Reproducibility Index

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

International Conference on Learning Representations (ICLR) - 2024

Documentation Rate of Empirical Papers by Reproducibility Variable

Distribution of Empirical Papers by Number of Documented Variables

Website:

Venue	Year	Papers	Reproducibility Score Reproducibility Score based on Gundersen et al. (2025). See Methods for details.	Documentation Score Documentation Score is the average score over the seven reproducibility variables for empirical research papers. See Methods for details.	% Empirical Percentage of papers that are empirical research vs theoretical research.	% Industry Percentage of empirical research papers with at least one author from Industry.	Website
ICLR	2024	2260	0.66	4.27	97.43%	48.86%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection	✅	✅	✅	✅	✅	❌	✅	6
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models	✅	❌	✅	❌	❌	❌	✅	3
$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity	❌	✅	✅	❌	✅	❌	✅	4
$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States	❌	✅	✅	❌	✅	❌	✅	4
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning	✅	✅	✅	✅	✅	❌	✅	6
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis	✅	❌	✅	✅	✅	❌	✅	5
$\pi$2vec: Policy Representation with Successor Features	❌	❌	✅	✅	❌	❌	✅	3
$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation	❌	✅	✅	❌	✅	❌	✅	4
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence	✅	✅	✅	✅	✅	✅	✅	7
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining	❌	✅	✅	✅	✅	❌	✅	5
3D Reconstruction with Generalizable Neural Fields using Scene Priors	✅	❌	✅	❌	✅	❌	✅	4
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation	❌	❌	✅	❌	✅	❌	✅	3
A 2-Dimensional State Space Layer for Spatial Inductive Bias	❌	✅	✅	✅	❌	❌	✅	4
A Benchmark Study on Calibration	❌	✅	✅	✅	❌	❌	✅	4
A Benchmark for Learning to Translate a New Language from One Grammar Book	❌	✅	✅	✅	❌	❌	✅	4
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
A Branching Decoder for Set Generation	✅	✅	✅	✅	✅	✅	✅	7
A Characterization Theorem for Equivariant Networks with Point-wise Activations	❌	❌	❌	❌	❌	❌	❌	0
A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks	✅	❌	✅	❌	✅	✅	✅	5
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection	✅	❌	✅	✅	❌	❌	✅	4
A Differentially Private Clustering Algorithm for Well-Clustered Graphs	✅	❌	❌	❌	✅	✅	✅	4
A Discretization Framework for Robust Contextual Stochastic Optimization	✅	❌	✅	❌	❌	❌	✅	3
A Dynamical View of the Question of Why	❌	✅	❌	❌	❌	❌	✅	2
A Fast and Provable Algorithm for Sparse Phase Retrieval	✅	✅	❌	❌	✅	❌	✅	4
A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality	✅	❌	✅	❌	✅	✅	✅	5
A Foundation Model for Error Correction Codes	❌	❌	✅	❌	✅	❌	✅	3
A Framework for Inference Inspired by Human Memory Mechanisms	✅	✅	✅	✅	❌	❌	✅	5
A General Framework for User-Guided Bayesian Optimization	✅	✅	✅	❌	❌	❌	✅	4
A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation	❌	✅	✅	✅	✅	❌	✅	5
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation	✅	✅	✅	✅	✅	❌	✅	6
A Hierarchical Bayesian Model for Few-Shot Meta Learning	✅	✅	✅	✅	❌	❌	✅	5
A Lie Group Approach to Riemannian Batch Normalization	✅	✅	✅	✅	✅	❌	✅	6
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging	✅	✅	✅	❌	✅	❌	✅	5
A Linear Algebraic Framework for Counterfactual Generation	❌	❌	✅	❌	❌	❌	✅	2
A Multi-Level Framework for Accelerating Training Transformer Models	✅	✅	✅	✅	✅	❌	✅	6
A Mutual Information Perspective on Federated Contrastive Learning	✅	❌	✅	❌	❌	❌	✅	3
A Neural Framework for Generalized Causal Sensitivity Analysis	✅	✅	✅	✅	❌	❌	✅	5
A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines	❌	✅	❌	❌	❌	❌	✅	2
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
A Plug-and-Play Image Registration Network	❌	❌	✅	❌	❌	❌	✅	2
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs	❌	❌	✅	✅	✅	❌	✅	4
A Policy Gradient Method for Confounded POMDPs	✅	❌	❌	❌	❌	❌	✅	2
A Precise Characterization of SGD Stability Using Loss Surface Geometry	❌	✅	❌	❌	❌	❌	✅	2
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints	✅	✅	✅	❌	✅	❌	✅	5
A Probabilistic Framework for Modular Continual Learning	✅	✅	✅	✅	✅	✅	✅	7
A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model	✅	✅	✅	❌	❌	❌	✅	4
A Quadratic Synchronization Rule for Distributed Deep Learning	✅	❌	✅	❌	✅	❌	✅	4
A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER	✅	❌	✅	❌	✅	❌	✅	4
A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis	❌	❌	✅	❌	✅	✅	✅	4
A Recipe for Improved Certifiable Robustness	❌	❌	✅	❌	✅	❌	✅	3
A Restoration Network as an Implicit Prior	✅	✅	✅	❌	❌	❌	✅	4
A Semantic Invariant Robust Watermark for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis	❌	✅	✅	❌	❌	❌	✅	3
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction	❌	❌	✅	✅	✅	❌	✅	4
A Simple and Effective Pruning Approach for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
A Simple and Scalable Representation for Graph Generation	❌	✅	✅	✅	✅	❌	✅	5
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks	✅	❌	✅	✅	✅	❌	✅	5
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data	❌	✅	✅	❌	❌	❌	✅	3
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization	❌	✅	✅	✅	❌	❌	✅	4
A Sublinear Adversarial Training Algorithm	✅	❌	❌	❌	❌	❌	✅	2
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors	❌	✅	✅	❌	✅	❌	✅	4
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance	✅	✅	✅	✅	❌	❌	✅	5
A Unified Framework for Bayesian Optimization under Contextual Uncertainty	✅	✅	✅	❌	❌	✅	✅	5
A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models	✅	✅	✅	❌	✅	❌	✅	5
A Unified and General Framework for Continual Learning	✅	❌	✅	✅	❌	❌	✅	4
A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error	❌	❌	✅	✅	✅	❌	✅	4
A Variational Perspective on Solving Inverse Problems with Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables	✅	❌	✅	❌	✅	❌	✅	4
A differentiable brain simulator bridging brain simulation and brain-inspired computing	✅	✅	✅	❌	✅	✅	✅	6
A path-norm toolkit for modern networks: consequences, promises and challenges	✅	✅	✅	✅	❌	❌	✅	5
A representation-learning game for classes of prediction tasks	✅	✅	❌	❌	✅	❌	✅	4
A unique M-pattern for micro-expression spotting in long videos	✅	❌	✅	❌	❌	✅	✅	4
ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression	❌	❌	✅	❌	✅	❌	✅	3
ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process	✅	✅	✅	✅	❌	❌	✅	5
ADOPD: A Large-Scale Document Page Decomposition Dataset	✅	❌	✅	✅	✅	❌	✅	5
AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation	❌	❌	✅	✅	✅	❌	✅	4
ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models	✅	✅	✅	✅	✅	❌	✅	6
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents	✅	✅	✅	❌	✅	❌	✅	5
ARGS: Alignment as Reward-Guided Search	✅	✅	✅	❌	✅	✅	✅	6
ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning	❌	❌	✅	✅	✅	❌	✅	4
ASID: Active Exploration for System Identification in Robotic Manipulation	❌	✅	❌	❌	❌	❌	❌	1
ASMR: Activation-Sharing Multi-Resolution Coordinate Networks for Efficient Inference	❌	❌	✅	❌	✅	❌	✅	3
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images	❌	❌	✅	✅	✅	❌	✅	4
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers	✅	✅	✅	✅	❌	❌	✅	5
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise	✅	❌	✅	✅	❌	❌	✅	4
Accelerated Sampling with Stacked Restricted Boltzmann Machines	❌	❌	✅	❌	❌	❌	✅	2
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling	✅	✅	✅	❌	✅	✅	✅	6
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks	❌	❌	✅	❌	❌	❌	✅	2
Accelerating Sinkhorn algorithm with sparse Newton iterations	✅	❌	✅	❌	✅	❌	✅	4
Accurate Forgetting for Heterogeneous Federated Continual Learning	✅	✅	✅	❌	✅	❌	✅	5
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models	✅	✅	✅	❌	✅	❌	✅	5
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Achieving Human Parity in Content-Grounded Datasets Generation	✅	❌	✅	❌	❌	✅	❌	3
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping	✅	❌	❌	❌	❌	❌	✅	2
Active Retrosynthetic Planning Aware of Route Quality	✅	❌	✅	✅	❌	❌	✅	4
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm	✅	✅	✅	❌	✅	❌	✅	5
AdaMerging: Adaptive Model Merging for Multi-Task Learning	❌	✅	✅	✅	✅	❌	✅	5
Adapting Large Language Models via Reading Comprehension	❌	✅	✅	❌	✅	❌	✅	4
Adapting to Distribution Shift by Visual Domain Prompt Generation	✅	❌	✅	✅	❌	❌	✅	4
Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts	❌	✅	✅	❌	❌	✅	✅	4
Adaptive Federated Learning with Auto-Tuned Clients	✅	✅	✅	❌	❌	❌	✅	4
Adaptive Instrument Design for Indirect Experiments	✅	❌	✅	❌	❌	❌	✅	3
Adaptive Rational Activations to Boost Deep Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Adaptive Regret for Bandits Made Possible: Two Queries Suffice	✅	❌	✅	❌	❌	❌	✅	3
Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation	✅	✅	✅	❌	✅	❌	✅	5
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders	✅	❌	✅	✅	✅	❌	✅	5
Adaptive Self-training Framework for Fine-grained Scene Graph Generation	✅	✅	✅	✅	✅	❌	✅	6
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks	✅	❌	✅	✅	✅	❌	✅	5
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning	✅	❌	✅	❌	✅	❌	✅	4
Adaptive Window Pruning for Efficient Local Motion Deblurring	❌	✅	✅	❌	✅	❌	✅	4
Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism	✅	❌	✅	✅	✅	❌	✅	5
Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning	✅	✅	✅	❌	❌	❌	✅	4
Addressing Signal Delay in Deep Reinforcement Learning	❌	❌	✅	❌	❌	❌	✅	2
AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models	✅	✅	✅	❌	✅	❌	✅	5
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models	❌	✅	✅	✅	✅	✅	✅	6
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness	✅	✅	✅	❌	❌	✅	✅	5
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs	✅	❌	❌	❌	✅	✅	✅	4
Adversarial Attacks on Fairness of Graph Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Adversarial AutoMixup	✅	✅	✅	✅	❌	❌	✅	5
Adversarial Causal Bayesian Optimization	✅	✅	✅	❌	❌	❌	❌	3
Adversarial Feature Map Pruning for Backdoor	✅	✅	✅	✅	❌	❌	✅	5
Adversarial Imitation Learning via Boosting	✅	❌	✅	❌	❌	❌	✅	3
Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive	❌	❌	✅	✅	✅	❌	✅	4
Adversarial Training Should Be Cast as a Non-Zero-Sum Game	✅	❌	✅	✅	❌	❌	✅	4
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization	✅	❌	✅	❌	✅	✅	✅	5
AffineQuant: Affine Transformation Quantization for Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
AgentBench: Evaluating LLMs as Agents	❌	✅	✅	✅	❌	❌	✅	4
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors	❌	✅	✅	❌	❌	✅	✅	4
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction	❌	✅	✅	✅	✅	✅	✅	6
Algorithms for Caching and MTS with reduced number of predictions	✅	✅	✅	❌	❌	❌	✅	4
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic	❌	✅	✅	✅	✅	❌	❌	4
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework	❌	✅	✅	❌	❌	❌	✅	3
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model	✅	❌	✅	❌	❌	❌	✅	3
Aligning Relational Learning with Lipschitz Fairness	✅	✅	✅	✅	❌	❌	✅	5
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps	✅	✅	✅	❌	✅	❌	❌	4
AlpaGasus: Training a Better Alpaca with Fewer Data	❌	✅	✅	❌	✅	❌	✅	4
Alt-Text with Context: Improving Accessibility for Images on Twitter	❌	❌	✅	✅	✅	❌	✅	4
Amortized Network Intervention to Steer the Excitatory Point Processes	✅	❌	✅	✅	✅	❌	✅	5
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification	✅	✅	✅	❌	✅	❌	✅	5
Amortizing intractable inference in large language models	❌	✅	✅	✅	❌	❌	✅	4
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression	❌	❌	❌	❌	❌	❌	❌	0
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment	✅	✅	✅	❌	✅	❌	✅	5
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization	❌	✅	✅	✅	❌	❌	✅	4
An Efficient Tester-Learner for Halfspaces	✅	❌	❌	❌	❌	❌	❌	1
An Emulator for Fine-tuning Large Language Models using Small Language Models	❌	✅	✅	❌	❌	❌	✅	3
An Extensible Framework for Open Heterogeneous Collaborative Perception	❌	✅	✅	✅	✅	❌	✅	5
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models	✅	✅	✅	❌	❌	❌	✅	4
An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks	✅	✅	✅	❌	❌	❌	✅	4
An Investigation of Representation and Allocation Harms in Contrastive Learning	❌	✅	✅	✅	❌	❌	✅	4
An LLM can Fool Itself: A Prompt-Based Adversarial Attack	❌	✅	✅	❌	✅	❌	✅	4
An Unforgeable Publicly Verifiable Watermark for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
An improved analysis of per-sample and per-update clipping in federated learning	✅	❌	✅	✅	❌	✅	✅	5
An interpretable error correction method for enhancing code-to-code translation	❌	✅	✅	❌	❌	❌	✅	3
An operator preconditioning perspective on training in physics-informed machine learning	❌	❌	❌	❌	❌	✅	✅	2
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity	❌	✅	❌	❌	❌	❌	✅	2
Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps	❌	✅	✅	✅	✅	❌	✅	5
Analyzing and Improving Optimal-Transport-based Adversarial Networks	✅	✅	✅	❌	❌	❌	✅	4
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models	✅	✅	✅	✅	✅	❌	✅	6
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning	❌	✅	✅	❌	✅	❌	✅	4
Annealing Self-Distillation Rectification Improves Adversarial Training	✅	✅	✅	✅	✅	❌	✅	6
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection	❌	❌	✅	❌	✅	✅	✅	4
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?	❌	✅	✅	✅	✅	❌	✅	5
AnyText: Multilingual Visual Text Generation and Editing	❌	✅	✅	✅	✅	❌	✅	5
Approximately Piecewise E(3) Equivariant Point Networks	✅	❌	✅	✅	✅	❌	✅	5
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization	❌	❌	✅	❌	❌	❌	✅	2
ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor	✅	✅	✅	✅	❌	❌	✅	5
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations	❌	✅	✅	✅	✅	❌	✅	5
Are Human-generated Demonstrations Necessary for In-context Learning?	❌	✅	✅	✅	❌	❌	✅	4
Are Models Biased on Text without Gender-related Language?	❌	✅	✅	❌	❌	✅	✅	4
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?	❌	❌	✅	❌	❌	❌	✅	2
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition	✅	❌	✅	❌	❌	❌	✅	3
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning	❌	❌	✅	✅	✅	❌	✅	4
At Which Training Stage Does Code Data Help LLMs Reasoning?	❌	✅	✅	❌	✅	✅	✅	5
AttEXplore: Attribution for Explanation with model parameters eXploration	❌	✅	✅	❌	✅	❌	✅	4
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models	❌	✅	✅	✅	✅	✅	✅	6
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Attention-based Iterative Decomposition for Tensor Product Representation	✅	✅	✅	✅	❌	❌	✅	5
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation	✅	✅	✅	✅	✅	❌	✅	6
Augmented Bayesian Policy Search	✅	✅	✅	❌	✅	✅	✅	6
Augmenting Transformers with Recursively Composed Multi-grained Representations	✅	✅	✅	✅	✅	❌	✅	6
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval	❌	✅	✅	❌	❌	❌	✅	3
AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference	✅	❌	❌	❌	✅	❌	❌	2
AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models	✅	✅	✅	❌	✅	✅	✅	6
AutoLoRa: An Automated Robust Fine-Tuning Framework	✅	✅	✅	✅	❌	❌	✅	5
AutoVP: An Automated Visual Prompting Framework and Benchmark	✅	✅	✅	✅	✅	❌	✅	6
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ	❌	✅	✅	❌	❌	❌	✅	3
Automatic Functional Differentiation in JAX	✅	✅	❌	❌	❌	❌	✅	3
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost	❌	✅	✅	✅	❌	❌	✅	4
BECLR: Batch Enhanced Contrastive Few-Shot Learning	✅	✅	✅	✅	✅	❌	✅	6
BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks	❌	✅	✅	✅	✅	❌	✅	5
BENO: Boundary-embedded Neural Operators for Elliptic PDEs	✅	✅	❌	✅	✅	❌	✅	5
BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation	✅	❌	✅	✅	✅	❌	✅	5
BRUSLEATTACK: A QUERY-EFFICIENT SCORE- BASED BLACK-BOX SPARSE ADVERSARIAL ATTACK	✅	✅	✅	✅	✅	❌	✅	6
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models	✅	✅	✅	✅	✅	✅	✅	7
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection	✅	✅	✅	✅	✅	❌	✅	6
Backdoor Contrastive Learning via Bi-level Trigger Optimization	✅	✅	✅	✅	❌	❌	✅	5
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers	❌	❌	✅	✅	✅	❌	✅	4
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency	❌	✅	✅	✅	✅	❌	✅	5
BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models	❌	✅	✅	✅	❌	❌	✅	4
BadEdit: Backdooring Large Language Models by Model Editing	✅	❌	✅	✅	✅	❌	✅	5
Balancing Act: Constraining Disparate Impact in Sparse Models	✅	✅	✅	✅	✅	✅	✅	7
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation	✅	❌	❌	❌	❌	❌	✅	2
Bandits with Replenishable Knapsacks: the Best of both Worlds	✅	❌	❌	❌	❌	❌	❌	1
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering	❌	❌	✅	✅	❌	❌	✅	3
Batch normalization is sufficient for universal function approximation in CNNs	❌	❌	✅	❌	✅	❌	✅	3
BatchPrompt: Accomplish more with less	✅	✅	✅	✅	❌	❌	✅	5
