	4
Energy-based Out-of-Distribution Detection for Graph Neural Networks	❌	✅	✅	✅	✅	✅	✅	6
Enhancing Meta Learning via Multi-Objective Soft Improvement Functions	✅	❌	✅	✅	✅	❌	✅	5
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems	❌	✅	❌	✅	✅	✅	✅	5
Ensuring DNN Solution Feasibility for Optimization Problems with Linear Constraints	✅	❌	✅	❌	✅	❌	✅	4
Equal Improvability: A New Fairness Notion Considering the Long-term Impact	✅	✅	✅	❌	❌	❌	✅	4
EquiMod: An Equivariance Module to Improve Visual Instance Discrimination	❌	✅	✅	✅	❌	❌	✅	4
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs	❌	✅	✅	✅	✅	❌	✅	5
Equivariance-aware Architectural Optimization of Neural Networks	✅	❌	✅	✅	❌	❌	✅	4
Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learning	✅	✅	❌	❌	✅	❌	✅	4
Equivariant Energy-Guided SDE for Inverse Molecular Design	✅	✅	✅	✅	❌	❌	✅	5
Equivariant Hypergraph Diffusion Neural Operators	✅	✅	✅	✅	✅	❌	✅	6
Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug Design	✅	✅	✅	✅	❌	❌	✅	5
Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning	✅	✅	✅	❌	❌	❌	✅	4
Estimating individual treatment effects under unobserved confounding using binary instruments	✅	✅	✅	✅	✅	❌	✅	6
Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation	❌	✅	✅	✅	✅	✅	✅	6
Evaluating Long-Term Memory in 3D Mazes	❌	✅	❌	✅	❌	❌	✅	3
Evaluating Representations with Readout Model Switching	✅	❌	✅	✅	❌	❌	✅	4
Everybody Needs Good Neighbours: An Unsupervised Locality-based Method for Bias Mitigation	❌	✅	✅	✅	✅	✅	✅	6
Evidential Uncertainty and Diversity Guided Active Learning for Scene Graph Generation	✅	❌	✅	✅	❌	❌	✅	4
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems	✅	❌	✅	✅	✅	❌	✅	5
Evolving Populations of Diverse RL Agents with MAP-Elites	✅	✅	✅	❌	❌	❌	✅	4
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods	✅	❌	❌	❌	❌	❌	✅	2
Explaining RL Decisions with Trajectories	✅	❌	✅	❌	✅	❌	✅	4
Explaining Temporal Graph Models through an Explorer-Navigator Framework	✅	✅	✅	✅	✅	❌	✅	6
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation	❌	✅	✅	✅	✅	❌	✅	5
Explicitly Minimizing the Blur Error of Variational Autoencoders	❌	❌	✅	❌	❌	❌	✅	2
Exploring Active 3D Object Detection from a Generalization Perspective	✅	✅	✅	✅	❌	❌	✅	5
Exploring Low-Rank Property in Multiple Instance Learning for Whole Slide Image Classification	❌	✅	✅	✅	✅	❌	✅	5
Exploring Temporally Dynamic Data Augmentation for Video Recognition	❌	✅	✅	✅	✅	❌	✅	5
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders	❌	❌	✅	✅	✅	❌	✅	4
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness	❌	✅	✅	✅	✅	❌	✅	5
Exploring perceptual straightness in learned visual representations	❌	✅	✅	❌	❌	✅	❌	3
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping	✅	✅	✅	✅	✅	❌	✅	6
Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms	✅	❌	❌	❌	❌	❌	❌	1
ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion	❌	✅	✅	✅	✅	✅	✅	6
Expressive Monotonic Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Extracting Robust Models with Uncertain Examples	✅	✅	✅	✅	✅	❌	✅	6
Extreme Q-Learning: MaxEnt RL without Entropy	✅	✅	✅	❌	❌	❌	✅	4
Extremely Simple Activation Shaping for Out-of-Distribution Detection	✅	✅	✅	✅	✅	❌	✅	6
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data	✅	✅	✅	❌	✅	❌	✅	5
FIGARO: Controllable Music Generation using Learned and Expert Features	✅	✅	✅	✅	✅	❌	✅	6
FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities	❌	✅	✅	❌	✅	✅	✅	5
FIT: A Metric for Model Sensitivity	❌	✅	✅	❌	✅	❌	✅	4
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
Factorized Fourier Neural Operators	❌	✅	✅	✅	✅	❌	✅	5
FaiREE: fair classification with finite-sample and distribution-free guarantee	✅	✅	✅	✅	❌	❌	✅	5
Fair Attribute Completion on Graph with Missing Attributes	✅	✅	✅	❌	❌	❌	✅	4
FairGBM: Gradient Boosting with Fairness Constraints	✅	✅	✅	✅	✅	❌	✅	6
Fairness and Accuracy under Domain Generalization	✅	✅	✅	✅	✅	✅	✅	7
Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes	✅	❌	✅	❌	❌	❌	✅	3
Fake It Until You Make It : Towards Accurate Near-Distribution Novelty Detection	❌	✅	✅	❌	❌	❌	✅	3
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems	✅	✅	✅	✅	❌	❌	✅	5
Fast Nonlinear Vector Quantile Regression	❌	✅	✅	✅	✅	❌	✅	5
Fast Sampling of Diffusion Models with Exponential Integrator	✅	✅	✅	❌	❌	❌	✅	4
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search	✅	✅	✅	✅	✅	❌	✅	6
FastFill: Efficient Compatible Model Update	❌	✅	✅	✅	❌	❌	✅	4
Faster Gradient-Free Methods for Escaping Saddle Points	✅	❌	❌	❌	✅	❌	✅	3
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games	✅	❌	❌	❌	❌	❌	❌	1
Faster federated optimization under second-order similarity	✅	✅	✅	❌	❌	❌	✅	4
Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Feature selection and low test error in shallow low-rotation ReLU networks	❌	❌	✅	❌	❌	❌	✅	2
FedDAR: Federated Domain-Aware Representation Learning	✅	✅	✅	✅	❌	❌	✅	5
FedExP: Speeding Up Federated Averaging via Extrapolation	✅	✅	✅	❌	❌	❌	✅	4
FedFA: Federated Feature Augmentation	✅	✅	✅	✅	✅	❌	✅	6
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy	✅	❌	✅	❌	✅	❌	✅	4
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach	✅	✅	✅	✅	❌	❌	✅	5
Federated Learning from Small Datasets	✅	✅	✅	❌	❌	❌	✅	4
Federated Nearest Neighbor Machine Translation	❌	✅	✅	✅	✅	❌	✅	5
Federated Neural Bandits	✅	✅	✅	❌	✅	❌	✅	5
Few-Shot Domain Adaptation For End-to-End Communication	✅	✅	❌	✅	✅	❌	✅	5
Few-shot Backdoor Attacks via Neural Tangent Kernels	✅	✅	✅	✅	❌	❌	✅	5
Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning	✅	✅	✅	❌	❌	❌	✅	4
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification	✅	✅	✅	✅	✅	❌	✅	6
Filter-Recovery Network for Multi-Speaker Audio-Visual Speech Separation	❌	❌	✅	✅	❌	❌	✅	3
Finding Actual Descent Directions for Adversarial Training	✅	❌	✅	✅	❌	❌	✅	4
Finding the Global Semantic Representation in GAN through Fréchet Mean	❌	❌	✅	❌	❌	❌	✅	2
First Steps Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains	❌	❌	❌	❌	❌	❌	❌	0
Fisher-Legendre (FishLeg) optimization of deep neural networks	✅	✅	✅	❌	✅	❌	✅	5
Flow Annealed Importance Sampling Bootstrap	✅	✅	❌	✅	✅	❌	✅	5
Flow Matching for Generative Modeling	❌	❌	✅	✅	❌	❌	✅	3
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow	✅	✅	✅	❌	❌	❌	✅	4
FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation	❌	✅	❌	❌	✅	❌	✅	3
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs	✅	✅	✅	✅	✅	❌	✅	6
Fooling SHAP with Stealthily Biased Sampling	✅	✅	✅	✅	❌	❌	✅	5
Formal Mathematics Statement Curriculum Learning	❌	✅	✅	✅	✅	❌	✅	5
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions	✅	❌	✅	❌	❌	❌	❌	2
Free Lunch for Domain Adversarial Training: Environment Label Smoothing	❌	✅	✅	✅	✅	❌	✅	5
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
From $t$-SNE to UMAP with contrastive learning	✅	✅	✅	✅	✅	✅	✅	7
From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data	❌	❌	✅	❌	❌	❌	✅	2
Function-Consistent Feature Distillation	❌	✅	✅	✅	✅	❌	✅	5
Function-space regularized Rényi divergences	❌	❌	✅	❌	❌	❌	✅	2
Fundamental Limits in Formal Verification of Message-Passing Neural Networks	❌	❌	❌	❌	❌	❌	❌	0
Fundamental limits on the robustness of image classifiers	✅	❌	✅	❌	❌	❌	❌	2
FunkNN: Neural Interpolation for Functional Generation	❌	✅	✅	❌	✅	❌	✅	4
Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation	✅	✅	✅	✅	✅	❌	✅	6
GAIN: On the Generalization of Instructional Action Understanding	❌	✅	✅	❌	❌	❌	✅	3
GAMR: A Guided Attention Model for (visual) Reasoning	✅	❌	✅	✅	❌	❌	✅	4
GEASS: Neural causal feature selection for high-dimensional biological data	❌	❌	✅	❌	❌	❌	✅	2
GFlowNets and variational inference	❌	✅	❌	❌	❌	❌	✅	2
GLM-130B: An Open Bilingual Pre-trained Model	❌	✅	✅	✅	✅	❌	✅	5
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks	✅	❌	✅	❌	✅	✅	✅	5
GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure	❌	✅	✅	✅	✅	❌	✅	5
GOOD: Exploring geometric cues for detecting objects in an open world	❌	✅	✅	✅	❌	❌	✅	4
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation	❌	✅	✅	❌	✅	❌	✅	4
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints	✅	✅	✅	❌	✅	❌	✅	5
GReTo: Remedying dynamic graph topology-task discordance via target homophily	❌	✅	✅	❌	❌	❌	✅	3
GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis	❌	✅	✅	❌	✅	❌	✅	4
General Neural Gauge Fields	✅	✅	✅	❌	❌	❌	✅	4
Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses	❌	❌	✅	❌	❌	❌	✅	2
Generalization and Estimation Error Bounds for Model-based Neural Networks	❌	✅	❌	❌	❌	❌	✅	2
Generalize Learned Heuristics to Solve Large-scale Vehicle Routing Problems in Real-time	✅	❌	❌	❌	✅	❌	✅	3
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks	❌	❌	✅	❌	✅	❌	❌	2
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap	❌	❌	✅	✅	❌	❌	✅	3
Generate rather than Retrieve: Large Language Models are Strong Context Generators	❌	✅	✅	✅	✅	❌	✅	5
Generating Diverse Cooperative Agents by Learning Incompatible Policies	✅	✅	✅	❌	❌	❌	✅	4
Generating Sequences by Learning to Self-Correct	✅	✅	✅	✅	❌	❌	✅	5
Generative Augmented Flow Networks	✅	✅	✅	❌	❌	❌	✅	4
Generative Modeling Helps Weak Supervision (and Vice Versa)	✅	✅	✅	✅	✅	❌	✅	6
Generative Modelling with Inverse Heat Dissipation	✅	✅	✅	❌	✅	❌	✅	5
Geometrically regularized autoencoders for non-Euclidean data	✅	✅	✅	✅	✅	❌	✅	6
Git Re-Basin: Merging Models modulo Permutation Symmetries	✅	✅	✅	❌	✅	❌	✅	5
Global Explainability of GNNs via Logic Combination of Learned Concepts	❌	✅	✅	✅	❌	❌	✅	4
Globally Optimal Training of Neural Networks with Threshold Activation Functions	❌	❌	✅	❌	✅	❌	✅	3
GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation	❌	✅	❌	❌	❌	❌	✅	2
Gradient Boosting Performs Gaussian Process Inference	✅	✅	✅	✅	❌	❌	✅	5
Gradient Gating for Deep Multi-Rate Learning on Graphs	❌	❌	✅	✅	✅	❌	✅	4
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models	✅	✅	✅	❌	❌	❌	✅	4
Graph Contrastive Learning for Skeleton-based Action Recognition	❌	✅	✅	✅	✅	❌	✅	5
Graph Domain Adaptation via Theory-Grounded Spectral Regularization	❌	✅	✅	✅	✅	❌	✅	5
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning	✅	✅	✅	✅	✅	✅	✅	7
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs	❌	✅	✅	✅	✅	✅	✅	6
Graph Neural Networks for Link Prediction with Subgraph Sketching	✅	✅	✅	✅	✅	❌	✅	6
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution	✅	✅	✅	✅	✅	✅	✅	7
Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems	✅	✅	✅	❌	✅	❌	✅	5
Gray-Box Gaussian Processes for Automated Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement	✅	✅	✅	❌	❌	❌	✅	4
Gromov-Wasserstein Autoencoders	❌	✅	✅	✅	✅	❌	✅	5
Grounding Graph Network Simulators using Physical Sensor Observations	❌	✅	✅	✅	❌	❌	✅	4
Guarded Policy Optimization with Imperfect Online Demonstrations	✅	✅	✅	❌	❌	❌	✅	4
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners	❌	✅	✅	❌	❌	❌	✅	3
Guiding Energy-based Models via Contrastive Latent Variables	✅	✅	✅	❌	✅	❌	✅	5
Guiding Safe Exploration with Weakest Preconditions	✅	✅	✅	❌	❌	❌	✅	4
Guiding continuous operator learning through Physics-based boundary constraints	✅	✅	❌	❌	✅	❌	✅	4
H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection	❌	✅	✅	✅	✅	❌	✅	5
Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks	✅	❌	✅	✅	✅	❌	✅	5
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting	❌	✅	✅	❌	✅	❌	✅	4
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style	✅	❌	✅	✅	✅	❌	✅	5
Hebbian Deep Learning Without Feedback	❌	✅	✅	✅	✅	❌	✅	5
Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs	✅	✅	✅	✅	❌	❌	✅	5
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles	❌	❌	✅	❌	❌	❌	✅	2
HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention	✅	✅	✅	✅	✅	❌	✅	6
HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings	✅	✅	✅	❌	✅	❌	✅	5
HiViT: A Simpler and More Efficient Design of Hierarchical Vision Transformer	❌	✅	✅	✅	✅	✅	✅	6
Hidden Markov Transformer for Simultaneous Machine Translation	✅	✅	✅	✅	✅	❌	✅	6
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement	✅	❌	✅	❌	❌	❌	❌	2
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion	✅	✅	✅	✅	✅	❌	✅	6
Hierarchical Sliced Wasserstein Distance	✅	✅	✅	❌	❌	❌	✅	4
Holistic Adversarially Robust Pruning	✅	✅	✅	❌	✅	❌	✅	5
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers	✅	❌	✅	✅	✅	❌	✅	5
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing	❌	✅	✅	✅	✅	❌	✅	5
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study	❌	✅	❌	❌	❌	❌	✅	2
How I Learned to Stop Worrying and Love Retraining	❌	✅	✅	✅	❌	❌	✅	4
How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?	❌	✅	✅	✅	❌	❌	✅	4
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization	❌	✅	✅	✅	✅	❌	✅	5
How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules	✅	❌	✅	✅	❌	❌	✅	4
How Sharpness-Aware Minimization Minimizes Sharpness?	❌	❌	❌	❌	❌	❌	❌	0
How gradient estimator variance and bias impact learning in neural networks	❌	✅	✅	❌	❌	❌	✅	3
How robust is unsupervised representation learning to distribution shift?	❌	❌	✅	✅	❌	❌	✅	3
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?	✅	✅	✅	❌	✅	✅	✅	6
How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections	❌	❌	✅	❌	❌	❌	✅	2
How to prepare your task head for finetuning	❌	✅	✅	✅	❌	❌	✅	4
Human Motion Diffusion Model	❌	✅	✅	❌	✅	❌	✅	4
Human MotionFormer: Transferring Human Motions with Vision Transformers	✅	✅	✅	❌	❌	❌	✅	4
Human alignment of neural network representations	✅	❌	✅	✅	❌	❌	✅	4
Human-Guided Fair Classification for Natural Language Processing	❌	✅	✅	❌	❌	✅	✅	4
Human-level Atari 200x faster	✅	❌	✅	❌	✅	❌	✅	4
Humanly Certifying Superhuman Classifiers	✅	✅	✅	❌	❌	❌	✅	4
Hungry Hungry Hippos: Towards Language Modeling with State Space Models	✅	✅	✅	✅	✅	❌	✅	6
Hybrid RL: Using both offline and online data can make RL efficient	✅	✅	❌	❌	✅	❌	✅	4
HypeR: Multitask Hyper-Prompted Training Enables Large-Scale Retrieval Generalization	❌	✅	✅	❌	✅	❌	✅	4
Hyper-Decision Transformer for Efficient Online Policy Adaptation	✅	❌	✅	❌	❌	❌	✅	3
HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork	❌	❌	✅	✅	❌	❌	✅	3
Hyperbolic Deep Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
Hyperbolic Self-paced Learning for Self-supervised Skeleton-based Action Representations	❌	✅	✅	✅	✅	❌	✅	5
Hyperparameter Optimization through Neural Network Partitioning	❌	✅	✅	✅	✅	✅	✅	6
IDEAL: Query-Efficient Data-Free Learning from Black-Box Models	✅	❌	✅	❌	❌	❌	✅	3
ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation	✅	✅	✅	✅	✅	❌	✅	6
IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION?	❌	✅	✅	✅	❌	❌	✅	4
ISAAC Newton: Input-based Approximate Curvature for Newton's Method	✅	❌	✅	❌	✅	❌	✅	4
ISS: Image as Stepping Stone for Text-Guided 3D Shape Generation	❌	✅	✅	❌	✅	❌	✅	4
Identifiability Results for Multimodal Contrastive Learning	❌	✅	❌	✅	❌	❌	✅	3
Image as Set of Points	❌	✅	✅	✅	✅	❌	✅	5
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction	❌	✅	✅	✅	❌	❌	✅	4
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations	❌	✅	✅	✅	❌	❌	✅	4
Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules	❌	✅	✅	❌	✅	❌	✅	4
ImaginaryNet: Learning Object Detectors without Real Images and Annotations	❌	✅	✅	✅	❌	❌	✅	4
Imbalanced Semi-supervised Learning with Bias Adaptive Classifier	✅	✅	✅	✅	✅	❌	✅	6
Imitating Graph-Based Planning with Goal-Conditioned Policies	✅	✅	❌	❌	✅	❌	✅	4
Imitating Human Behaviour with Diffusion Models	✅	✅	❌	❌	✅	❌	✅	4
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data	❌	❌	✅	❌	❌	❌	✅	2
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions	❌	❌	✅	❌	❌	❌	✅	2
Implicit Regularization for Group Sparsity	✅	✅	❌	❌	❌	❌	✅	3
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent	❌	❌	✅	❌	❌	❌	✅	2
Impossibly Good Experts and How to Follow Them	✅	✅	✅	❌	❌	❌	✅	4
Improved Convergence of Differential Private SGD with Gradient Clipping	✅	❌	✅	❌	✅	❌	✅	4
Improved Learning-augmented Algorithms for k-means and k-medians Clustering	✅	✅	✅	❌	✅	❌	✅	5
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs	✅	❌	❌	❌	❌	❌	❌	1
Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography	❌	✅	❌	✅	✅	❌	✅	4
Improving Deep Policy Gradients with Value Function Search	✅	❌	✅	❌	✅	❌	✅	4
Improving Deep Regression with Ordinal Entropy	❌	✅	✅	❌	❌	❌	✅	3
Improving Differentiable Neural Architecture Search by Encouraging Transferability	✅	❌	✅	✅	✅	✅	✅	6
Improving Object-centric Learning with Query Optimization	✅	✅	✅	❌	❌	❌	✅	4
Improving Out-of-distribution Generalization with Indirection Representations	❌	❌	✅	❌	✅	❌	✅	3
Improving the imputation of missing data with Markov Blanket discovery	✅	✅	✅	❌	❌	❌	✅	4
In-Situ Text-Only Adaptation of Speech Models with Low-Overhead Speech Imputations	✅	❌	✅	✅	✅	❌	✅	5
In-context Reinforcement Learning with Algorithm Distillation	✅	❌	❌	❌	❌	❌	✅	2
In-sample Actor Critic for Offline Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
InCoder: A Generative Model for Code Infilling and Synthesis	❌	✅	✅	✅	✅	❌	✅	5
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning	❌	❌	✅	✅	❌	❌	✅	3
Incompatibility Clustering as a Defense Against Backdoor Poisoning Attacks	✅	✅	✅	❌	❌	❌	✅	4
Incremental Learning of Structured Memory via Closed-Loop Transcription	✅	❌	✅	✅	✅	❌	✅	5
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
Individual Privacy Accounting with Gaussian Differential Privacy	✅	✅	✅	❌	❌	❌	✅	4
Inequality phenomenon in $l_{\infty}$-adversarial training, and its unrealized threats	✅	❌	✅	❌	❌	❌	✅	3
Information Plane Analysis for Dropout Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Information-Theoretic Analysis of Unsupervised Domain Adaptation	✅	❌	✅	✅	✅	❌	✅	5
Information-Theoretic Diffusion	✅	❌	✅	✅	✅	❌	✅	5
Instance-wise Batch Label Restoration via Gradients in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Integrating Symmetry into Differentiable Planning with Steerable Convolutions	✅	❌	✅	✅	❌	❌	✅	4
Interaction-Based Disentanglement of Entities for Object-Centric World Models	❌	❌	✅	❌	❌	❌	✅	2
Interactive Portrait Harmonization	❌	✅	✅	❌	✅	❌	✅	4
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation	✅	❌	❌	❌	❌	❌	✅	2
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small	✅	❌	❌	❌	❌	❌	✅	2
Interpretability with full complexity by constraining feature information	❌	✅	✅	✅	✅	❌	✅	5
Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization	✅	✅	✅	❌	✅	❌	✅	5
Interpretable Geometric Deep Learning via Learnable Randomness Injection	❌	✅	✅	✅	❌	❌	✅	4
Interpretations of Domain Adaptations via Layer Variational Analysis	❌	✅	✅	✅	✅	❌	✅	5
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning	❌	❌	✅	❌	✅	❌	✅	3
Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?	❌	✅	✅	❌	✅	❌	✅	4
Is Attention All That NeRF Needs?	✅	❌	✅	✅	❌	❌	✅	4
Is Conditional Generative Modeling all you need for Decision Making?	✅	❌	✅	❌	❌	❌	✅	3
Is Forgetting Less a Good Inductive Bias for Forward Transfer?	✅	❌	✅	✅	❌	❌	✅	4
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function	✅	❌	✅	❌	❌	❌	✅	3
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization	✅	✅	✅	✅	❌	❌	✅	5
Is a Caption Worth a Thousand Images? A Study on Representation Learning	❌	✅	✅	❌	❌	❌	✅	3
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification	❌	✅	✅	✅	✅	❌	✅	5
Iterative Circuit Repair Against Formal Specifications	✅	✅	✅	✅	✅	✅	✅	7
Iterative Patch Selection for High-Resolution Image Recognition	✅	✅	✅	✅	✅	❌	✅	6
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Jointly Learning Visual and Auditory Speech Representations from Raw Data	❌	✅	✅	✅	✅	❌	✅	5
Kernel Neural Optimal Transport	❌	✅	✅	❌	✅	❌	✅	4
KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP	❌	✅	✅	❌	✅	❌	✅	4
Knowledge Distillation based Degradation Estimation for Blind Super-Resolution	❌	✅	✅	✅	❌	❌	✅	4
Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models	❌	❌	✅	✅	✅	❌	✅	4
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts	❌	✅	✅	✅	❌	❌	✅	4
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals	✅	❌	✅	❌	✅	❌	✅	4
LAVA: Data Valuation without Pre-Specified Learning Algorithms	❌	✅	✅	✅	✅	❌	❌	4
LDMIC: Learning-based Distributed Multi-view Image Coding	❌	✅	✅	✅	✅	✅	✅	6
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence	✅	✅	✅	✅	✅	❌	✅	6
LMSeg: Language-guided Multi-dataset Segmentation	❌	❌	✅	✅	✅	❌	✅	4
LPT: Long-tailed Prompt Tuning for Image Classification	❌	✅	✅	❌	✅	❌	✅	4
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Label Propagation with Weak Supervision	❌	✅	✅	✅	✅	❌	✅	5
Label-free Concept Bottleneck Models	❌	✅	✅	✅	✅	❌	✅	5
Language Modelling with Pixels	✅	✅	✅	✅	✅	❌	✅	6
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought	✅	✅	✅	❌	❌	❌	✅	4
Language Models Can Teach Themselves to Program Better	❌	✅	✅	❌	❌	❌	✅	3
Language Models are Realistic Tabular Data Generators	❌	✅	✅	❌	✅	❌	✅	4
Language models are multilingual chain-of-thought reasoners	❌	❌	✅	✅	❌	❌	✅	3
Large Language Models are Human-Level Prompt Engineers	✅	✅	✅	✅	❌	❌	✅	5
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations	❌	✅	✅	✅	❌	✅	✅	5
Latent Bottlenecked Attentive Neural Processes	❌	✅	✅	❌	✅	❌	✅	4
Latent Graph Inference using Product Manifolds	❌	✅	✅	✅	✅	❌	✅	5
Latent Neural ODEs with Sparse Bayesian Multiple Shooting	❌	✅	✅	✅	✅	✅	✅	6
Latent State Marginalization as a Low-cost Approach for Improving Exploration	✅	✅	✅	❌	✅	❌	✅	5