Batched Low-Rank Adaptation of Foundation Models	✅	❌	✅	❌	✅	✅	✅	5
BatteryML: An Open-source Platform for Machine Learning on Battery Degradation	❌	✅	✅	❌	❌	❌	✅	3
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information	❌	✅	✅	✅	❌	❌	✅	4
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference	✅	✅	✅	❌	❌	❌	✅	4
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction	✅	✅	✅	✅	✅	❌	✅	6
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures	❌	✅	✅	❌	❌	❌	✅	3
Bayesian Coreset Optimization for Personalized Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Bayesian Low-rank Adaptation for Large Language Models	✅	✅	✅	✅	❌	❌	✅	5
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation	❌	✅	✅	✅	✅	❌	✅	5
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data	✅	✅	✅	❌	✅	✅	✅	6
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference	✅	✅	✅	❌	✅	❌	✅	5
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks	❌	✅	✅	❌	✅	✅	✅	5
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design	✅	✅	✅	❌	✅	❌	✅	5
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games	❌	❌	❌	❌	❌	❌	✅	1
Behaviour Distillation	✅	✅	✅	❌	✅	❌	✅	5
Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations	✅	✅	✅	❌	✅	❌	✅	5
Bellman Optimal Stepsize Straightening of Flow-Matching Models	✅	✅	✅	❌	✅	❌	✅	5
Benchmarking Algorithms for Federated Domain Generalization	✅	✅	✅	✅	❌	✅	✅	6
Benchmarking and Improving Generator-Validator Consistency of Language Models	❌	✅	✅	❌	✅	❌	✅	4
Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate	❌	❌	✅	❌	❌	❌	✅	2
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data	❌	❌	❌	❌	❌	❌	✅	1
Bespoke Solvers for Generative Flow Models	✅	❌	✅	✅	❌	❌	✅	4
Better Neural PDE Solvers Through Data-Free Mesh Movers	❌	✅	❌	❌	✅	❌	✅	3
Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain	❌	✅	✅	✅	✅	✅	✅	6
Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes	❌	✅	✅	❌	❌	❌	✅	3
Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment	✅	✅	✅	❌	❌	❌	✅	4
Beyond Memorization: Violating Privacy via Inference with Large Language Models	❌	✅	❌	❌	❌	❌	✅	2
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints	✅	❌	✅	❌	❌	❌	✅	3
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs	❌	✅	✅	✅	✅	❌	✅	5
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods	✅	❌	❌	❌	❌	❌	✅	2
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders	❌	❌	✅	❌	❌	❌	✅	2
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness	❌	✅	✅	✅	✅	✅	✅	6
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies	✅	✅	✅	❌	✅	❌	✅	5
Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning	❌	✅	✅	✅	❌	❌	✅	4
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs	❌	✅	✅	✅	❌	✅	✅	5
Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values	❌	✅	✅	✅	✅	✅	✅	6
Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation	✅	❌	✅	✅	✅	❌	✅	5
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis	✅	✅	✅	✅	✅	✅	✅	7
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs	❌	✅	✅	✅	❌	❌	✅	4
Blending Imitation and Reinforcement Learning for Robust Policy Improvement	✅	✅	✅	❌	✅	❌	✅	5
Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World	✅	❌	✅	✅	❌	❌	✅	4
BooookScore: A systematic exploration of book-length summarization in the era of LLMs	❌	✅	✅	✅	❌	❌	✅	4
Boosting Graph Anomaly Detection with Adaptive Message Passing	❌	✅	✅	❌	✅	✅	✅	5
Boosting Vanilla Lightweight Vision Transformers via Re-parameterization	❌	❌	✅	✅	✅	❌	✅	4
Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models	✅	✅	✅	❌	❌	❌	✅	4
Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective	✅	✅	✅	✅	✅	✅	✅	7
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification	❌	✅	✅	✅	✅	❌	✅	5
Boundary Denoising for Video Activity Localization	❌	✅	✅	✅	❌	✅	✅	5
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments	❌	✅	✅	✅	✅	✅	✅	6
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks	✅	✅	✅	✅	✅	❌	✅	6
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation	❌	✅	✅	✅	❌	❌	✅	4
Brain decoding: toward real-time reconstruction of visual perception	❌	❌	✅	✅	✅	❌	✅	4
BrainLM: A foundation model for brain activity recordings	❌	❌	✅	❌	❌	❌	✅	2
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity	❌	✅	✅	✅	✅	❌	✅	5
Branch-GAN: Improving Text Generation with (not so) Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages	✅	✅	✅	✅	✅	❌	✅	6
Bridging Neural and Symbolic Representations with Transitional Dictionary Learning	✅	✅	✅	✅	✅	❌	✅	6
Bridging State and History Representations: Understanding Self-Predictive RL	✅	✅	✅	❌	❌	❌	✅	4
Bridging Vision and Language Spaces with Assignment Prediction	❌	✅	✅	❌	❌	❌	✅	3
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics	❌	✅	✅	✅	✅	✅	✅	6
Building Cooperative Embodied Agents Modularly with Large Language Models	❌	❌	✅	❌	❌	❌	✅	2
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression	❌	❌	✅	✅	✅	❌	✅	4
Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game	✅	✅	✅	❌	❌	❌	✅	4
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion	❌	✅	✅	❌	✅	❌	✅	4
CABINET: Content Relevance-based Noise Reduction for Table Question Answering	❌	✅	✅	✅	✅	❌	✅	5
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling	✅	❌	✅	✅	❌	❌	✅	4
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception	❌	❌	✅	✅	✅	❌	✅	4
CAMBranch: Contrastive Learning with Augmented MILPs for Branching	❌	❌	✅	❌	✅	✅	✅	4
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images	❌	✅	✅	✅	✅	❌	❌	4
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting	✅	✅	✅	❌	✅	❌	✅	5
CAS: A Probability-Based Approach for Universal Condition Alignment Score	❌	❌	✅	❌	❌	❌	✅	2
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning	✅	❌	✅	❌	❌	❌	✅	3
CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis	❌	✅	✅	✅	✅	✅	✅	6
CLAP: Collaborative Adaptation for Patchwork Learning	✅	✅	✅	❌	✅	❌	✅	5
CLEX: Continuous Length Extrapolation for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?	✅	❌	✅	❌	✅	❌	✅	4
CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding	❌	✅	✅	✅	✅	❌	✅	5
CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction	❌	✅	✅	✅	✅	❌	✅	5
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech	❌	❌	✅	❌	✅	❌	✅	3
CNN Kernels Can Be the Best Shapelets	❌	❌	✅	✅	✅	❌	✅	4
CO2: Efficient Distributed Training with Full Communication-Computation Overlap	✅	✅	✅	✅	✅	✅	✅	7
COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery	✅	✅	✅	✅	❌	❌	✅	5
CODE REPRESENTATION LEARNING AT SCALE	❌	✅	✅	✅	❌	❌	✅	4
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits	❌	✅	✅	✅	✅	❌	✅	5
COLLIE: Systematic Construction of Constrained Text Generation Tasks	✅	✅	✅	❌	❌	❌	✅	4
COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL	✅	✅	✅	❌	✅	❌	✅	5
CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects	✅	✅	✅	❌	❌	❌	✅	4
COSA: Concatenated Sample Pretrained Vision-Language Foundation Model	❌	✅	✅	✅	✅	❌	✅	5
CPPO: Continual Learning for Reinforcement Learning with Human Feedback	✅	❌	✅	✅	✅	❌	✅	5
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets	❌	✅	✅	❌	❌	❌	✅	3
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing	✅	✅	✅	✅	❌	❌	✅	5
Cameras as Rays: Pose Estimation via Ray Diffusion	❌	✅	✅	❌	✅	❌	✅	4
Can LLM-Generated Misinformation Be Detected?	❌	❌	✅	❌	❌	✅	✅	3
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs	❌	✅	✅	❌	❌	❌	✅	3
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory	❌	❌	❌	❌	❌	❌	✅	1
Can Large Language Models Infer Causation from Correlation?	❌	✅	✅	✅	✅	❌	✅	5
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks	❌	✅	✅	✅	❌	❌	✅	4
Can Transformers Capture Spatial Relations between Objects?	❌	✅	✅	✅	❌	❌	✅	4
Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?	❌	✅	✅	❌	❌	❌	✅	3
Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?	❌	✅	✅	❌	✅	❌	✅	4
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning	✅	❌	✅	❌	❌	❌	✅	3
Cascading Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation	✅	✅	✅	✅	✅	❌	✅	6
Cauchy-Schwarz Divergence Information Bottleneck for Regression	❌	✅	✅	✅	✅	❌	✅	5
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework	✅	✅	✅	✅	❌	❌	✅	5
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder	✅	✅	✅	❌	❌	❌	✅	4
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning	✅	✅	✅	❌	✅	❌	✅	5
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions	✅	❌	✅	❌	❌	❌	❌	2
Causal-StoNet: Causal Inference for High-Dimensional Complex Data	✅	✅	✅	✅	❌	❌	✅	5