Latent Variable Representation for Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations	❌	✅	✅	✅	✅	❌	✅	5
Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection	❌	✅	✅	❌	❌	✅	✅	4
Learnable Graph Convolutional Attention Networks	❌	✅	✅	✅	✅	❌	✅	5
Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Learned Index with Dynamic $\epsilon$	✅	✅	✅	❌	✅	❌	✅	5
Learning About Progress From Experts	✅	❌	✅	❌	✅	❌	✅	4
Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward	❌	✅	✅	❌	❌	❌	✅	3
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition	✅	❌	❌	❌	❌	❌	❌	1
Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations	✅	✅	✅	❌	❌	❌	✅	4
Learning Controllable Adaptive Simulation for Multi-resolution Physics	❌	✅	✅	❌	✅	❌	✅	4
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model	✅	✅	✅	✅	✅	✅	✅	7
Learning Diffusion Bridges on Constrained Domains	✅	✅	✅	❌	❌	❌	✅	4
Learning Domain-Agnostic Representation for Disease Diagnosis	❌	❌	✅	✅	❌	❌	✅	3
Learning Fair Graph Representations via Automated Data Augmentations	✅	✅	❌	✅	❌	❌	✅	4
Learning Fast and Slow for Online Time Series Forecasting	✅	✅	✅	✅	❌	❌	✅	5
Learning Group Importance using the Differentiable Hypergeometric Distribution	✅	✅	✅	✅	✅	❌	✅	6
Learning Harmonic Molecular Representations on Riemannian Manifold	❌	✅	✅	✅	✅	❌	✅	5
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network	❌	✅	✅	✅	❌	❌	✅	4
Learning Hierarchical Protein Representations via Complete 3D Graph Networks	❌	✅	✅	✅	✅	❌	✅	5
Learning Human-Compatible Representations for Case-Based Decision Support	❌	✅	✅	✅	✅	❌	✅	5
Learning Hyper Label Model for Programmatic Weak Supervision	❌	✅	✅	✅	✅	❌	✅	5
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance	❌	✅	✅	❌	✅	❌	✅	4
Learning Iterative Neural Optimizers for Image Steganography	✅	✅	✅	✅	✅	❌	✅	6
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment	✅	❌	✅	❌	❌	❌	✅	3
Learning Label Encodings for Deep Regression	✅	✅	✅	✅	✅	❌	✅	6
Learning Language Representations with Logical Inductive Bias	❌	❌	✅	✅	✅	❌	✅	4
Learning Locality and Isotropy in Dialogue Modeling	❌	✅	✅	✅	✅	❌	✅	5
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets	❌	❌	❌	❌	❌	❌	✅	1
Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency	❌	✅	✅	✅	❌	❌	❌	3
Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions	✅	✅	✅	✅	✅	❌	✅	6
Learning Multimodal Data Augmentation in Feature Space	✅	✅	✅	❌	✅	❌	✅	5
Learning Object-Language Alignments for Open-Vocabulary Object Detection	❌	✅	✅	✅	✅	❌	✅	5
Learning Probabilistic Topological Representations Using Discrete Morse Theory	✅	❌	✅	✅	✅	❌	✅	5
Learning Proximal Operators to Discover Multiple Optima	❌	✅	✅	✅	✅	❌	✅	5
Learning Rationalizable Equilibria in Multiplayer Games	✅	❌	❌	❌	❌	❌	❌	1
Learning ReLU networks to high uniform accuracy is intractable	❌	✅	❌	❌	✅	❌	✅	3
Learning Simultaneous Navigation and Construction in Grid Worlds	✅	✅	❌	✅	✅	❌	✅	5
Learning Soft Constraints From Constrained Expert Demonstrations	✅	❌	✅	❌	❌	❌	✅	3
Learning Sparse Group Models Through Boolean Relaxation	❌	✅	✅	✅	✅	✅	✅	6
Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization	✅	✅	✅	✅	❌	❌	✅	5
Learning Structured Representations by Embedding Class Hierarchy	❌	❌	✅	❌	❌	❌	✅	2
Learning Symbolic Models for Graph-structured Physical Mechanism	✅	❌	✅	❌	❌	❌	✅	3
Learning Uncertainty for Unknown Domains with Zero-Target-Assumption	✅	❌	✅	❌	✅	❌	✅	4
Learning Vortex Dynamics for Fluid Inference and Prediction	❌	✅	✅	❌	✅	❌	✅	4
Learning What and Where: Disentangling Location and Identity Tracking Without Supervision	✅	✅	✅	✅	❌	❌	✅	5
Learning Zero-Shot Cooperation with Humans, Assuming Humans Are Biased	✅	❌	✅	❌	❌	❌	✅	3
Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering	✅	✅	✅	✅	✅	✅	✅	7
Learning differentiable solvers for systems with hard constraints	❌	❌	✅	✅	✅	❌	✅	4
Learning in temporally structured environments	❌	❌	✅	❌	❌	❌	✅	2
Learning multi-scale local conditional probability models of images	✅	✅	✅	✅	❌	❌	✅	5
Learning on Large-scale Text-attributed Graphs via Variational Inference	❌	✅	✅	✅	✅	❌	✅	5
Learning rigid dynamics with face interaction graph networks	❌	❌	✅	✅	✅	❌	✅	4
Learning the Positions in CountSketch	✅	❌	✅	❌	✅	❌	✅	4
Learning to CROSS exchange to solve min-max vehicle routing problems	✅	❌	❌	❌	✅	✅	✅	4
Learning to Compose Soft Prompts for Compositional Zero-Shot Learning	✅	✅	✅	✅	✅	❌	✅	6
Learning to Decompose Visual Features with Latent Textual Prompts	❌	❌	✅	❌	❌	❌	✅	2
Learning to Estimate Shapley Values with Vision Transformers	✅	✅	✅	✅	✅	❌	✅	6
Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision	❌	✅	✅	❌	✅	✅	✅	5
Learning to Extrapolate: A Transductive Approach	✅	❌	✅	❌	❌	❌	✅	3
Learning to Generate Columns with Application to Vertex Coloring	✅	✅	✅	✅	✅	❌	✅	6
Learning to Grow Pretrained Models for Efficient Transformer Training	✅	❌	✅	✅	❌	❌	✅	4
Learning to Induce Causal Structure	❌	❌	✅	❌	❌	❌	✅	2
Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models	✅	❌	✅	❌	❌	❌	✅	3
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference	✅	✅	✅	❌	✅	❌	✅	5
Learning to Segment from Noisy Annotations: A Spatial Correction Approach	✅	✅	✅	✅	✅	❌	✅	6
Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer	❌	✅	✅	✅	✅	❌	✅	5
Learning to reason over visual objects	❌	✅	✅	✅	✅	❌	✅	5
Learning topology-preserving data representations	❌	✅	✅	❌	✅	❌	✅	4
Learning where and when to reason in neuro-symbolic inference	❌	✅	✅	✅	❌	✅	✅	5
Learning with Auxiliary Activation for Memory-Efficient Training	❌	✅	✅	✅	✅	❌	✅	5
Learning with Logical Constraints but without Shortcut Satisfaction	✅	✅	✅	❌	✅	❌	✅	5
Learning with Stochastic Orders	✅	✅	✅	✅	✅	❌	✅	6
Learning without Prejudices: Continual Unbiased Learning via Benign and Malignant Forgetting	✅	❌	✅	✅	❌	❌	✅	4
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models	❌	❌	✅	❌	❌	✅	✅	3
Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction	❌	❌	✅	✅	❌	❌	❌	2
Leveraging Importance Weights in Subset Selection	✅	❌	✅	✅	✅	❌	✅	5
Leveraging Large Language Models for Multiple Choice Question Answering	❌	✅	✅	✅	❌	❌	✅	4
Leveraging Unlabeled Data to Track Memorization	✅	✅	✅	✅	✅	❌	✅	6
LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval	❌	✅	✅	✅	✅	❌	✅	5
LiftedCL: Lifting Contrastive Learning for Human-Centric Perception	❌	❌	✅	✅	❌	❌	✅	3
Light Sampling Field and BRDF Representation for Physically-based Neural Rendering	❌	❌	❌	❌	✅	❌	✅	2
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation	❌	✅	✅	✅	❌	❌	✅	4
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification	❌	✅	✅	❌	✅	❌	✅	4
Limitless Stability for Graph Convolutional Networks	❌	❌	✅	❌	❌	❌	✅	2
Linear Connectivity Reveals Generalization Strategies	❌	✅	✅	✅	✅	❌	✅	5
Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies	✅	❌	❌	❌	❌	❌	❌	1
Linearly Mapping from Image to Text Space	❌	✅	✅	✅	✅	❌	✅	5
Link Prediction with Non-Contrastive Learning	✅	✅	✅	✅	✅	❌	✅	6
LipsFormer: Introducing Lipschitz Continuity to Vision Transformers	❌	❌	✅	✅	✅	❌	✅	4
Liquid Structural State-Space Models	✅	✅	✅	✅	❌	❌	✅	5
Localized Randomized Smoothing for Collective Robustness Certification	❌	✅	✅	✅	✅	✅	✅	6
LogicDP: Creating Labels for Graph Data via Inductive Logic Programming	✅	✅	✅	✅	✅	❌	✅	6
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning	❌	✅	✅	✅	❌	❌	✅	4
Logical Message Passing Networks with One-hop Inference on Atomic Formulas	❌	✅	✅	❌	✅	❌	✅	4
Long Range Language Modeling via Gated State Spaces	✅	❌	✅	❌	✅	❌	✅	4
Long-Tailed Learning Requires Feature Learning	❌	✅	❌	❌	❌	❌	✅	2
Long-Tailed Partial Label Learning via Dynamic Rebalancing	✅	✅	✅	✅	❌	❌	✅	5
Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent	❌	✅	✅	❌	❌	❌	✅	3
Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation	❌	❌	✅	❌	❌	❌	✅	2
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes	❌	❌	❌	❌	❌	❌	❌	0
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation	✅	✅	✅	❌	❌	❌	✅	4
MA-BERT: Towards Matrix Arithmetic-only BERT Inference by Eliminating Complex Non-Linear Functions	❌	✅	✅	✅	✅	❌	✅	5
MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection	✅	✅	✅	✅	✅	❌	✅	6
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning	✅	❌	✅	✅	✅	❌	✅	5
MARS: Meta-learning as Score Matching in the Function Space	✅	✅	✅	✅	❌	❌	✅	5
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors	❌	❌	✅	❌	❌	❌	✅	2
MCAL: Minimum Cost Human-Machine Active Labeling	✅	✅	✅	❌	✅	❌	✅	5
MECTA: Memory-Economic Continual Test-Time Model Adaptation	✅	✅	✅	❌	✅	✅	✅	6
MEDFAIR: Benchmarking Fairness for Medical Imaging	❌	✅	✅	✅	✅	✅	✅	6
MEDICAL IMAGE UNDERSTANDING WITH PRETRAINED VISION LANGUAGE MODELS: A COMPREHENSIVE STUDY	❌	✅	✅	✅	❌	❌	✅	4
MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
MIMT: Masked Image Modeling Transformer for Video Compression	✅	❌	✅	❌	✅	❌	✅	4
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization	✅	✅	✅	✅	✅	✅	✅	7
MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises	❌	✅	✅	❌	❌	✅	✅	4
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models	❌	✅	✅	✅	✅	❌	✅	5
MPCFORMER: FAST, PERFORMANT AND PRIVATE TRANSFORMER INFERENCE WITH MPC	❌	✅	✅	❌	✅	❌	✅	4
Machine Unlearning of Federated Clusters	✅	✅	✅	❌	❌	❌	✅	4
Make-A-Video: Text-to-Video Generation without Text-Video Data	❌	❌	✅	❌	❌	❌	✅	2
Making Better Decision by Directly Planning in Continuous Control	✅	✅	✅	❌	❌	❌	✅	4
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples	❌	✅	✅	✅	✅	❌	✅	5
Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds	✅	❌	✅	❌	❌	❌	✅	3
ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills	✅	✅	✅	❌	✅	❌	✅	5
ManyDG: Many-domain Generalization for Healthcare Applications	❌	✅	✅	✅	✅	✅	✅	6
MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction	❌	✅	✅	❌	✅	❌	✅	4
Markup-to-Image Diffusion Models with Scheduled Sampling	✅	✅	✅	✅	✅	❌	✅	6
Martingale Posterior Neural Processes	❌	✅	✅	✅	✅	✅	✅	6
MaskFusion: Feature Augmentation for Click-Through Rate Prediction via Input-adaptive Mask Fusion	❌	❌	✅	✅	✅	❌	✅	4
MaskViT: Masked Visual Pre-Training for Video Prediction	❌	❌	✅	❌	✅	✅	✅	4
Masked Distillation with Receptive Tokens	❌	✅	✅	✅	❌	❌	✅	4
Masked Frequency Modeling for Self-Supervised Visual Pre-Training	✅	✅	✅	✅	✅	❌	✅	6
Masked Image Modeling with Denoising Contrast	✅	❌	✅	✅	✅	❌	✅	5
Masked Unsupervised Self-training for Label-free Image Classification	❌	✅	✅	❌	✅	❌	✅	4
Masked Vision and Language Modeling for Multi-modal Representation Learning	❌	❌	✅	✅	✅	❌	✅	4
Mass-Editing Memory in a Transformer	✅	✅	✅	❌	✅	✅	✅	6
Massively Scaling Heteroscedastic Classifiers	❌	✅	✅	✅	✅	❌	✅	5
Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning	✅	✅	✅	✅	❌	❌	✅	5
Matching receptor to odorant with protein language and graph neural networks	❌	✅	✅	✅	✅	❌	✅	5
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence	❌	❌	❌	❌	❌	❌	❌	0
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam	✅	✅	✅	✅	✅	❌	✅	6
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition	✅	✅	✅	✅	✅	❌	✅	6
Measure the Predictive Heterogeneity	✅	❌	✅	❌	❌	❌	❌	2
Measuring Forgetting of Memorized Training Examples	✅	❌	✅	❌	❌	❌	✅	3
Measuring axiomatic soundness of counterfactual image models	✅	❌	✅	✅	❌	❌	✅	4
Mega: Moving Average Equipped Gated Attention	❌	❌	✅	✅	❌	❌	✅	3
Memorization Capacity of Neural Networks with Conditional Computation	✅	❌	❌	❌	❌	❌	❌	1
Memorization-Dilation: Modeling Neural Collapse Under Noise	❌	❌	✅	❌	❌	❌	✅	2
Memory Gym: Partially Observable Challenges to Memory-Based Agents	❌	✅	✅	✅	✅	✅	✅	6
MeshDiffusion: Score-based Generative 3D Mesh Modeling	✅	✅	✅	✅	✅	❌	✅	6
Meta Knowledge Condensation for Federated Learning	✅	❌	✅	✅	❌	❌	✅	4
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning	❌	✅	✅	✅	✅	❌	✅	5
Meta Temporal Point Processes	❌	✅	✅	❌	❌	❌	✅	3
Meta-Learning in Games	✅	❌	✅	❌	❌	❌	✅	3
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction	✅	✅	✅	✅	✅	❌	✅	6
Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets	❌	✅	✅	✅	✅	❌	✅	5
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning	✅	✅	✅	✅	❌	❌	✅	5
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics	❌	❌	✅	✅	❌	❌	✅	3
Mid-Vision Feedback	❌	✅	✅	❌	❌	❌	✅	3
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning	✅	✅	✅	✅	✅	✅	✅	7
Mind the Gap: Offline Policy Optimization for Imperfect Rewards	✅	✅	✅	❌	✅	❌	✅	5
Mind the Pool: Convolutional Neural Networks Can Overfit Input Size	✅	❌	✅	✅	❌	❌	✅	4
Mind's Eye: Grounded Language Model Reasoning through Simulation	❌	❌	❌	❌	✅	❌	✅	2
Mini-batch $k$-means terminates within $O(d/\epsilon)$ iterations	✅	❌	❌	❌	❌	❌	❌	1
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform	✅	❌	✅	❌	❌	❌	✅	3
Minimax Optimal Kernel Operator Learning via Multilevel Training	❌	❌	❌	❌	❌	❌	❌	0
Minimum Description Length Control	✅	❌	✅	❌	❌	❌	✅	3
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients	❌	✅	✅	✅	❌	❌	✅	4
Mitigating Dataset Bias by Using Per-Sample Gradient	✅	❌	✅	✅	✅	❌	✅	5
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach	✅	❌	✅	✅	❌	❌	✅	4
Mitigating Memorization of Noisy Labels via Regularization between Representations	❌	✅	✅	❌	❌	❌	✅	3
MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer	✅	❌	✅	✅	✅	❌	✅	5
MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations	✅	✅	✅	❌	❌	❌	✅	4
MocoSFL: enabling cross-client collaborative self-supervised learning	❌	✅	✅	✅	✅	❌	✅	5
Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning	✅	❌	✅	✅	❌	❌	✅	4
Model-based Causal Bayesian Optimization	✅	✅	✅	✅	❌	❌	✅	5
Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts	✅	✅	✅	✅	✅	❌	✅	6
Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval	❌	❌	✅	✅	✅	❌	✅	4
Modeling content creator incentives on algorithm-curated platforms	❌	✅	✅	✅	✅	✅	✅	6
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization	✅	✅	✅	✅	✅	✅	✅	7
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN	❌	✅	✅	✅	✅	❌	✅	5
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning	✅	✅	✅	❌	✅	❌	✅	5
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules	❌	✅	✅	✅	❌	❌	✅	4
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching	✅	✅	✅	✅	✅	❌	✅	6
Molecule Generation For Target Protein Binding with Structural Motifs	❌	✅	✅	✅	✅	✅	✅	6
Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Monocular Scene Reconstruction with 3D SDF Transformers	❌	✅	✅	❌	✅	❌	✅	4
More Centralized Training, Still Decentralized Execution: Multi-Agent Conditional Policy Factorization	❌	✅	✅	❌	✅	❌	✅	4
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity	✅	✅	✅	✅	✅	✅	✅	7
Mosaic Representation Learning for Self-supervised Visual Pre-training	✅	✅	✅	✅	✅	❌	✅	6
Moving Forward by Moving Backward: Embedding Action Impact over Action Semantics	❌	❌	✅	✅	✅	✅	✅	5
Multi-Objective Online Learning	✅	❌	✅	❌	✅	❌	✅	4
Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality	✅	✅	✅	❌	❌	✅	✅	5
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve	✅	✅	✅	✅	❌	❌	✅	5
Multi-domain image generation and translation with identifiability guarantees	❌	✅	✅	❌	❌	❌	✅	3
Multi-level Protein Structure Pre-training via Prompt Learning	✅	❌	✅	✅	✅	❌	✅	5
Multi-lingual Evaluation of Code Generation Models	❌	✅	✅	✅	❌	❌	✅	4
Multi-objective optimization via equivariant deep hypervolume approximation	❌	✅	✅	✅	✅	❌	✅	5
Multi-skill Mobile Manipulation for Object Rearrangement	❌	✅	✅	✅	❌	❌	✅	4
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization	❌	✅	✅	✅	✅	✅	✅	6
MultiViz: Towards Visualizing and Understanding Multimodal Models	✅	✅	✅	✅	❌	❌	✅	5
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders	❌	✅	✅	✅	❌	✅	✅	5
Multimodal Analogical Reasoning over Knowledge Graphs	❌	✅	✅	✅	✅	❌	✅	5
Multimodal Federated Learning via Contrastive Representation Ensemble	✅	❌	✅	❌	❌	❌	✅	3
Multiple sequence alignment as a sequence-to-sequence learning problem	❌	❌	❌	✅	✅	❌	✅	3
Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning	❌	❌	✅	✅	❌	❌	✅	3
Multivariate Time-series Imputation with Disentangled Temporal Representations	❌	✅	✅	✅	✅	✅	✅	6
Mutual Partial Label Learning with Competitive Label Noise	✅	❌	✅	✅	❌	❌	✅	4
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs	✅	✅	✅	✅	✅	❌	✅	6
NANSY++: Unified Voice Synthesis with Neural Analysis and Synthesis	❌	❌	✅	✅	✅	❌	✅	4
NERDS: A General Framework to Train Camera Denoisers from Raw-RGB Noisy Image Pairs	❌	❌	✅	❌	✅	❌	✅	3
NORM: Knowledge Distillation via N-to-One Representation Matching	❌	✅	✅	✅	✅	❌	✅	5
NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning	❌	✅	✅	❌	✅	❌	✅	4
NTK-SAP: Improving neural network pruning by aligning training dynamics	✅	✅	✅	❌	✅	❌	✅	5
NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes	❌	✅	✅	❌	✅	❌	✅	4
NeRN: Learning Neural Representations for Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Near-Optimal Adversarial Reinforcement Learning with Switching Costs	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Near-optimal Coresets for Robust Clustering	✅	❌	✅	❌	✅	✅	✅	5
Near-optimal Policy Identification in Active Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game	✅	❌	❌	❌	❌	❌	✅	2
Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication	❌	✅	❌	✅	✅	❌	✅	4
Neural Architecture Design and Robustness: A Dataset	✅	✅	✅	❌	✅	❌	✅	5
Neural Bregman Divergences for Distance Learning	✅	❌	✅	✅	✅	❌	✅	5
Neural Causal Models for Counterfactual Identification and Estimation	✅	✅	❌	❌	❌	❌	❌	2
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning	❌	✅	✅	❌	❌	❌	✅	3
Neural Compositional Rule Learning for Knowledge Graph Reasoning	✅	✅	✅	❌	❌	❌	✅	4
Neural DAG Scheduling via One-Shot Priority Sampling	✅	❌	✅	✅	✅	❌	✅	5
Neural Design for Genetic Perturbation Experiments	✅	✅	✅	❌	❌	❌	✅	4
Neural Episodic Control with State Abstraction	✅	✅	✅	❌	✅	❌	✅	5
Neural Groundplans: Persistent Neural Scene Representations from a Single Image	❌	❌	✅	✅	✅	❌	✅	4
Neural Image-based Avatars: Generalizable Radiance Fields for Human Avatar Modeling	❌	❌	✅	✅	❌	❌	❌	2
Neural Implicit Shape Editing using Boundary Sensitivity	❌	❌	✅	❌	❌	❌	✅	2
Neural Lagrangian Schr\"{o}dinger Bridge: Diffusion Modeling for Population Dynamics	✅	✅	✅	✅	✅	❌	✅	6
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD	✅	❌	❌	❌	❌	❌	❌	1
Neural Networks and the Chomsky Hierarchy	✅	✅	✅	❌	✅	❌	✅	5
Neural Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Neural Radiance Field Codebooks	❌	❌	✅	✅	✅	❌	✅	4
Neural Systematic Binder	✅	✅	✅	❌	❌	❌	✅	4
Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks	❌	❌	✅	✅	❌	❌	❌	2
Neural-based classification rule learning for sequential data	❌	✅	✅	✅	✅	❌	✅	5
Neuro-Symbolic Procedural Planning with Commonsense Prompting	✅	✅	✅	❌	✅	❌	✅	5
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery	✅	✅	✅	❌	✅	❌	✅	5
Neuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity	❌	❌	✅	❌	✅	❌	✅	3
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning	❌	✅	✅	❌	✅	❌	✅	4
No Reason for No Supervision: Improved Generalization in Supervised Models	❌	✅	✅	✅	✅	❌	✅	5
Noise Injection Node Regularization for Robust Learning	❌	✅	✅	✅	❌	❌	✅	4
Noise Is Not the Main Factor Behind the Gap Between Sgd and Adam on Transformers, But Sign Descent Might Be	✅	✅	✅	✅	❌	❌	✅	5
Noise-Robust De-Duplication at Scale	❌	✅	✅	✅	✅	❌	✅	5
Non-parametric Outlier Synthesis	✅	✅	✅	❌	✅	✅	✅	6
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities	❌	❌	❌	✅	❌	❌	✅	2
Not All Tasks Are Born Equal: Understanding Zero-Shot Generalization	❌	✅	✅	❌	❌	❌	✅	3
Novel View Synthesis with Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
ODAM: Gradient-based Instance-Specific Visual Explanations for Object Detection	✅	❌	✅	✅	✅	❌	✅	5
OPTQ: Accurate Quantization for Generative Pre-trained Transformers	✅	✅	✅	✅	✅	❌	✅	6
OTOv2: Automatic, Generic, User-Friendly	✅	✅	✅	❌	✅	❌	✅	5
Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement	✅	❌	❌	❌	❌	❌	✅	2
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes	❌	❌	✅	❌	✅	❌	✅	3
Offline RL for Natural Language Generation with Implicit Language Q Learning	❌	✅	✅	❌	✅	❌	✅	4
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization	✅	✅	✅	❌	❌	❌	✅	4
Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling	✅	✅	✅	❌	✅	❌	✅	5
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient	✅	❌	❌	❌	❌	❌	❌	1
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework	❌	✅	✅	❌	✅	❌	❌	3
Omnigrok: Grokking Beyond Algorithmic Data	❌	✅	✅	❌	❌	❌	✅	3
On Accelerated Perceptrons and Beyond	✅	❌	❌	❌	❌	❌	❌	1
On Achieving Optimal Adversarial Test Error	❌	❌	❌	❌	❌	❌	✅	1
On Compositional Uncertainty Quantification for Seq2seq Graph Parsing	✅	✅	✅	✅	❌	❌	❌	4
On Explaining Neural Network Robustness with Activation Path	✅	✅	✅	❌	❌	❌	✅	4
On Pre-training Language Model for Antibody	❌	✅	✅	✅	❌	❌	✅	4
On Representing Linear Programs by Graph Neural Networks	✅	✅	❌	❌	✅	❌	✅	4
On Representing Mixed-Integer Linear Programs by Graph Neural Networks	✅	✅	❌	❌	✅	❌	✅	4
On The Inadequacy of Optimizing Alignment and Uniformity in Contrastive Learning of Sentence Representations	❌	✅	✅	✅	✅	✅	✅	6
On The Relative Error of Random Fourier Features for Preserving Kernel Distance	❌	❌	❌	❌	❌	❌	✅	1
On The Specialization of Neural Modules	❌	✅	✅	❌	❌	❌	✅	3
On amortizing convex conjugates for optimal transport	✅	✅	✅	❌	✅	❌	✅	5