CausalLM is not optimal for in-context learning	❌	❌	✅	✅	❌	❌	✅	3
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery	✅	✅	✅	❌	✅	❌	✅	5
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Causally Aligned Curriculum Learning	✅	❌	✅	❌	❌	❌	✅	3
CellPLM: Pre-training of Cell Language Model Beyond Single Cells	❌	✅	✅	✅	✅	❌	✅	5
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Chain of Hindsight aligns Language Models with Feedback	✅	✅	✅	✅	✅	❌	✅	6
Chain of Log-Concave Markov Chains	✅	❌	❌	❌	❌	❌	✅	2
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems	✅	✅	❌	❌	❌	❌	✅	3
Chain-of-Experts: When LLMs Meet Complex Operations Research Problems	✅	✅	✅	✅	❌	❌	✅	5
Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources	❌	✅	✅	✅	✅	✅	✅	6
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding	✅	❌	✅	✅	❌	❌	✅	4
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning	✅	❌	✅	❌	✅	❌	✅	4
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words	❌	✅	✅	✅	✅	❌	✅	5
ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate	✅	❌	✅	❌	❌	❌	✅	3
Circuit Component Reuse Across Tasks in Transformer Language Models	❌	✅	✅	❌	❌	❌	✅	3
CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment	❌	✅	✅	❌	❌	✅	✅	4
Circumventing Concept Erasure Methods For Text-To-Image Generative Models	✅	✅	✅	❌	✅	❌	✅	5
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents	❌	✅	❌	❌	❌	❌	✅	2
Class Incremental Learning via Likelihood Ratio Based Task Prediction	✅	✅	✅	❌	✅	❌	✅	5
Class Probability Matching with Calibrated Networks for Label Shift Adaption	✅	✅	✅	✅	❌	❌	✅	5
Classification with Conceptual Safeguards	✅	✅	✅	❌	❌	❌	✅	4
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform	✅	✅	✅	❌	✅	❌	✅	5
Clifford Group Equivariant Simplicial Message Passing Networks	✅	✅	✅	✅	✅	❌	✅	6
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs	❌	✅	✅	✅	✅	❌	✅	5
Closing the Curious Case of Neural Text Degeneration	✅	✅	✅	✅	❌	✅	✅	6
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.	✅	✅	✅	❌	❌	❌	✅	4
CoBIT: A Contrastive Bi-directional Image-Text Generation Model	❌	❌	✅	✅	✅	❌	✅	4
CoLiDE: Concomitant Linear DAG Estimation	✅	✅	❌	❌	✅	❌	✅	4
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs	✅	✅	✅	✅	✅	❌	✅	6
CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding	✅	✅	✅	✅	✅	❌	✅	6
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding	✅	❌	✅	✅	❌	❌	✅	4
CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules	❌	✅	✅	✅	❌	✅	✅	5
Coeditor: Leveraging Repo-level Diffs for Code Auto-editing	❌	✅	✅	✅	✅	❌	✅	5
Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback	✅	✅	❌	❌	❌	❌	✅	3
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning	✅	❌	✅	✅	✅	❌	✅	5
Communication-Efficient Federated Non-Linear Bandit Optimization	✅	❌	✅	❌	❌	❌	✅	3
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates	✅	✅	✅	❌	❌	❌	✅	4
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models	✅	✅	✅	❌	❌	❌	✅	4
Complete and Efficient Graph Transformers for Crystal Material Property Prediction	❌	✅	✅	✅	✅	❌	✅	5
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities	❌	✅	✅	❌	❌	❌	✅	3
Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis	✅	✅	✅	✅	✅	❌	✅	6
Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization	❌	✅	✅	❌	❌	❌	✅	3
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Compositional Generative Inverse Design	✅	✅	❌	❌	✅	❌	✅	4
Compositional Preference Models for Aligning LMs	❌	✅	✅	✅	✅	✅	✅	6
Compressed Context Memory for Online Language Model Interaction	✅	✅	✅	❌	✅	❌	✅	5
Compressing LLMs: The Truth is Rarely Pure and Never Simple	❌	✅	✅	❌	❌	❌	✅	3
Compressing Latent Space via Least Volume	❌	✅	✅	❌	✅	❌	✅	4
ConR: Contrastive Regularizer for Deep Imbalanced Regression	✅	✅	✅	✅	✅	❌	✅	6
Concept Bottleneck Generative Models	❌	✅	✅	❌	✅	❌	❌	3
Conditional Information Bottleneck Approach for Time Series Imputation	✅	✅	✅	✅	✅	❌	✅	6
Conditional Instrumental Variable Regression with Representation Learning for Causal Inference	✅	✅	✅	✅	❌	❌	✅	5
Conditional Variational Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models	✅	❌	✅	❌	❌	❌	✅	3
Confidential-DPproof: Confidential Proof of Differentially Private Training	✅	✅	✅	❌	✅	❌	✅	5
Conformal Inductive Graph Neural Networks	✅	✅	✅	✅	❌	❌	✅	5
Conformal Language Modeling	✅	✅	✅	✅	✅	❌	✅	6
Conformal Prediction via Regression-as-Classification	✅	✅	✅	❌	❌	❌	✅	4
Conformal Risk Control	❌	✅	✅	✅	❌	❌	✅	4
Confronting Reward Model Overoptimization with Constrained RLHF	✅	✅	✅	✅	✅	❌	✅	6
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection	❌	✅	✅	❌	❌	❌	✅	3
Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data	✅	✅	✅	✅	❌	❌	✅	5
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers	✅	✅	✅	✅	❌	❌	✅	5
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training	✅	✅	✅	❌	❌	❌	✅	4
Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision	✅	✅	✅	✅	✅	✅	✅	7
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion	✅	✅	✅	✅	✅	❌	✅	6
Consistency-guided Prompt Learning for Vision-Language Models	❌	✅	✅	❌	✅	❌	✅	4
Consistent Multi-Class Classification from Multiple Unlabeled Datasets	✅	❌	✅	❌	✅	❌	✅	4
Consistent Video-to-Video Transfer Using Synthetic Dataset	❌	✅	✅	❌	✅	❌	✅	4
Consistent algorithms for multi-label classification with macro-at-$k$ metrics	✅	✅	✅	✅	✅	❌	✅	6
Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video	❌	❌	✅	❌	✅	❌	✅	3
Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm	✅	✅	✅	✅	✅	✅	✅	7
Constrained Decoding for Cross-lingual Label Projection	✅	✅	✅	✅	✅	❌	✅	6
Constraint-Free Structure Learning with Smooth Acyclic Orientations	❌	✅	✅	❌	✅	❌	✅	4
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit	✅	❌	✅	❌	✅	❌	✅	4
Context is Environment	❌	✅	✅	✅	✅	❌	✅	5
Context-Aware Meta-Learning	❌	✅	✅	❌	❌	❌	✅	3
ContextRef: Evaluating Referenceless Metrics for Image Description Generation	❌	✅	✅	❌	❌	❌	✅	3
Contextual Bandits with Online Neural Regression	✅	❌	✅	❌	❌	❌	✅	3
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline	✅	✅	✅	❌	✅	❌	✅	5
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation	✅	✅	✅	✅	✅	❌	✅	6
Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks	❌	✅	✅	❌	✅	❌	✅	4
Continuous Invariance Learning	✅	❌	✅	✅	✅	❌	✅	5
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach	✅	✅	✅	✅	✅	❌	✅	6
Contrastive Difference Predictive Coding	✅	✅	✅	❌	❌	❌	✅	4
Contrastive Learning is Spectral Clustering on Similarity Graph	✅	✅	✅	✅	✅	✅	✅	7
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
ControlVideo: Training-free Controllable Text-to-video Generation	✅	✅	✅	❌	✅	❌	✅	5
Controlled Text Generation via Language Model Arithmetic	✅	✅	✅	❌	✅	❌	✅	5
Controlling Vision-Language Models for Multi-Task Image Restoration	❌	✅	✅	❌	✅	❌	✅	4
Convergence of Bayesian Bilevel Optimization	✅	❌	✅	❌	❌	❌	✅	3
Conversational Drug Editing Using Retrieval and Domain Feedback	❌	✅	✅	❌	✅	❌	✅	4
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model	❌	✅	✅	✅	✅	❌	✅	5
Convolutional Deep Kernel Machines	❌	✅	✅	❌	✅	❌	✅	4
Coordinate-Aware Modulation for Neural Fields	❌	❌	✅	❌	❌	❌	✅	2
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion	✅	❌	✅	✅	❌	❌	✅	4
Copula Conformal prediction for multi-step time series prediction	✅	✅	✅	✅	✅	❌	✅	6
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning	✅	❌	✅	❌	❌	❌	✅	3
Counterfactual Density Estimation using Kernel Stein Discrepancies	✅	✅	✅	✅	❌	❌	✅	5
Counting Graph Substructures with Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Course Correcting Koopman Representations	❌	❌	✅	✅	❌	❌	✅	3
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping	❌	✅	✅	✅	✅	❌	✅	5
Critical Learning Periods Emerge Even in Deep Linear Networks	❌	✅	❌	❌	✅	❌	✅	3
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing	❌	✅	✅	✅	❌	❌	✅	4
CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity	✅	✅	✅	❌	✅	❌	✅	5
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding	❌	✅	✅	✅	✅	❌	✅	5
Curiosity-driven Red-teaming for Large Language Models	❌	✅	✅	❌	❌	✅	✅	4
Curriculum reinforcement learning for quantum architecture search under hardware errors	✅	✅	✅	❌	✅	✅	✅	6
Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning	❌	❌	✅	✅	✅	❌	✅	4
Cycle Consistency Driven Object Discovery	❌	❌	✅	✅	✅	❌	✅	4
DAFA: Distance-Aware Fair Adversarial Training	✅	✅	✅	❌	✅	✅	✅	6
DAM: Towards a Foundation Model for Forecasting	✅	✅	✅	✅	✅	❌	✅	6