On the Convergence of AdaGrad(Norm) on $\mathbb{R}^d$: Beyond Convexity, Non-Asymptotic Rate and Acceleration	✅	❌	❌	❌	❌	❌	✅	2
On the Data-Efficiency with Contrastive Image Transformation in Reinforcement Learning	✅	✅	✅	❌	❌	❌	❌	3
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.	✅	✅	✅	❌	✅	❌	✅	5
On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
On the Importance and Applicability of Pre-Training for Federated Learning	❌	✅	✅	✅	✅	❌	✅	5
On the Performance of Temporal Difference Learning With Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
On the Perils of Cascading Robust Classifiers	✅	✅	✅	❌	✅	❌	✅	5
On the Robustness of Safe Reinforcement Learning under Observational Perturbations	✅	✅	✅	❌	✅	❌	✅	5
On the Saturation Effect of Kernel Ridge Regression	❌	❌	❌	❌	❌	❌	✅	1
On the Sensitivity of Reward Inference to Misspecified Human Models	❌	❌	✅	❌	❌	❌	✅	2
On the Soft-Subnetwork for Few-Shot Class Incremental Learning	✅	✅	✅	❌	✅	✅	✅	6
On the Trade-Off between Actionable Explanations and the Right to be Forgotten	✅	❌	✅	❌	❌	❌	✅	3
On the Usefulness of Embeddings, Clusters and Strings for Text Generation Evaluation	❌	✅	✅	✅	❌	❌	✅	4
On the Word Boundaries of Emergent Languages Based on Harris's Articulation Scheme	✅	✅	❌	❌	❌	❌	✅	3
On the complexity of nonsmooth automatic differentiation	✅	❌	❌	❌	❌	❌	❌	1
On the duality between contrastive and non-contrastive self-supervised learning	✅	✅	✅	✅	✅	❌	✅	6
One Transformer Can Understand Both 2D & 3D Molecular Data	❌	✅	✅	✅	✅	❌	✅	5
One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Online Bias Correction for Task-Free Continual Learning	✅	✅	✅	✅	❌	❌	✅	5
Online Boundary-Free Continual Learning by Scheduled Data Prior	✅	✅	✅	❌	✅	❌	✅	5
Online Low Rank Matrix Completion	✅	❌	❌	❌	❌	❌	❌	1
Open-Vocabulary Object Detection upon Frozen Vision and Language Models	❌	❌	✅	✅	❌	❌	✅	3
Optimal Activation Functions for the Random Features Regression Model	❌	✅	✅	❌	✅	✅	✅	5
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian	✅	❌	❌	❌	❌	❌	❌	1
Optimal Transport for Offline Imitation Learning	✅	✅	✅	❌	✅	❌	✅	5
Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics	✅	❌	❌	❌	❌	❌	❌	1
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning	✅	✅	✅	✅	❌	❌	✅	5
Optimizing Spca-based Continual Learning: A Theoretical Approach	✅	✅	✅	❌	❌	❌	✅	4
Order Matters: Agent-by-agent Policy Optimization	✅	✅	✅	❌	❌	❌	✅	4
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing	✅	✅	✅	✅	✅	❌	✅	6
Out-of-Distribution Detection and Selective Generation for Conditional Language Models	✅	❌	✅	❌	❌	❌	✅	3
Out-of-Distribution Detection based on In-Distribution Data Patterns Memorization with Modern Hopfield Energy	❌	✅	✅	✅	✅	✅	✅	6
Out-of-distribution Detection with Implicit Outlier Transformation	✅	✅	✅	✅	❌	❌	✅	5
Out-of-distribution Representation Learning for Time Series Classification	❌	✅	✅	✅	❌	❌	✅	4
Outcome-directed Reinforcement Learning by Uncertainty \& Temporal Distance-Aware Curriculum Goal Generation	✅	✅	✅	❌	❌	❌	✅	4
Over-Training with Mixup May Hurt Generalization	❌	❌	✅	✅	❌	❌	✅	3
Over-parameterized Model Optimization with Polyak-{\L}ojasiewicz Condition	✅	❌	✅	❌	✅	❌	✅	4
PAC Reinforcement Learning for Predictive State Representations	✅	❌	❌	❌	❌	❌	❌	1
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification	❌	❌	❌	❌	✅	❌	✅	2
PASHA: Efficient HPO and NAS with Progressive Resource Allocation	✅	✅	✅	✅	❌	❌	✅	5
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm	✅	✅	✅	❌	✅	❌	✅	5
PEER: A Collaborative Language Model	❌	❌	✅	✅	❌	❌	✅	3
PGrad: Learning Principal Gradients For Domain Generalization	❌	❌	✅	✅	❌	❌	✅	3
PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales	❌	✅	✅	✅	❌	❌	✅	4
PLOT: Prompt Learning with Optimal Transport for Vision-Language Models	✅	✅	✅	✅	✅	✅	✅	7
POPGym: Benchmarking Partially Observable Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
PV3D: A 3D Generative Model for Portrait Video Generation	❌	✅	✅	❌	✅	❌	✅	4
PaLI: A Jointly-Scaled Multilingual Language-Image Model	❌	❌	✅	✅	✅	❌	✅	4
Packed Ensembles for efficient uncertainty estimation	❌	✅	✅	✅	✅	✅	✅	6
PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs	✅	✅	✅	❌	✅	❌	✅	5
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation	❌	❌	✅	❌	❌	❌	✅	2
Parallel Deep Neural Networks Have Zero Duality Gap	❌	❌	❌	❌	❌	❌	❌	0
Parameter-Efficient Fine-Tuning Design Spaces	❌	✅	✅	✅	✅	❌	✅	5
Parametrizing Product Shape Manifolds by Composite Networks	❌	✅	✅	❌	❌	❌	✅	3
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization	✅	✅	✅	✅	✅	✅	✅	7
Part-Based Models Improve Adversarial Robustness	❌	✅	✅	✅	✅	❌	✅	5
Partial Label Unsupervised Domain Adaptation with Class-Prototype Alignment	✅	❌	✅	❌	❌	❌	✅	3
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms	✅	❌	❌	❌	❌	❌	❌	1
Particle-based Variational Inference with Preconditioned Functional Gradient Flow	✅	❌	✅	✅	✅	✅	✅	6
Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning	✅	✅	✅	❌	✅	❌	✅	5
PatchDCT: Patch Refinement for High Quality Instance Segmentation	❌	✅	✅	✅	✅	❌	✅	5
PerFedMask: Personalized Federated Learning with Optimized Masking Vectors	✅	✅	✅	✅	❌	✅	✅	6
Perfectly Secure Steganography Using Minimum Entropy Coupling	✅	✅	✅	❌	✅	❌	✅	5
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs	✅	❌	❌	❌	❌	❌	❌	1
Personalized Federated Learning with Feature Alignment and Classifier Collaboration	✅	✅	✅	✅	✅	❌	✅	6
Personalized Reward Learning with Interaction-Grounded Learning (IGL)	✅	✅	✅	❌	❌	❌	✅	4
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Phase transition for detecting a small community in a large network	❌	❌	❌	❌	❌	❌	❌	0
Phase2vec: dynamical systems embedding with a physics-informed convolutional network	❌	✅	✅	✅	✅	✅	✅	6
Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions	❌	❌	✅	✅	❌	❌	✅	3
PiFold: Toward effective and efficient protein inverse folding	❌	✅	✅	✅	✅	❌	✅	5
Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning	✅	✅	✅	✅	❌	✅	✅	6
Pitfalls of Gaussians as a noise distribution in NCE	❌	❌	❌	❌	❌	❌	❌	0
Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training	❌	✅	✅	❌	❌	✅	✅	4
Planning Goals for Exploration	✅	❌	✅	❌	✅	❌	✅	4
Planning with Large Language Models for Code Generation	✅	❌	✅	✅	✅	❌	✅	5
Planning with Sequence Models through Iterative Energy Minimization	✅	❌	✅	❌	❌	❌	✅	3
Plateau in Monotonic Linear Interpolation --- A "Biased" View of Loss Landscape for Deep Networks	❌	✅	✅	❌	✅	❌	✅	4
Policy Expansion for Bridging Offline-to-Online Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling	❌	✅	✅	✅	❌	❌	✅	4
Policy-Based Self-Competition for Planning Problems	✅	✅	✅	✅	❌	❌	✅	5
Population-size-Aware Policy Optimization for Mean-Field Games	✅	❌	✅	❌	✅	❌	✅	4
Post-hoc Concept Bottleneck Models	❌	✅	✅	✅	✅	❌	✅	5
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions	✅	✅	❌	✅	❌	❌	✅	4
PowerQuant: Automorphism Search for Non-Uniform Quantization	✅	❌	✅	❌	✅	❌	❌	3
Pre-training via Denoising for Molecular Property Prediction	❌	✅	✅	✅	✅	❌	✅	5
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information	❌	✅	✅	✅	❌	❌	❌	3
Predictive Inference with Feature Conformal Prediction	✅	✅	✅	✅	❌	❌	✅	5
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift	✅	✅	❌	❌	❌	❌	✅	3
Preference Transformer: Modeling Human Preferences using Transformers for RL	❌	✅	✅	❌	✅	❌	✅	4
Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models	✅	✅	✅	✅	✅	❌	✅	6
Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses	✅	❌	✅	✅	❌	❌	✅	4
Proactive Multi-Camera Collaboration for 3D Human Pose Estimation	✅	✅	✅	✅	✅	❌	✅	6
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse	✅	❌	✅	❌	❌	❌	✅	3
Programmatically Grounded, Compositionally Generalizable Robotic Manipulation	❌	✅	✅	✅	❌	❌	✅	4
Progress measures for grokking via mechanistic interpretability	❌	✅	❌	❌	❌	❌	✅	2
Progressive Mix-Up for Few-Shot Supervised Multi-Source Domain Transfer	❌	✅	✅	✅	❌	❌	✅	4
Progressive Prompts: Continual Learning for Language Models	❌	❌	✅	✅	❌	❌	✅	3
Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning	✅	✅	✅	✅	❌	❌	✅	5
Progressively Compressed Auto-Encoder for Self-supervised Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Projective Proximal Gradient Descent for Nonconvex Nonsmooth Optimization: Fast Convergence Without Kurdyka-Lojasiewicz (KL) Property	✅	❌	✅	❌	❌	❌	✅	3
Prompt-to-Prompt Image Editing with Cross-Attention Control	✅	❌	❌	❌	❌	❌	✅	2
Promptagator: Few-shot Dense Retrieval From 8 Examples	❌	❌	✅	✅	❌	❌	✅	3
Prompting GPT-3 To Be Reliable	❌	✅	✅	❌	❌	❌	✅	3
Proposal-Contrastive Pretraining for Object Detection from Fewer Data	❌	❌	✅	✅	✅	❌	✅	4
Protein Representation Learning by Geometric Structure Pretraining	❌	✅	✅	✅	✅	❌	✅	5
Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning	❌	✅	✅	❌	❌	❌	✅	3
Protein Sequence and Structure Co-Design with Equivariant Translation	✅	❌	✅	✅	✅	❌	✅	5
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks	✅	✅	✅	❌	❌	❌	✅	4
Prototypical Calibration for Few-shot Learning of Language Models	❌	✅	✅	✅	✅	❌	✅	5
Provable Defense Against Geometric Transformations	✅	✅	✅	✅	✅	❌	✅	6
Provable Memorization Capacity of Transformers	❌	❌	✅	❌	✅	❌	✅	3
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization	✅	❌	✅	✅	✅	❌	✅	5
Provable Sim-to-real Transfer in Continuous Domain with Partial Observations	✅	❌	❌	❌	❌	❌	❌	1
Provably Auditing Ordinary Least Squares in Low Dimensions	✅	❌	✅	❌	✅	❌	✅	4
Provably Efficient Lifelong Reinforcement Learning with Linear Representation	✅	❌	❌	❌	❌	❌	✅	2
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path	✅	❌	❌	❌	❌	❌	✅	2
Pruning Deep Neural Networks from a Sparsity Perspective	✅	✅	✅	❌	❌	❌	✅	4
Pseudo-label Training and Model Inertia in Neural Machine Translation	❌	❌	✅	✅	❌	✅	✅	4
Pseudoinverse-Guided Diffusion Models for Inverse Problems	✅	❌	✅	✅	❌	❌	✅	4
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play	✅	❌	✅	✅	❌	❌	✅	4
Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore	✅	❌	✅	✅	❌	❌	✅	4
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots	✅	✅	✅	❌	❌	❌	✅	4
QAID: Question Answering Inspired Few-shot Intent Detection	❌	❌	✅	✅	✅	❌	✅	4
QuAnt: Quantum Annealing with Learnt Couplings	❌	✅	✅	✅	✅	✅	✅	6
Quality-Similar Diversity via Population Based Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Quantifying Memorization Across Neural Language Models	❌	❌	✅	❌	❌	❌	❌	1
Quantifying and Mitigating the Impact of Label Errors on Model Disparity Metrics	❌	✅	✅	❌	❌	❌	❌	2
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions	❌	✅	✅	✅	❌	❌	❌	3
Quantized Compressed Sensing with Score-Based Generative Models	✅	✅	✅	✅	❌	❌	✅	5