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks	❌	✅	❌	✅	✅	❌	✅	4
DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations	❌	✅	✅	❌	✅	❌	✅	4
DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS	❌	❌	✅	✅	✅	❌	✅	4
DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING	✅	✅	✅	✅	✅	❌	✅	6
DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models	✅	✅	✅	✅	✅	✅	✅	7
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation	❌	✅	✅	✅	✅	❌	✅	5
DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations	✅	✅	✅	❌	✅	❌	✅	5
DMV3D: Denoising Multi-view Diffusion Using 3D Large Reconstruction Model	❌	❌	✅	❌	✅	❌	✅	3
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text	❌	✅	✅	❌	❌	❌	✅	3
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes	❌	✅	✅	✅	✅	❌	✅	5
DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$	❌	❌	✅	❌	✅	❌	✅	3
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection	✅	✅	✅	❌	✅	❌	✅	5
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer	✅	✅	✅	✅	❌	❌	✅	5
DP-SGD Without Clipping: The Lipschitz Neural Network Way	✅	✅	✅	✅	✅	✅	✅	7
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning	❌	✅	✅	❌	✅	❌	✅	4
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption	✅	❌	✅	❌	❌	❌	✅	3
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness	❌	✅	✅	✅	✅	❌	✅	5
DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines	✅	✅	✅	✅	✅	✅	✅	7
DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation	✅	✅	✅	❌	✅	❌	✅	5
Data Debugging with Shapley Importance over Machine Learning Pipelines	✅	✅	✅	✅	✅	❌	✅	6
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality	✅	✅	✅	❌	❌	❌	✅	4
Data Filtering Networks	✅	❌	✅	✅	✅	❌	✅	5
Data-independent Module-aware Pruning for Hierarchical Vision Transformers	❌	✅	✅	✅	❌	❌	✅	4
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation	✅	❌	✅	❌	❌	❌	❌	2
De novo Protein Design Using Geometric Vector Field Networks	✅	✅	✅	✅	✅	❌	✅	6
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning	❌	✅	✅	✅	✅	❌	✅	5
Debiased Collaborative Filtering with Kernel-Based Causal Balancing	✅	✅	✅	❌	❌	❌	✅	4
Debiasing Algorithm through Model Adaptation	❌	✅	✅	❌	❌	❌	✅	3
Debiasing Attention Mechanism in Transformer without Demographics	✅	✅	✅	❌	✅	❌	✅	5
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold	✅	❌	✅	❌	✅	❌	✅	4
Deceptive Fairness Attacks on Graphs via Meta Learning	✅	✅	✅	✅	✅	✅	✅	7
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making	❌	✅	✅	❌	✅	❌	✅	4
Decodable and Sample Invariant Continuous Object Encoder	✅	❌	✅	❌	❌	❌	✅	3
Decoding Natural Images from EEG for Object Recognition	✅	✅	✅	✅	✅	❌	✅	6
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization	✅	❌	✅	❌	✅	❌	✅	4
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems	✅	✅	✅	❌	✅	❌	✅	5
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces	❌	✅	✅	✅	✅	✅	✅	6
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations	❌	❌	✅	❌	✅	❌	✅	3
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks	✅	✅	✅	✅	✅	❌	✅	6
Decoupling regularization from the action space	✅	✅	✅	❌	❌	❌	✅	4
Deep Confident Steps to New Pockets: Strategies for Docking Generalization	❌	✅	✅	✅	✅	❌	✅	5
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders	✅	✅	✅	✅	❌	❌	✅	5
Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data	❌	❌	✅	✅	✅	✅	✅	5
Deep Neural Networks Tend To Extrapolate Predictably	❌	✅	✅	❌	❌	❌	✅	3
Deep Orthogonal Hypersphere Compression for Anomaly Detection	✅	✅	✅	✅	❌	✅	✅	6
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling	✅	✅	✅	✅	✅	❌	✅	6
Deep Reinforcement Learning for Modelling Protein Complexes	✅	❌	✅	✅	✅	❌	✅	5
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks	✅	✅	✅	❌	❌	❌	✅	4
Deep Temporal Graph Clustering	❌	✅	✅	❌	✅	❌	✅	4
DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation	❌	❌	✅	❌	✅	❌	✅	3
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training	✅	✅	✅	❌	✅	❌	✅	5
Defining Expertise: Applications to Treatment Effect Estimation	❌	✅	✅	✅	✅	❌	✅	5
Defining and extracting generalizable interaction primitives from DNNs	❌	✅	✅	❌	❌	❌	✅	3
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding	✅	✅	✅	✅	✅	❌	✅	6
Delta-AI: Local objectives for amortized inference in sparse graphical models	✅	✅	✅	❌	❌	❌	✅	4
Democratizing Fine-grained Visual Recognition with Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Demonstration-Regularized RL	✅	❌	❌	❌	❌	❌	❌	1
Demystifying CLIP Data	✅	✅	✅	❌	✅	❌	✅	5
Demystifying Embedding Spaces using Large Language Models	❌	❌	✅	❌	❌	❌	✅	2
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework	✅	❌	❌	❌	❌	❌	❌	1
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition	❌	✅	✅	❌	❌	❌	✅	3
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective	❌	✅	✅	✅	❌	❌	✅	4
Denoising Diffusion Bridge Models	✅	❌	✅	❌	❌	❌	✅	3
Denoising Diffusion Step-aware Models	✅	✅	✅	❌	✅	❌	✅	5
Denoising Diffusion via Image-Based Rendering	❌	✅	✅	✅	❌	❌	✅	4
Denoising Task Routing for Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit	❌	❌	✅	❌	❌	❌	✅	2
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess	❌	✅	❌	✅	✅	✅	✅	5
Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization	✅	❌	✅	❌	❌	❌	✅	3
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy	✅	✅	✅	❌	✅	✅	✅	6
Detecting Pretraining Data from Large Language Models	✅	❌	✅	✅	❌	❌	✅	4
Detecting, Explaining, and Mitigating Memorization in Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models	❌	✅	✅	❌	❌	✅	✅	4
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making	❌	✅	✅	✅	✅	❌	✅	5
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking	❌	✅	❌	❌	❌	❌	✅	2
Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks	❌	❌	✅	❌	❌	❌	✅	2
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation	❌	✅	✅	✅	✅	❌	✅	5
DiffEnc: Variational Diffusion with a Learned Encoder	❌	✅	✅	❌	❌	❌	✅	3
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction	✅	❌	✅	✅	✅	❌	✅	5
Differentiable Euler Characteristic Transforms for Shape Classification	❌	✅	✅	✅	✅	❌	✅	5
Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach	✅	❌	✅	❌	✅	❌	✅	4
Differentially Private Synthetic Data via Foundation Model APIs 1: Images	✅	✅	✅	❌	✅	❌	✅	5
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization	✅	✅	✅	❌	❌	❌	✅	4
Diffusion Model for Dense Matching	❌	✅	✅	❌	✅	❌	✅	4
Diffusion Models for Multi-Task Generative Modeling	✅	❌	✅	✅	✅	❌	✅	5
Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective	✅	❌	✅	✅	✅	❌	✅	5
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts	✅	❌	✅	❌	✅	❌	✅	4
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation	✅	❌	✅	❌	✅	❌	✅	4
Diffusion-TS: Interpretable Diffusion for General Time Series Generation	✅	✅	✅	❌	✅	❌	✅	5
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
DiffusionSat: A Generative Foundation Model for Satellite Imagery	❌	✅	✅	✅	✅	❌	✅	5
Directly Fine-Tuning Diffusion Models on Differentiable Rewards	✅	❌	✅	✅	✅	❌	✅	5
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning	✅	✅	✅	❌	❌	❌	✅	4
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search	✅	✅	✅	❌	✅	❌	✅	5
Discovering Temporally-Aware Reinforcement Learning Algorithms	❌	✅	✅	❌	✅	❌	✅	4
Discovering modular solutions that generalize compositionally	✅	✅	❌	❌	✅	✅	✅	5
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation	❌	✅	✅	❌	✅	❌	✅	4
Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference	✅	✅	✅	❌	✅	❌	✅	5
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI	❌	✅	✅	❌	✅	❌	✅	4
Dissecting learning and forgetting in language model finetuning	❌	✅	✅	✅	✅	❌	✅	5
DistillSpec: Improving Speculative Decoding via Knowledge Distillation	✅	❌	✅	❌	✅	❌	✅	4
Distinguished In Uniform: Self-Attention Vs. Virtual Nodes	❌	✅	✅	✅	❌	❌	✅	4
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF	❌	✅	✅	❌	❌	❌	✅	3
Distributionally Robust Optimization with Bias and Variance Reduction	✅	✅	✅	✅	✅	❌	✅	6
DittoGym: Learning to Control Soft Shape-Shifting Robots	❌	✅	✅	❌	✅	❌	✅	4
Diverse Projection Ensembles for Distributional Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Divide and not forget: Ensemble of selectively trained experts in Continual Learning	❌	✅	✅	✅	✅	❌	✅	5
Diving Segmentation Model into Pixels	❌	❌	✅	✅	✅	❌	✅	4
Do Generated Data Always Help Contrastive Learning?	❌	✅	✅	❌	✅	❌	✅	4
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Does CLIP’s generalization performance mainly stem from high train-test similarity?	❌	✅	✅	❌	✅	❌	✅	4
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?	❌	✅	✅	❌	❌	❌	✅	3
Does Writing with Language Models Reduce Content Diversity?	❌	✅	✅	❌	❌	❌	✅	3
Domain Randomization via Entropy Maximization	✅	✅	✅	❌	❌	❌	✅	4
Domain constraints improve risk prediction when outcome data is missing	❌	✅	✅	❌	❌	❌	❌	2
Domain-Agnostic Molecular Generation with Chemical Feedback	❌	✅	✅	✅	✅	❌	✅	5
Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts	✅	✅	✅	✅	✅	✅	✅	7
Don't Judge by the Look: Towards Motion Coherent Video Representation	❌	✅	✅	✅	✅	❌	✅	5
Don't Play Favorites: Minority Guidance for Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization	❌	✅	✅	❌	❌	❌	✅	3
Doubly Robust Instance-Reweighted Adversarial Training	✅	✅	✅	✅	✅	✅	✅	7
Doubly Robust Proximal Causal Learning for Continuous Treatments	❌	✅	✅	❌	❌	❌	✅	3
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization	✅	❌	✅	❌	✅	❌	✅	4
DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks	✅	❌	✅	❌	❌	❌	✅	3
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
DreamClean: Restoring Clean Image Using Deep Diffusion Prior	✅	❌	✅	✅	❌	❌	✅	4
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior	✅	✅	❌	❌	✅	❌	✅	4
DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow	✅	❌	✅	❌	✅	❌	✅	4
DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation	❌	❌	✅	❌	✅	❌	✅	3
DreamLLM: Synergistic Multimodal Comprehension and Creation	❌	✅	✅	✅	✅	❌	✅	5
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing	✅	❌	✅	❌	✅	❌	✅	4
DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation	✅	✅	✅	❌	✅	❌	✅	5
Dropout Enhanced Bilevel Training	✅	❌	✅	✅	✅	❌	✅	5
Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation	❌	✅	✅	❌	❌	❌	✅	3
Dual Associated Encoder for Face Restoration	❌	✅	✅	✅	✅	❌	✅	5
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning	✅	✅	✅	❌	✅	❌	✅	5
Dual-Encoders for Extreme Multi-label Classification	✅	❌	✅	✅	✅	❌	✅	5
Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment	✅	❌	❌	❌	✅	❌	✅	3
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos	❌	❌	✅	✅	❌	❌	✅	3
DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks	❌	✅	✅	❌	✅	❌	✅	4
DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization	✅	❌	✅	❌	✅	❌	✅	4
Dynamic Discounted Counterfactual Regret Minimization	✅	✅	✅	❌	✅	❌	✅	5
Dynamic Layer Tying for Parameter-Efficient Transformers	✅	❌	✅	✅	✅	❌	✅	5
Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces	✅	✅	✅	❌	✅	❌	✅	5
Dynamic Neural Response Tuning	❌	✅	✅	✅	✅	❌	✅	5
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs	✅	✅	✅	✅	✅	❌	✅	6
Dynamic Sparse Training with Structured Sparsity	✅	✅	✅	❌	✅	❌	✅	5
Dynamics-Informed Protein Design with Structure Conditioning	❌	✅	✅	✅	✅	❌	✅	5
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model	❌	✅	✅	✅	✅	❌	✅	5
ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models	✅	✅	✅	✅	✅	❌	✅	6
EControl: Fast Distributed Optimization with Compression and Error Control	✅	✅	✅	❌	❌	❌	✅	4
ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF	❌	✅	✅	❌	✅	❌	✅	4
EMO: EARTH MOVER DISTANCE OPTIMIZATION FOR AUTO-REGRESSIVE LANGUAGE MODELING	❌	✅	✅	✅	❌	❌	✅	4
EQA-MX: Embodied Question Answering using Multimodal Expression	❌	✅	✅	✅	✅	✅	✅	6
EX-Graph: A Pioneering Dataset Bridging Ethereum and X	❌	✅	✅	✅	✅	✅	✅	6
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization	❌	❌	✅	❌	❌	❌	✅	2
Early Stopping Against Label Noise Without Validation Data	✅	❌	✅	✅	❌	✅	✅	5
EasyTPP: Towards Open Benchmarking Temporal Point Processes	✅	✅	✅	✅	✅	❌	✅	6
Effective Data Augmentation With Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
Effective Structural Encodings via Local Curvature Profiles	❌	✅	✅	✅	✅	❌	✅	5
Effective and Efficient Federated Tree Learning on Hybrid Data	✅	❌	✅	❌	✅	❌	✅	4
Effective pruning of web-scale datasets based on complexity of concept clusters	✅	✅	✅	✅	❌	✅	✅	6
Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios	❌	❌	✅	❌	✅	❌	✅	3
Efficient Backpropagation with Variance Controlled Adaptive Sampling	✅	✅	✅	✅	✅	❌	✅	6
Efficient Continual Finite-Sum Minimization	✅	✅	✅	❌	❌	❌	✅	4
Efficient ConvBN Blocks for Transfer Learning and Beyond	✅	✅	✅	❌	✅	✅	✅	6
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory	✅	✅	✅	❌	✅	❌	✅	5
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation	❌	❌	✅	✅	❌	❌	✅	3
Efficient Integrators for Diffusion Generative Models	✅	✅	✅	❌	✅	✅	✅	6
Efficient Inverse Multiagent Learning	✅	✅	✅	✅	❌	❌	❌	4
Efficient Modulation for Vision Networks	❌	✅	✅	✅	✅	❌	✅	5
Efficient Multi-agent Reinforcement Learning by Planning	❌	✅	✅	❌	❌	❌	✅	3
Efficient Planning with Latent Diffusion	✅	✅	✅	❌	✅	❌	✅	5
Efficient Score Matching with Deep Equilibrium Layers	✅	✅	✅	✅	❌	❌	✅	5
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models	✅	✅	✅	✅	✅	❌	✅	6
Efficient Streaming Language Models with Attention Sinks	❌	✅	✅	❌	✅	❌	✅	4
Efficient Subgraph GNNs by Learning Effective Selection Policies	✅	✅	✅	✅	✅	❌	✅	6
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition	✅	❌	✅	✅	✅	❌	✅	5
Efficient and Scalable Graph Generation through Iterative Local Expansion	✅	✅	✅	✅	✅	❌	✅	6
Efficient local linearity regularization to overcome catastrophic overfitting	✅	✅	✅	✅	✅	❌	✅	6
Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day	❌	❌	✅	✅	✅	✅	✅	5
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Efficiently Computing Similarities to Private Datasets	✅	❌	✅	❌	✅	❌	✅	4
Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning	✅	✅	✅	❌	❌	❌	✅	4
Elucidating the Exposure Bias in Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Elucidating the design space of classifier-guided diffusion generation	✅	✅	✅	❌	✅	❌	❌	4
Embarrassingly Simple Dataset Distillation	✅	✅	✅	✅	✅	❌	✅	6
Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches	✅	❌	✅	❌	✅	✅	✅	5
EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models	❌	❌	✅	❌	❌	❌	✅	2
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision	❌	✅	✅	❌	✅	❌	✅	4
Emergent Communication with Conversational Repair	❌	✅	✅	✅	❌	❌	✅	4
Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks	❌	✅	❌	❌	✅	❌	✅	3
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation	❌	✅	✅	✅	❌	❌	✅	4
Empirical Likelihood for Fair Classification	❌	❌	✅	❌	❌	❌	✅	2
Emu: Generative Pretraining in Multimodality	❌	✅	✅	✅	✅	❌	✅	5
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products	❌	✅	✅	✅	✅	❌	✅	5
Enabling Lanuguage Models to Implicitly Learn Self-Improvement	✅	❌	✅	✅	✅	❌	✅	5
Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning	✅	✅	✅	❌	✅	✅	✅	6
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon	❌	❌	✅	✅	✅	❌	✅	4
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations	✅	✅	✅	✅	✅	❌	✅	6
Energy-based Automated Model Evaluation	✅	✅	✅	✅	❌	❌	❌	4
Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials	❌	✅	✅	✅	✅	❌	✅	5
Energy-guided Entropic Neural Optimal Transport	✅	✅	✅	❌	✅	❌	✅	5
Enhanced Face Recognition using Intra-class Incoherence Constraint	❌	❌	✅	❌	❌	❌	✅	2
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation	❌	❌	✅	✅	✅	❌	✅	4
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests	✅	✅	✅	❌	❌	❌	✅	4
Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping	❌	✅	✅	❌	✅	❌	✅	4
Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain	✅	✅	❌	❌	✅	❌	✅	4
Enhancing Human-AI Collaboration Through Logic-Guided Reasoning	✅	❌	✅	❌	❌	❌	❌	2
Enhancing Instance-Level Image Classification with Set-Level Labels	✅	❌	✅	❌	❌	❌	✅	3
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations	❌	❌	✅	✅	✅	❌	✅	4
Enhancing Neural Training via a Correlated Dynamics Model	✅	✅	✅	✅	❌	❌	✅	5
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting	✅	✅	✅	✅	❌	❌	✅	5
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting	❌	✅	✅	✅	✅	❌	✅	5
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction	❌	✅	✅	✅	✅	❌	✅	5
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling	✅	❌	✅	✅	✅	❌	✅	5
Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation	✅	✅	✅	❌	❌	❌	✅	4
Ensemble Distillation for Unsupervised Constituency Parsing	✅	✅	✅	✅	✅	❌	❌	5
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels	❌	✅	❌	❌	❌	❌	✅	2
Entropy Coding of Unordered Data Structures	✅	✅	✅	❌	✅	❌	❌	4
Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors	✅	❌	✅	✅	✅	❌	✅	5
Entropy-MCMC: Sampling from Flat Basins with Ease	✅	✅	✅	❌	❌	❌	✅	4
Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning	✅	✅	✅	❌	❌	❌	✅	4