Quasi-optimal Reinforcement Learning with Continuous Actions	✅	✅	✅	❌	✅	❌	✅	5
REPAIR: REnormalizing Permuted Activations for Interpolation Repair	✅	✅	✅	✅	❌	❌	✅	5
REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH	❌	✅	✅	❌	❌	❌	✅	3
RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection	❌	❌	✅	✅	❌	❌	✅	3
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch	✅	✅	✅	❌	✅	❌	✅	5
ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs	✅	✅	✅	❌	✅	✅	✅	6
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning	❌	✅	✅	✅	✅	❌	✅	5
RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
RandProx: Primal-Dual Optimization Algorithms with Randomized Proximal Updates	✅	❌	❌	❌	❌	❌	❌	1
Random Laplacian Features for Learning with Hyperbolic Space	✅	❌	✅	✅	✅	❌	✅	5
Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images	❌	✅	✅	❌	❌	❌	✅	3
Re-Imagen: Retrieval-Augmented Text-to-Image Generator	❌	❌	✅	✅	✅	❌	✅	4
Re-calibrating Feature Attributions for Model Interpretation	✅	✅	✅	✅	✅	✅	✅	7
Re-parameterizing Your Optimizers rather than Architectures	❌	✅	✅	✅	✅	❌	✅	5
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization	✅	❌	✅	❌	✅	❌	✅	4
ReAct: Synergizing Reasoning and Acting in Language Models	❌	✅	✅	❌	❌	❌	✅	3
Real-Time Image Demoir$\acute{e}$ing on Mobile Devices	❌	✅	✅	✅	✅	❌	✅	5
Real-time variational method for learning neural trajectory and its dynamics	✅	❌	✅	❌	✅	❌	✅	4
Recitation-Augmented Language Models	✅	✅	✅	✅	✅	❌	✅	6
Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning	✅	✅	✅	❌	❌	❌	✅	4
Recursive Time Series Data Augmentation	✅	✅	✅	❌	✅	❌	✅	5
Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors	✅	✅	✅	❌	✅	❌	✅	5
Regression with Label Differential Privacy	✅	❌	✅	❌	❌	❌	✅	3
Relational Attention: Generalizing Transformers for Graph-Structured Tasks	❌	✅	✅	✅	✅	❌	✅	5
Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences	❌	✅	✅	❌	❌	❌	✅	3
Relative representations enable zero-shot latent space communication	❌	✅	✅	✅	❌	❌	✅	4
Reliability of CKA as a Similarity Measure in Deep Learning	✅	❌	✅	❌	❌	❌	✅	3
Reparameterization through Spatial Gradient Scaling	✅	✅	✅	✅	✅	❌	✅	6
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay	✅	❌	✅	❌	✅	❌	✅	4
Replicable Bandits	✅	❌	❌	❌	❌	❌	✅	2
Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency	✅	❌	❌	❌	❌	❌	❌	1
Representation Learning for Low-rank General-sum Markov Games	✅	✅	❌	❌	❌	❌	✅	3
Representational Dissimilarity Metric Spaces for Stochastic Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor	✅	✅	✅	✅	❌	❌	✅	5
Restricted Strong Convexity of Deep Learning Models with Smooth Activations	❌	❌	✅	❌	❌	❌	✅	2
Rethinking Graph Lottery Tickets: Graph Sparsity Matters	✅	❌	✅	✅	❌	❌	✅	4
Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation	❌	❌	✅	✅	✅	❌	✅	4
Rethinking Symbolic Regression: Morphology and Adaptability in the Context of Evolutionary Algorithms	✅	✅	✅	❌	❌	❌	✅	4
Rethinking skip connection model as a learnable Markov chain	✅	❌	✅	✅	✅	❌	✅	5
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
Rethinking the Expressive Power of GNNs via Graph Biconnectivity	✅	✅	✅	✅	✅	❌	✅	6
Retrieval-based Controllable Molecule Generation	✅	✅	✅	✅	✅	❌	✅	6
Reversible Column Networks	❌	✅	✅	✅	✅	❌	✅	5
Revisit Finetuning strategy for Few-Shot Learning to Transfer the Emdeddings	❌	✅	✅	✅	❌	❌	✅	4
Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective	✅	✅	✅	✅	❌	❌	✅	5
Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments	❌	✅	✅	❌	✅	❌	✅	4
Revisiting Populations in multi-agent Communication	❌	✅	✅	✅	❌	❌	✅	4
Revisiting Robustness in Graph Machine Learning	❌	✅	✅	✅	❌	❌	✅	4
Revisiting adapters with adversarial training	❌	❌	✅	✅	❌	✅	✅	4
Revisiting the Assumption of Latent Separability for Backdoor Defenses	❌	✅	✅	❌	✅	❌	✅	4
Revisiting the Entropy Semiring for Neural Speech Recognition	❌	✅	✅	✅	❌	❌	✅	4
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching	✅	✅	✅	❌	✅	❌	✅	5
Reward Design with Language Models	❌	✅	✅	❌	❌	❌	✅	3
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise	❌	✅	✅	✅	❌	❌	✅	4
Riemannian Metric Learning via Optimal Transport	❌	❌	✅	❌	✅	✅	✅	4
Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation	✅	✅	❌	❌	❌	❌	✅	3
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data	❌	✅	✅	✅	✅	❌	✅	5
Robust Active Distillation	✅	❌	✅	✅	✅	❌	✅	5
Robust Algorithms on Adaptive Inputs from Bounded Adversaries	✅	❌	❌	❌	✅	✅	✅	4
Robust Explanation Constraints for Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework	❌	✅	✅	❌	❌	❌	✅	3
Robust Graph Dictionary Learning	✅	✅	✅	✅	❌	❌	✅	5
Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms	✅	✅	✅	❌	❌	❌	✅	4
Robust Scheduling with GFlowNets	❌	❌	✅	❌	❌	❌	✅	2
Robust and Controllable Object-Centric Learning through Energy-based Models	✅	✅	✅	❌	✅	❌	✅	5
Robustness to corruption in pre-trained Bayesian neural networks	✅	✅	✅	✅	✅	❌	✅	6
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction	❌	✅	✅	✅	✅	✅	✅	6
S-NeRF: Neural Radiance Fields for Street Views	❌	✅	✅	✅	✅	❌	✅	5
SAM as an Optimal Relaxation of Bayes	✅	❌	✅	❌	❌	❌	✅	3
SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency	❌	✅	✅	❌	✅	❌	✅	4
SCoMoE: Efficient Mixtures of Experts with Structured Communication	❌	✅	✅	✅	✅	❌	✅	5
SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization	✅	❌	❌	❌	❌	❌	✅	2
SIMPLE: A Gradient Estimator for k-Subset Sampling	✅	✅	✅	✅	❌	❌	✅	5
SIMPLE: Specialized Model-Sample Matching for Domain Generalization	❌	✅	✅	✅	✅	❌	✅	5
SLTUNET: A Simple Unified Model for Sign Language Translation	❌	✅	✅	✅	❌	❌	✅	4
SMART: Self-supervised Multi-task pretrAining with contRol Transformers	❌	✅	✅	✅	❌	❌	✅	4
SMART: Sentences as Basic Units for Text Evaluation	✅	✅	✅	❌	❌	❌	✅	4
SP2 : A Second Order Stochastic Polyak Method	❌	❌	✅	❌	❌	❌	✅	2
SQA3D: Situated Question Answering in 3D Scenes	❌	✅	✅	✅	❌	❌	✅	4
STREET: A MULTI-TASK STRUCTURED REASONING AND EXPLANATION BENCHMARK	✅	✅	✅	✅	✅	✅	✅	7
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables	✅	✅	✅	✅	❌	❌	✅	5
STaSy: Score-based Tabular data Synthesis	✅	✅	✅	✅	✅	✅	✅	7
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication	✅	✅	✅	❌	✅	❌	✅	5
SYNC: SAFETY-AWARE NEURAL CONTROL FOR STABILIZING STOCHASTIC DELAY-DIFFERENTIAL EQUATIONS	✅	✅	❌	❌	❌	❌	✅	3
Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL	✅	❌	❌	❌	❌	❌	❌	1
Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation	✅	✅	✅	❌	❌	❌	✅	4
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks	✅	❌	✅	❌	❌	❌	✅	3
Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier	❌	❌	✅	❌	✅	❌	✅	3
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions	❌	❌	❌	❌	❌	❌	❌	0
Sampling with Mollified Interaction Energy Descent	✅	✅	✅	✅	❌	❌	✅	5
Sampling-based inference for large linear models, with application to linearised Laplace	✅	✅	✅	✅	✅	❌	✅	6
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks	✅	✅	✅	❌	✅	❌	✅	5
Scaffolding a Student to Instill Knowledge	✅	✅	✅	✅	❌	❌	✅	5
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing	✅	✅	✅	✅	❌	❌	✅	5
Scalable Subset Sampling with Neural Conditional Poisson Networks	✅	❌	✅	✅	❌	❌	✅	4
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions	✅	❌	✅	✅	✅	❌	✅	5
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel	✅	✅	✅	✅	✅	❌	✅	6
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting	✅	✅	✅	❌	✅	❌	✅	5
Scaling Forward Gradient With Local Losses	✅	✅	✅	❌	❌	❌	✅	4
Scaling Laws For Deep Learning Based Image Reconstruction	❌	✅	✅	✅	✅	❌	✅	5
Scaling Laws for a Multi-Agent Reinforcement Learning Model	❌	✅	❌	❌	❌	❌	✅	2
Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL	✅	✅	✅	❌	❌	❌	✅	4
Scaling Up Probabilistic Circuits by Latent Variable Distillation	✅	✅	✅	✅	✅	❌	✅	6
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation	❌	❌	❌	✅	✅	❌	✅	3
Scenario-based Question Answering with Interacting Contextual Properties	❌	✅	✅	✅	❌	❌	✅	4
Schema Inference for Interpretable Image Classification	✅	✅	✅	❌	✅	✅	✅	6
Score-based Continuous-time Discrete Diffusion Models	❌	❌	✅	✅	✅	❌	✅	4
SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective	✅	❌	✅	✅	✅	❌	✅	5
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning	✅	❌	✅	❌	✅	❌	✅	4
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning	✅	❌	✅	❌	✅	❌	✅	4
Selective Annotation Makes Language Models Better Few-Shot Learners	✅	✅	✅	✅	❌	❌	✅	5
Selective Frequency Network for Image Restoration	❌	✅	✅	❌	✅	❌	✅	4
Self-Consistency Improves Chain of Thought Reasoning in Language Models	❌	❌	✅	✅	✅	❌	✅	4
Self-Distillation for Further Pre-training of Transformers	✅	❌	✅	❌	✅	❌	✅	4
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors	✅	✅	✅	✅	✅	❌	✅	6
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning	✅	✅	✅	✅	❌	❌	✅	5
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability	✅	✅	✅	❌	❌	❌	✅	4
Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance	❌	✅	✅	❌	❌	✅	✅	4
Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild	❌	✅	✅	❌	❌	❌	✅	3
Self-Supervised Set Representation Learning for Unsupervised Meta-Learning	✅	✅	✅	✅	❌	❌	✅	5
Self-supervised learning with rotation-invariant kernels	❌	✅	✅	✅	✅	❌	✅	5
Self-supervision through Random Segments with Autoregressive Coding (RandSAC)	✅	❌	✅	❌	❌	❌	✅	3
SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations	✅	✅	✅	✅	✅	❌	✅	6
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation	✅	✅	✅	❌	✅	❌	✅	5
Semi-Implicit Variational Inference via Score Matching	✅	❌	✅	✅	✅	❌	✅	5
Semi-Parametric Inducing Point Networks and Neural Processes	❌	✅	✅	✅	✅	❌	✅	5
Semi-supervised Community Detection via Structural Similarity Metrics	✅	✅	✅	✅	❌	❌	✅	5
Semi-supervised learning with a principled likelihood from a generative model of data curation	❌	✅	✅	❌	✅	❌	✅	4
Sequential Attention for Feature Selection	✅	✅	✅	❌	❌	❌	✅	4
Sequential Gradient Coding For Straggler Mitigation	✅	✅	✅	❌	✅	❌	✅	5
Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
Sequential Learning of Neural Networks for Prequential MDL	✅	❌	✅	✅	❌	❌	✅	4
Serving Graph Compression for Graph Neural Networks	✅	❌	✅	✅	❌	❌	✅	4
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process	✅	❌	❌	❌	❌	❌	❌	1
Short-Term Memory Convolutions	❌	❌	✅	❌	✅	❌	✅	3
Sign and Basis Invariant Networks for Spectral Graph Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
SimPer: Simple Self-Supervised Learning of Periodic Targets	✅	✅	✅	✅	❌	❌	✅	5
Simple Emergent Action Representations from Multi-Task Policy Training	✅	❌	✅	✅	❌	❌	✅	4
Simple and Scalable Nearest Neighbor Machine Translation	❌	✅	✅	✅	✅	❌	✅	5
Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth	❌	❌	✅	✅	❌	❌	✅	3
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification	❌	✅	✅	✅	✅	❌	✅	5
Simplicial Hopfield networks	❌	✅	✅	❌	❌	❌	✅	3
Simplified State Space Layers for Sequence Modeling	✅	✅	✅	✅	✅	❌	✅	6
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective	✅	✅	✅	❌	❌	❌	✅	4
Single-shot General Hyper-parameter Optimization for Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
SketchKnitter: Vectorized Sketch Generation with Diffusion Models	❌	❌	✅	❌	✅	❌	✅	3
SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models	❌	❌	✅	✅	✅	✅	✅	5
SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing	❌	❌	✅	❌	✅	❌	✅	3
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language	❌	✅	✅	❌	✅	❌	✅	4
Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning	❌	❌	✅	✅	✅	❌	✅	4
SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning	✅	✅	✅	✅	✅	❌	✅	6
SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments	❌	✅	❌	❌	❌	❌	✅	2
Softened Symbol Grounding for Neuro-symbolic Systems	✅	✅	✅	❌	❌	❌	✅	4
Solving Constrained Variational Inequalities via a First-order Interior Point-based Method	✅	✅	✅	❌	✅	❌	✅	5
Solving Continuous Control via Q-learning	❌	❌	✅	❌	✅	❌	✅	3
Solving stochastic weak Minty variational inequalities without increasing batch size	✅	❌	❌	❌	❌	❌	✅	2
Sound Randomized Smoothing in Floating-Point Arithmetic	✅	✅	✅	❌	✅	❌	✅	5
Spacetime Representation Learning	✅	❌	✅	✅	✅	❌	✅	5
Sparse Distributed Memory is a Continual Learner	✅	✅	✅	✅	❌	❌	✅	5
Sparse Mixture-of-Experts are Domain Generalizable Learners	✅	❌	✅	✅	❌	❌	✅	4
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers	✅	✅	✅	❌	✅	❌	✅	5
Sparse Random Networks for Communication-Efficient Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
Sparse Token Transformer with Attention Back Tracking	✅	❌	✅	✅	❌	❌	✅	4
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints	✅	✅	✅	✅	✅	❌	✅	6
Sparse tree-based Initialization for Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!	❌	✅	✅	✅	✅	❌	✅	5
Sparsity-Constrained Optimal Transport	❌	❌	✅	✅	✅	❌	✅	4
Spatial Attention Kinetic Networks with E(n)-Equivariance	✅	✅	✅	✅	✅	❌	✅	6
Spatio-temporal point processes with deep non-stationary kernels	✅	❌	✅	❌	✅	❌	✅	4
Specformer: Spectral Graph Neural Networks Meet Transformers	❌	✅	✅	✅	✅	✅	✅	6
Spectral Augmentation for Self-Supervised Learning on Graphs	✅	❌	✅	✅	✅	❌	✅	5
Spectral Decomposition Representation for Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
SpeedyZero: Mastering Atari with Limited Data and Time	❌	❌	✅	❌	✅	❌	✅	3
Spherical Sliced-Wasserstein	✅	✅	✅	❌	❌	❌	✅	4
Spikformer: When Spiking Neural Network Meets Transformer	❌	❌	✅	✅	❌	❌	✅	3
Spiking Convolutional Neural Networks for Text Classification	✅	✅	✅	❌	❌	❌	✅	4
Spotlight: Mobile UI Understanding using Vision-Language Models with a Focus	✅	❌	✅	✅	✅	❌	✅	5
Squeeze Training for Adversarial Robustness	✅	✅	✅	❌	✅	❌	✅	5
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random	✅	✅	✅	❌	✅	❌	✅	5
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions	✅	✅	✅	✅	✅	❌	✅	6
Statistical Efficiency of Score Matching: The View from Isoperimetry	❌	❌	❌	❌	❌	❌	✅	1
Statistical Guarantees for Consensus Clustering	✅	❌	❌	❌	❌	❌	✅	2
Statistical Inference for Fisher Market Equilibrium	❌	❌	❌	❌	❌	❌	✅	1
Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms	❌	❌	✅	❌	❌	❌	❌	1
Stay Moral and Explore: Learn to Behave Morally in Text-based Games	✅	✅	✅	❌	❌	❌	✅	4
Stochastic Differentially Private and Fair Learning	✅	❌	✅	✅	❌	❌	✅	4
Stochastic Multi-Person 3D Motion Forecasting	❌	❌	✅	❌	✅	❌	✅	3
Stochastic No-regret Learning for General Games with Variance Reduction	✅	❌	❌	❌	❌	❌	❌	1
Strategic Classification with Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Strong inductive biases provably prevent harmless interpolation	❌	✅	✅	❌	❌	❌	✅	3
StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training	❌	✅	✅	✅	✅	❌	✅	5
Structure by Architecture: Structured Representations without Regularization	❌	✅	✅	✅	✅	❌	✅	5
StyleMorph: Disentangled 3D-Aware Image Synthesis with a 3D Morphable StyleGAN	❌	❌	✅	❌	❌	❌	❌	1
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks	✅	✅	❌	✅	❌	❌	✅	4
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation	✅	❌	✅	❌	❌	❌	❌	2
Subsampling in Large Graphs Using Ricci Curvature	✅	❌	✅	❌	✅	❌	✅	4
Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees	✅	✅	✅	✅	✅	❌	✅	6
Supervision Complexity and its Role in Knowledge Distillation	✅	❌	✅	❌	❌	❌	✅	3
Suppressing the Heterogeneity: A Strong Feature Extractor for Few-shot Segmentation	❌	❌	✅	✅	✅	❌	✅	4
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts	❌	❌	✅	✅	❌	❌	✅	3
Switch-NeRF: Learning Scene Decomposition with Mixture of Experts for Large-scale Neural Radiance Fields	❌	✅	✅	✅	✅	❌	✅	5
Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search	✅	❌	✅	✅	✅	❌	✅	5
Symmetric Pruning in Quantum Neural Networks	✅	❌	❌	❌	❌	❌	✅	2
Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow	❌	✅	✅	❌	❌	❌	✅	3
Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation	✅	✅	✅	✅	✅	❌	✅	6
Systematic Rectification of Language Models via Dead-end Analysis	❌	✅	✅	✅	❌	❌	✅	4
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization	✅	✅	✅	✅	✅	❌	✅	6
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations	✅	✅	✅	❌	✅	❌	✅	5
TEMPERA: Test-Time Prompt Editing via Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs	❌	❌	✅	✅	❌	❌	✅	3
TTN: A Domain-Shift Aware Batch Normalization in Test-Time Adaptation	✅	❌	✅	❌	❌	❌	✅	3
TVSPrune - Pruning Non-discriminative filters via Total Variation separability of intermediate representations without fine tuning	✅	✅	✅	✅	✅	❌	✅	6
TabCaps: A Capsule Neural Network for Tabular Data Classification with BoW Routing	❌	✅	✅	✅	✅	✅	✅	6
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second	✅	✅	✅	✅	✅	❌	✅	6
Tailoring Language Generation Models under Total Variation Distance	❌	✅	✅	✅	❌	❌	✅	4
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives	✅	✅	✅	✅	❌	❌	✅	5
Task Ambiguity in Humans and Language Models	❌	✅	✅	✅	❌	❌	✅	4
Task-Aware Information Routing from Common Representation Space in Lifelong Learning	✅	✅	✅	❌	❌	❌	❌	3
Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts	❌	❌	✅	❌	✅	❌	✅	3
TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding	❌	✅	✅	✅	❌	❌	✅	4
Teacher Guided Training: An Efficient Framework for Knowledge Transfer	❌	❌	✅	❌	❌	❌	✅	2
TempCLR: Temporal Alignment Representation with Contrastive Learning	❌	✅	✅	✅	✅	❌	✅	5
Temperature Schedules for self-supervised contrastive methods on long-tail data	✅	✅	✅	✅	❌	❌	✅	5
Temporal Coherent Test Time Optimization for Robust Video Classification	❌	❌	✅	❌	❌	❌	✅	2
Temporal Dependencies in Feature Importance for Time Series Prediction	✅	✅	✅	✅	✅	❌	✅	6
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Tensor-Based Sketching Method for the Low-Rank Approximation of Data Streams.	✅	❌	✅	❌	✅	❌	✅	4
Test-Time Adaptation via Self-Training with Nearest Neighbor Information	✅	✅	✅	✅	✅	❌	✅	6
Test-Time Robust Personalization for Federated Learning	✅	✅	✅	✅	❌	❌	✅	5
Text Summarization with Oracle Expectation	✅	✅	✅	✅	✅	❌	✅	6
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization	❌	✅	✅	✅	✅	❌	✅	5
TextShield: Beyond Successfully Detecting Adversarial Sentences in text classification	❌	❌	✅	✅	✅	❌	✅	4
Thalamus: a brain-inspired algorithm for biologically-plausible continual learning and disentangled representations	✅	✅	✅	❌	❌	❌	✅	4
That Label's got Style: Handling Label Style Bias for Uncertain Image Segmentation	❌	❌	✅	✅	❌	❌	✅	3
The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks	❌	✅	❌	❌	❌	✅	✅	3
The Augmented Image Prior: Distilling 1000 Classes by Extrapolating from a Single Image	❌	✅	✅	✅	✅	❌	✅	5
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation	✅	❌	✅	❌	✅	❌	✅	4
The Curious Case of Benign Memorization	❌	✅	✅	❌	❌	❌	✅	3
The Dark Side of AutoML: Towards Architectural Backdoor Search	✅	✅	✅	❌	❌	❌	✅	4
The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition	✅	✅	✅	✅	❌	❌	✅	5
The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks	❌	❌	✅	✅	❌	❌	✅	3
The In-Sample Softmax for Offline Reinforcement Learning	❌	✅	✅	❌	❌	✅	✅	4
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks	✅	❌	❌	❌	❌	❌	✅	2
The KFIoU Loss for Rotated Object Detection	❌	✅	✅	✅	✅	❌	✅	5
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers	❌	❌	✅	❌	✅	❌	✅	3
The Lie Derivative for Measuring Learned Equivariance	✅	✅	✅	✅	❌	❌	✅	5
The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation	✅	✅	✅	✅	❌	❌	✅	5
The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes	❌	❌	✅	✅	❌	❌	✅	3
The Power of Regularization in Solving Extensive-Form Games	✅	❌	✅	❌	❌	❌	❌	2
The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
The Role of Coverage in Online Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
The Role of ImageNet Classes in Fréchet Inception Distance	✅	✅	✅	✅	✅	❌	✅	6
The Surprising Computational Power of Nondeterministic Stack RNNs	❌	✅	✅	✅	❌	❌	✅	4
The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry	❌	✅	✅	✅	❌	✅	✅	5
The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium	✅	✅	✅	❌	✅	❌	✅	5
The Tilted Variational Autoencoder: Improving Out-of-Distribution Detection	❌	✅	✅	❌	✅	❌	✅	4
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning	❌	✅	✅	✅	❌	❌	✅	4
The hidden uniform cluster prior in self-supervised learning	❌	✅	✅	✅	❌	❌	✅	4
Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning	❌	❌	✅	✅	❌	❌	✅	3
This Looks Like It Rather Than That: ProtoKNN For Similarity-Based Classifiers	❌	❌	✅	❌	✅	❌	✅	3
TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization	✅	❌	✅	❌	❌	❌	✅	3
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors	❌	✅	✅	❌	❌	❌	❌	2
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection	❌	✅	✅	✅	✅	❌	✅	5
Time to augment self-supervised visual representation learning	❌	✅	✅	✅	✅	❌	✅	5
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis	❌	✅	✅	✅	✅	✅	✅	6
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints	✅	❌	✅	❌	❌	❌	✅	3
Toeplitz Neural Network for Sequence Modeling	❌	✅	✅	✅	✅	❌	✅	5
Token Merging: Your ViT But Faster	✅	✅	✅	✅	✅	❌	✅	6
Topology-aware Robust Optimization for Out-of-Distribution Generalization	✅	✅	✅	✅	❌	❌	✅	5
Toward Adversarial Training on Contextualized Language Representation	✅	✅	✅	✅	✅	❌	✅	6
Towards Addressing Label Skews in One-Shot Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
Towards Better Selective Classification	❌	✅	✅	✅	✅	❌	✅	5
Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective	❌	❌	❌	❌	✅	❌	✅	2
Towards Inferential Reproducibility of Machine Learning Research	❌	✅	✅	❌	✅	❌	✅	4
Towards Interpretable Deep Reinforcement Learning with Human-Friendly Prototypes	✅	✅	✅	❌	❌	❌	✅	4
Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection	❌	❌	✅	❌	✅	✅	✅	4
Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs	✅	❌	❌	❌	❌	❌	❌	1
Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case	✅	✅	✅	❌	✅	✅	✅	6
Towards Open Temporal Graph Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Towards Robust Object Detection Invariant to Real-World Domain Shifts	✅	❌	✅	✅	❌	❌	✅	4
Towards Robustness Certification Against Universal Perturbations	❌	✅	✅	✅	✅	❌	✅	5
Towards Smooth Video Composition	❌	✅	✅	❌	✅	❌	✅	4
Towards Stable Test-time Adaptation in Dynamic Wild World	✅	✅	✅	❌	✅	❌	✅	5
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning	❌	❌	✅	❌	❌	❌	❌	1
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation	✅	❌	❌	❌	❌	❌	✅	2
Towards Understanding Why Mask Reconstruction Pretraining Helps in Downstream Tasks	❌	❌	✅	❌	❌	❌	❌	1
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism	✅	✅	✅	❌	✅	❌	✅	5
Towards convergence to Nash equilibria in two-team zero-sum games	❌	❌	✅	❌	❌	❌	✅	2
Towards the Generalization of Contrastive Self-Supervised Learning	❌	❌	✅	❌	❌	❌	✅	2
Trading Information between Latents in Hierarchical Variational Autoencoders	❌	✅	✅	❌	✅	❌	✅	4
Trainability Preserving Neural Pruning	✅	✅	✅	✅	✅	❌	✅	6
Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions	✅	✅	✅	❌	✅	❌	✅	5
Training language models to summarize narratives improves brain alignment	✅	✅	✅	✅	❌	❌	✅	5
Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis	✅	✅	❌	❌	❌	✅	✅	4
TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation	❌	❌	✅	❌	✅	❌	✅	3
Transfer Learning with Deep Tabular Models	❌	✅	✅	✅	✅	❌	✅	5
Transfer NAS with Meta-learned Bayesian Surrogates	✅	✅	✅	✅	❌	❌	✅	5
Transferable Unlearnable Examples	❌	✅	✅	✅	❌	❌	✅	4
Transformer Meets Boundary Value Inverse Problems	❌	✅	✅	✅	✅	❌	✅	5
Transformer-Patcher: One Mistake Worth One Neuron	❌	✅	✅	✅	✅	❌	✅	5
Transformer-based World Models Are Happy With 100k Interactions	✅	✅	✅	❌	✅	❌	✅	5
Transformer-based model for symbolic regression via joint supervised learning	❌	✅	✅	✅	✅	❌	✅	5
Transformers Learn Shortcuts to Automata	✅	❌	❌	❌	✅	❌	✅	3
Transformers are Sample-Efficient World Models	✅	✅	✅	❌	✅	❌	✅	5
Treeformer: Dense Gradient Trees for Efficient Attention Computation	✅	❌	✅	❌	✅	❌	✅	4
TrojText: Test-time Invisible Textual Trojan Insertion	✅	✅	✅	✅	❌	❌	✅	5
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders	✅	✅	✅	❌	✅	✅	✅	6
Truthful Self-Play	✅	❌	✅	❌	❌	❌	✅	3
Tuning Frequency Bias in Neural Network Training with Nonuniform Data	❌	❌	✅	❌	❌	❌	✅	2
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection	✅	✅	✅	❌	❌	❌	❌	3
TypeT5: Seq2seq Type Inference using Static Analysis	❌	✅	✅	✅	✅	❌	✅	5
UL2: Unifying Language Learning Paradigms	✅	✅	✅	✅	✅	❌	✅	6
UNICORN: A Unified Backdoor Trigger Inversion Framework	❌	✅	✅	❌	✅	✅	✅	5
UNIFIED-IO: A Unified Model for Vision, Language, and Multi-modal Tasks	❌	✅	✅	❌	❌	❌	✅	3
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States	✅	❌	✅	✅	✅	❌	✅	5
Unbiased Supervised Contrastive Learning	❌	✅	✅	❌	✅	✅	✅	5
Understanding DDPM Latent Codes Through Optimal Transport	❌	✅	✅	❌	❌	❌	✅	3
Understanding Edge-of-Stability Training Dynamics with a Minimalist Example	❌	❌	✅	❌	❌	❌	✅	2
Understanding Embodied Reference with Touch-Line Transformer	❌	✅	✅	✅	✅	❌	✅	5
Understanding Influence Functions and Datamodels via Harmonic Analysis	✅	❌	✅	❌	❌	❌	✅	3
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles	❌	✅	✅	❌	❌	❌	✅	3
Understanding The Robustness of Self-supervised Learning Through Topic Modeling	❌	❌	✅	✅	✅	❌	✅	4
Understanding Train-Validation Split in Meta-Learning with Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
Understanding Why Generalized Reweighting Does Not Improve Over ERM	❌	❌	✅	❌	❌	❌	✅	2
Understanding Zero-shot Adversarial Robustness for Large-Scale Models	✅	✅	✅	❌	❌	❌	✅	4
Understanding and Adopting Rational Behavior by Bellman Score Estimation	✅	❌	✅	❌	❌	❌	❌	2
Understanding new tasks through the lens of training data via exponential tilting	✅	✅	✅	✅	❌	❌	✅	5
Understanding the Covariance Structure of Convolutional Filters	❌	✅	✅	❌	❌	❌	✅	3
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization	❌	❌	✅	❌	❌	❌	✅	2
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning	❌	❌	✅	❌	❌	❌	✅	2
Understanding weight-magnitude hyperparameters in training binary networks	❌	✅	✅	❌	✅	❌	✅	4
Uni-Mol: A Universal 3D Molecular Representation Learning Framework	✅	✅	✅	✅	✅	❌	✅	6
UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph	❌	✅	✅	✅	❌	❌	✅	4
UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining	✅	✅	✅	✅	✅	❌	✅	6
Unicom: Universal and Compact Representation Learning for Image Retrieval	❌	✅	✅	✅	✅	❌	✅	5
Unified Detoxifying and Debiasing in Language Generation via Inference-time Adaptive Optimization	✅	❌	✅	❌	✅	❌	✅	4
Unified Discrete Diffusion for Simultaneous Vision-Language Generation	❌	✅	✅	❌	✅	❌	✅	4
Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics	❌	❌	❌	❌	❌	❌	✅	1
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching	❌	✅	✅	✅	❌	❌	✅	4
Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval	❌	✅	✅	✅	❌	❌	✅	4
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask?	✅	❌	✅	❌	❌	❌	✅	3
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity	❌	❌	✅	❌	❌	❌	✅	2
Unsupervised Learning for Combinatorial Optimization Needs Meta Learning	✅	✅	✅	✅	✅	✅	✅	7
Unsupervised Manifold Alignment with Joint Multidimensional Scaling	✅	✅	✅	❌	✅	❌	✅	5
Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised Model Selection for Time Series Anomaly Detection	❌	✅	✅	✅	✅	✅	✅	6
Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised visualization of image datasets using contrastive learning	❌	✅	✅	✅	✅	✅	✅	6
Unveiling the sampling density in non-uniform geometric graphs	❌	❌	✅	✅	❌	❌	✅	3
User-Interactive Offline Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks	✅	✅	✅	✅	❌	❌	✅	5
Using Language to Extend to Unseen Domains	❌	✅	✅	✅	✅	❌	✅	5
VA-DepthNet: A Variational Approach to Single Image Depth Prediction	❌	✅	✅	✅	✅	✅	✅	6
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training	✅	✅	✅	❌	❌	❌	✅	4
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation	✅	✅	✅	❌	✅	❌	✅	5
Valid P-Value for Deep Learning-driven Salient Region	✅	✅	✅	❌	❌	❌	✅	4
Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top	✅	✅	✅	❌	✅	✅	✅	6
Variance-Aware Sparse Linear Bandits	✅	❌	❌	❌	❌	❌	❌	1
Variational Information Pursuit for Interpretable Predictions	❌	✅	✅	❌	✅	✅	✅	5
Variational Latent Branching Model for Off-Policy Evaluation	✅	✅	✅	❌	✅	❌	✅	5
Verifying the Union of Manifolds Hypothesis for Image Data	✅	✅	✅	✅	❌	❌	✅	5
Versatile Neural Processes for Learning Implicit Neural Representations	❌	✅	✅	❌	❌	❌	❌	2
Video Scene Graph Generation from Single-Frame Weak Supervision	❌	✅	✅	❌	❌	❌	✅	3
View Synthesis with Sculpted Neural Points	✅	✅	✅	❌	✅	❌	✅	5
ViewCo: Discovering Text-Supervised Segmentation Masks via Multi-View Semantic Consistency	❌	✅	✅	✅	❌	❌	✅	4
Vision Transformer Adapter for Dense Predictions	❌	❌	✅	✅	✅	❌	✅	4
Visual Classification via Description from Large Language Models	❌	❌	✅	✅	❌	❌	✅	3
Visual Imitation Learning with Patch Rewards	✅	✅	✅	❌	❌	❌	✅	4
Visual Recognition with Deep Nearest Centroids	✅	✅	✅	✅	✅	❌	✅	6
Visually-Augmented Language Modeling	❌	✅	✅	❌	✅	❌	✅	4
VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis	❌	✅	✅	❌	❌	✅	✅	4
Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding	❌	✅	✅	✅	✅	❌	✅	5
Volumetric Optimal Transportation by Fast Fourier Transform	✅	❌	❌	❌	✅	❌	✅	3
Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction	❌	✅	✅	❌	✅	❌	❌	3
Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning	❌	✅	✅	✅	✅	❌	✅	5
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees	✅	✅	✅	❌	✅	✅	✅	6
Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic	❌	✅	✅	✅	❌	❌	✅	4
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection	✅	✅	✅	✅	❌	❌	✅	5
Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Weighted Clock Logic Point Process	✅	✅	✅	✅	✅	✅	✅	7
Weighted Ensemble Self-Supervised Learning	✅	❌	✅	✅	✅	❌	✅	5
What Can we Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers?	❌	✅	✅	✅	❌	✅	✅	5
What Do Self-Supervised Vision Transformers Learn?	❌	✅	✅	✅	✅	❌	✅	5
What Is Missing in IRM Training and Evaluation? Challenges and Solutions	✅	✅	✅	❌	❌	❌	✅	4
What Makes Convolutional Models Great on Long Sequence Modeling?	✅	✅	✅	✅	❌	❌	✅	5
What shapes the loss landscape of self supervised learning?	❌	❌	✅	❌	❌	❌	✅	2
When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
When Source-Free Domain Adaptation Meets Learning with Noisy Labels	✅	❌	✅	❌	❌	❌	✅	3
When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It?	❌	✅	✅	✅	✅	❌	✅	5
When to Make and Break Commitments?	✅	✅	❌	❌	❌	❌	✅	3
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning	✅	❌	✅	❌	❌	✅	✅	4
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions	✅	❌	✅	❌	✅	❌	❌	3
Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks	❌	❌	✅	❌	❌	❌	✅	2
Why (and When) does Local SGD Generalize Better than SGD?	✅	✅	✅	❌	✅	✅	✅	6
Why adversarial training can hurt robust accuracy	❌	❌	✅	✅	❌	❌	✅	3
WiNeRT: Towards Neural Ray Tracing for Wireless Channel Modelling and Differentiable Simulations	❌	❌	✅	✅	✅	❌	✅	4
WikiWhy: Answering and Explaining Cause-and-Effect Questions	❌	✅	✅	✅	❌	❌	✅	4
Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms	✅	✅	✅	❌	❌	❌	✅	4
Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic	❌	❌	✅	❌	✅	❌	✅	3
Words are all you need? Language as an approximation for human similarity judgments	❌	✅	✅	✅	✅	❌	❌	4
Write and Paint: Generative Vision-Language Models are Unified Modal Learners	❌	✅	✅	✅	✅	❌	✅	5
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding	❌	❌	✅	✅	❌	❌	✅	3
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model	✅	✅	✅	❌	✅	❌	✅	5
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation	✅	✅	✅	❌	❌	❌	✅	4
ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients	✅	✅	✅	✅	✅	❌	✅	6
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation	✅	❌	✅	❌	❌	❌	✅	3
gDDIM: Generalized denoising diffusion implicit models	✅	✅	✅	❌	✅	❌	✅	5
kNN-Diffusion: Image Generation via Large-Scale Retrieval	✅	❌	✅	✅	✅	❌	✅	5
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing	❌	✅	✅	✅	✅	❌	✅	5
wav2tok: Deep Sequence Tokenizer for Audio Retrieval	❌	✅	✅	✅	❌	❌	✅	4
What learning algorithm is in-context learning? Investigations with linear models	❌	✅	❌	❌	✅	❌	✅	3