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations	❌	✅	✅	✅	✅	❌	✅	5
Equivariant Matrix Function Neural Networks	❌	❌	✅	✅	✅	❌	✅	4
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms	✅	✅	✅	✅	✅	❌	✅	6
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants	✅	❌	✅	✅	✅	❌	✅	5
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models	✅	❌	✅	❌	❌	❌	✅	3
Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning	✅	✅	✅	❌	❌	❌	✅	4
Estimating Conditional Mutual Information for Dynamic Feature Selection	✅	✅	✅	✅	✅	❌	✅	6
Estimating Shape Distances on Neural Representations with Limited Samples	❌	✅	✅	❌	❌	❌	❌	2
Eureka: Human-Level Reward Design via Coding Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
Evaluating Language Model Agency Through Negotiations	❌	✅	✅	❌	❌	❌	✅	3
Evaluating Large Language Models at Evaluating Instruction Following	❌	✅	✅	❌	❌	❌	✅	3
Evaluating Representation Learning on the Protein Structure Universe	❌	✅	✅	✅	✅	❌	✅	5
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models	❌	✅	✅	❌	✅	❌	✅	4
EventRPG: Event Data Augmentation with Relevance Propagation Guidance	❌	✅	✅	❌	❌	❌	✅	3
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing	✅	❌	✅	❌	❌	❌	✅	3
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis	✅	✅	✅	✅	✅	❌	✅	6
Expected flow networks in stochastic environments and two-player zero-sum games	✅	✅	✅	❌	✅	❌	✅	5
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection	✅	✅	✅	✅	✅	❌	✅	6
Explaining Kernel Clustering via Decision Trees	✅	✅	✅	❌	❌	❌	✅	4
Explaining Time Series via Contrastive and Locally Sparse Perturbations	✅	✅	✅	❌	❌	❌	✅	4
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Exploring Diffusion Time-steps for Unsupervised Representation Learning	❌	✅	✅	❌	✅	❌	✅	4
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses	❌	❌	✅	✅	✅	❌	✅	4
Exploring Target Representations for Masked Autoencoders	❌	✅	✅	✅	✅	❌	✅	5
Exploring Weight Balancing on Long-Tailed Recognition Problem	❌	✅	✅	✅	✅	❌	✅	5
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow	❌	❌	✅	❌	❌	❌	❌	1
Exploring the Promise and Limits of Real-Time Recurrent Learning	❌	✅	✅	❌	✅	❌	✅	4
Exploring the cloud of feature interaction scores in a Rashomon set	✅	✅	✅	✅	❌	❌	✅	5
Exposing Text-Image Inconsistency Using Diffusion Models	❌	✅	✅	❌	❌	❌	✅	3
Expressive Losses for Verified Robustness via Convex Combinations	✅	✅	✅	✅	✅	❌	✅	6
Expressivity of ReLU-Networks under Convex Relaxations	❌	❌	❌	❌	❌	❌	❌	0
Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World	❌	❌	❌	✅	✅	❌	✅	3
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods	✅	✅	✅	✅	❌	❌	✅	5
FITS: Modeling Time Series with $10k$ Parameters	❌	✅	✅	✅	❌	❌	✅	4
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets	❌	✅	✅	❌	❌	❌	✅	3
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing	❌	✅	✅	❌	✅	❌	✅	4
FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning	✅	✅	✅	❌	❌	✅	✅	5
FOSI: Hybrid First and Second Order Optimization	✅	✅	✅	❌	✅	✅	✅	6
FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition	❌	✅	✅	✅	✅	❌	✅	5
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?	❌	✅	✅	✅	✅	❌	✅	5
Fair Classifiers that Abstain without Harm	✅	✅	✅	✅	✅	❌	✅	6
Fair and Efficient Contribution Valuation for Vertical Federated Learning	❌	✅	✅	❌	✅	❌	✅	4
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling	❌	✅	✅	❌	❌	❌	✅	3
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis	✅	✅	✅	✅	❌	❌	✅	5
FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs	✅	❌	✅	✅	❌	❌	✅	4
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals	❌	✅	✅	✅	❌	❌	✅	4
Faithful Rule Extraction for Differentiable Rule Learning Models	✅	✅	✅	✅	✅	✅	✅	7
Faithful Vision-Language Interpretation via Concept Bottleneck Models	✅	❌	✅	❌	❌	❌	✅	3
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models	❌	✅	✅	❌	✅	❌	✅	4
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation	✅	✅	✅	❌	❌	❌	✅	4
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model	❌	❌	✅	✅	✅	✅	✅	5
Fantastic Generalization Measures are Nowhere to be Found	❌	❌	❌	❌	❌	❌	❌	0
Fast Ensembling with Diffusion Schrödinger Bridge	✅	✅	✅	✅	✅	❌	✅	6
Fast Equilibrium of SGD in Generic Situations	❌	❌	✅	❌	❌	❌	✅	2
Fast Hyperboloid Decision Tree Algorithms	❌	✅	✅	✅	✅	✅	✅	6
Fast Imitation via Behavior Foundation Models	❌	❌	✅	❌	❌	❌	✅	2
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices	✅	✅	✅	❌	❌	❌	✅	4
Fast Value Tracking for Deep Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
Fast and unified path gradient estimators for normalizing flows	✅	✅	✅	❌	✅	❌	✅	5
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space	❌	✅	✅	❌	❌	❌	✅	3
Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature	✅	✅	✅	❌	✅	❌	✅	5
Fast-ELECTRA for Efficient Pre-training	❌	❌	✅	✅	✅	❌	✅	4
Faster Approximation of Probabilistic and Distributional Values via Least Squares	✅	✅	✅	✅	❌	❌	✅	5
Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers	✅	❌	❌	❌	❌	❌	❌	1
FasterViT: Fast Vision Transformers with Hierarchical Attention	❌	✅	✅	✅	✅	✅	✅	6
FeatUp: A Model-Agnostic Framework for Features at Any Resolution	❌	✅	✅	✅	❌	❌	✅	4
Feature Collapse	❌	✅	❌	❌	❌	❌	✅	2
Feature emergence via margin maximization: case studies in algebraic tasks	❌	❌	❌	❌	❌	❌	✅	1
Feature-aligned N-BEATS with Sinkhorn divergence	✅	✅	✅	✅	✅	❌	✅	6
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation	✅	❌	✅	❌	✅	✅	✅	5
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler	✅	✅	✅	✅	❌	❌	✅	5
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization	✅	❌	✅	❌	✅	❌	✅	4
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent	✅	✅	✅	❌	❌	❌	✅	4
FedImpro: Measuring and Improving Client Update in Federated Learning	✅	✅	✅	❌	✅	✅	✅	6
FedInverse: Evaluating Privacy Leakage in Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data	✅	✅	✅	❌	✅	❌	✅	5
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity	✅	❌	✅	❌	✅	✅	✅	5
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
FedWon: Triumphing Multi-domain Federated Learning Without Normalization	✅	❌	✅	❌	✅	❌	✅	4
Federated Causal Discovery from Heterogeneous Data	✅	✅	✅	❌	❌	❌	✅	4
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost	✅	✅	❌	❌	❌	❌	✅	3
Federated Recommendation with Additive Personalization	✅	✅	✅	✅	✅	❌	✅	6
Federated Text-driven Prompt Generation for Vision-Language Models	✅	❌	✅	✅	❌	❌	✅	4
Federated Wasserstein Distance	✅	✅	✅	✅	❌	❌	✅	5
Ferret: Refer and Ground Anything Anywhere at Any Granularity	❌	✅	✅	❌	✅	❌	✅	4
Few-Shot Detection of Machine-Generated Text using Style Representations	❌	✅	✅	✅	✅	❌	✅	5
Few-shot Hybrid Domain Adaptation of Image Generator	❌	❌	✅	❌	✅	❌	✅	3
Fiber Monte Carlo	❌	❌	✅	❌	✅	❌	✅	3
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text	✅	✅	✅	✅	✅	✅	✅	7
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking	❌	✅	✅	✅	❌	❌	✅	4
Fine-Tuning Language Models for Factuality	❌	✅	❌	✅	❌	❌	✅	3
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!	❌	✅	✅	❌	❌	❌	✅	3
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions	❌	✅	✅	❌	✅	❌	✅	4
Finetuning Text-to-Image Diffusion Models for Fairness	✅	✅	✅	✅	✅	❌	✅	6
Finite Scalar Quantization: VQ-VAE Made Simple	❌	✅	✅	✅	❌	❌	✅	4
Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression	✅	✅	✅	❌	✅	❌	✅	5
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
First-order ANIL provably learns representations despite overparametrisation	❌	❌	❌	✅	❌	❌	✅	2
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation	✅	✅	✅	✅	❌	❌	✅	5
Fixed-Budget Differentially Private Best Arm Identification	✅	❌	❌	❌	❌	❌	✅	2
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization	✅	✅	✅	❌	✅	❌	✅	5
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning	✅	❌	❌	❌	✅	❌	✅	3
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores	✅	❌	✅	✅	✅	❌	✅	5
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem	❌	❌	❌	✅	❌	❌	✅	2
Flow Matching on General Geometries	✅	✅	✅	✅	✅	❌	✅	6
Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation	✅	✅	✅	❌	✅	❌	✅	5
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification	❌	✅	✅	❌	❌	❌	✅	3
Forward $\chi^2$ Divergence Based Variational Importance Sampling	✅	✅	✅	❌	❌	❌	✅	4
Forward Learning of Graph Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization	✅	✅	✅	❌	✅	❌	✅	5
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models	✅	❌	✅	❌	✅	❌	✅	4
Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D	✅	❌	✅	❌	✅	❌	✅	4
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning	✅	✅	✅	❌	❌	❌	✅	4
FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction	✅	✅	✅	✅	✅	❌	✅	6
FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling	❌	✅	✅	❌	✅	❌	✅	4
FreeReg: Image-to-Point Cloud Registration Leveraging Pretrained Diffusion Models and Monocular Depth Estimators	❌	✅	✅	✅	✅	❌	✅	5
Frequency-Aware Transformer for Learned Image Compression	❌	✅	✅	❌	✅	❌	✅	4
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication	❌	✅	✅	❌	❌	❌	✅	3
From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction	✅	✅	✅	✅	✅	❌	✅	6
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module	❌	✅	✅	❌	✅	❌	✅	4
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction	✅	✅	✅	✅	✅	❌	✅	6
From Posterior Sampling to Meaningful Diversity in Image Restoration	✅	✅	✅	❌	❌	❌	✅	4
From Sparse to Soft Mixtures of Experts	✅	✅	✅	✅	✅	❌	✅	6
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation	❌	✅	✅	✅	✅	❌	✅	5
Frozen Transformers in Language Models Are Effective Visual Encoder Layers	✅	✅	✅	✅	✅	❌	✅	6
Fully Hyperbolic Convolutional Neural Networks for Computer Vision	❌	✅	✅	✅	✅	❌	✅	5
Function Vectors in Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Function-space Parameterization of Neural Networks for Sequential Learning	✅	✅	✅	✅	✅	❌	✅	6
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data	✅	✅	✅	✅	❌	❌	✅	5
Functional Interpolation for Relative Positions improves Long Context Transformers	✅	❌	✅	❌	✅	❌	✅	4
Fusing Models with Complementary Expertise	❌	✅	✅	✅	❌	❌	✅	4
Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection	❌	✅	✅	❌	✅	❌	✅	4
Future Language Modeling from Temporal Document History	❌	✅	✅	✅	✅	❌	✅	5
G$^2$N$^2$ : Weisfeiler and Lehman go grammatical	❌	❌	✅	✅	❌	❌	✅	3
GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings	❌	✅	✅	✅	❌	❌	✅	4
GAIA: Zero-shot Talking Avatar Generation	❌	❌	✅	✅	✅	❌	✅	4
GAIA: a benchmark for General AI Assistants	❌	❌	✅	✅	❌	❌	✅	3
GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules	❌	❌	✅	✅	❌	❌	✅	3
GIM: Learning Generalizable Image Matcher From Internet Videos	❌	✅	✅	❌	✅	❌	✅	4
GIO: Gradient Information Optimization for Training Dataset Selection	✅	✅	✅	✅	✅	❌	✅	6
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries	✅	✅	✅	❌	✅	✅	✅	6
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations	❌	✅	✅	✅	❌	❌	✅	4
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking	❌	✅	✅	✅	✅	❌	✅	5
GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors	❌	❌	❌	❌	✅	❌	✅	2
GOAt: Explaining Graph Neural Networks via Graph Output Attribution	❌	✅	✅	✅	✅	❌	✅	5
GPAvatar: Generalizable and Precise Head Avatar from Image(s)	❌	✅	✅	❌	✅	❌	✅	4
GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher	❌	✅	✅	❌	❌	❌	✅	3
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data	❌	✅	✅	✅	✅	❌	✅	5
GRAPH-CONSTRAINED DIFFUSION FOR END-TO-END PATH PLANNING	✅	✅	✅	❌	✅	❌	✅	5
GROOT: Learning to Follow Instructions by Watching Gameplay Videos	❌	❌	✅	❌	✅	❌	✅	3
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers	✅	✅	✅	✅	✅	❌	✅	6
GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation	❌	✅	✅	✅	❌	❌	✅	4
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis	❌	❌	✅	❌	✅	❌	✅	3
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations	✅	❌	✅	❌	✅	❌	✅	4
Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions	❌	✅	✅	❌	❌	❌	✅	3
GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models	❌	❌	✅	❌	❌	❌	✅	2
GenSim: Generating Robotic Simulation Tasks via Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View	❌	✅	✅	❌	✅	❌	✅	4
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion	✅	✅	✅	✅	❌	❌	✅	5
General Graph Random Features	✅	✅	✅	❌	❌	❌	✅	4
General Stability Analysis for Zeroth-Order Optimization Algorithms	❌	❌	✅	✅	❌	❌	✅	3
Generalization error of spectral algorithms	❌	❌	❌	❌	❌	❌	✅	1
Generalization in diffusion models arises from geometry-adaptive harmonic representations	✅	✅	✅	❌	❌	❌	✅	4
Generalization of Scaled Deep ResNets in the Mean-Field Regime	❌	❌	✅	❌	❌	❌	✅	2
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions	❌	❌	✅	❌	✅	❌	✅	3
Generalized Policy Iteration using Tensor Approximation for Hybrid Control	✅	✅	✅	❌	✅	❌	✅	5
Generalized Schrödinger Bridge Matching	✅	❌	✅	❌	❌	❌	✅	3
Generating Images with 3D Annotations Using Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
Generating Pragmatic Examples to Train Neural Program Synthesizers	✅	✅	✅	✅	❌	❌	✅	5
Generative Adversarial Equilibrium Solvers	✅	❌	❌	❌	❌	❌	❌	1
Generative Human Motion Stylization in Latent Space	❌	✅	✅	❌	✅	❌	✅	4
Generative Judge for Evaluating Alignment	❌	✅	✅	❌	✅	❌	✅	4
Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns	✅	✅	✅	❌	❌	❌	✅	4
Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping	❌	✅	✅	❌	❌	❌	✅	3
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs	❌	✅	✅	❌	✅	✅	✅	5
Generative Modeling with Phase Stochastic Bridge	✅	❌	✅	❌	✅	❌	✅	4
Generative Pre-training for Speech with Flow Matching	❌	❌	✅	❌	✅	❌	✅	3
Generative Sliced MMD Flows with Riesz Kernels	✅	✅	✅	✅	✅	❌	✅	6
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation	❌	❌	✅	✅	✅	✅	✅	5
GeoLLM: Extracting Geospatial Knowledge from Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks	❌	✅	✅	✅	❌	❌	✅	4
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks	✅	❌	✅	✅	✅	❌	✅	5
Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields	❌	❌	✅	❌	❌	❌	✅	2
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs	❌	✅	✅	✅	✅	✅	✅	6
Ghost on the Shell: An Expressive Representation of General 3D Shapes	✅	❌	✅	❌	✅	❌	✅	4
Global Optimality for Non-linear Constrained Restoration Problems via Invexity	❌	❌	✅	✅	❌	❌	✅	3
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks	❌	✅	✅	✅	✅	❌	✅	5
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction	❌	✅	✅	✅	✅	❌	✅	5
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory	✅	✅	✅	❌	✅	❌	✅	5
Goodhart's Law in Reinforcement Learning	✅	❌	❌	❌	✅	❌	✅	3
Gradual Domain Adaptation via Gradient Flow	✅	✅	✅	✅	✅	❌	✅	6
Gradual Optimization Learning for Conformational Energy Minimization	✅	✅	✅	❌	✅	✅	✅	6
Graph Generation with $K^2$-trees	✅	✅	✅	✅	✅	❌	✅	6
Graph Lottery Ticket Automated	✅	❌	✅	✅	❌	❌	✅	4
Graph Metanetworks for Processing Diverse Neural Architectures	❌	❌	✅	✅	❌	❌	✅	3
Graph Neural Networks for Learning Equivariant Representations of Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Graph Parsing Networks	✅	✅	✅	✅	✅	❌	✅	6
Graph Transformers on EHRs: Better Representation Improves Downstream Performance	❌	✅	✅	✅	✅	❌	✅	5
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations	❌	✅	✅	✅	✅	❌	✅	5
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs	✅	✅	✅	✅	✅	✅	✅	7
GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
GraphPulse: Topological representations for temporal graph property prediction	❌	✅	✅	✅	✅	❌	✅	5
Graphical Multioutput Gaussian Process with Attention	❌	✅	❌	❌	❌	❌	✅	2
Grokking as a First Order Phase Transition in Two Layer Networks	❌	❌	❌	✅	❌	❌	✅	2
Grokking as the transition from lazy to rich training dynamics	❌	❌	✅	❌	❌	❌	✅	2
Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding	❌	❌	❌	❌	❌	❌	✅	1
Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Grounded Object-Centric Learning	✅	✅	✅	✅	✅	❌	✅	6
Grounding Language Plans in Demonstrations Through Counterfactual Perturbations	❌	❌	✅	❌	❌	❌	❌	1
Grounding Multimodal Large Language Models to the World	❌	✅	✅	✅	✅	❌	✅	5
Group Preference Optimization: Few-Shot Alignment of Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators	❌	✅	✅	✅	✅	❌	✅	5
Guess & Sketch: Language Model Guided Transpilation	✅	❌	✅	❌	✅	❌	✅	4
Guiding Instruction-based Image Editing via Multimodal Large Language Models	✅	❌	✅	✅	✅	❌	✅	5
Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram	❌	✅	✅	✅	✅	✅	✅	6
H-GAP: Humanoid Control with a Generalist Planner	✅	✅	✅	❌	✅	❌	✅	5
H2O-SDF: Two-phase Learning for 3D Indoor Reconstruction using Object Surface Fields	❌	❌	✅	❌	✅	❌	✅	3
HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments	❌	✅	✅	❌	✅	❌	✅	4
HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance	✅	❌	❌	❌	❌	❌	✅	2
HYPO: Hyperspherical Out-Of-Distribution Generalization	✅	✅	✅	✅	✅	✅	✅	7
Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots	❌	✅	✅	✅	✅	❌	✅	5
Harnessing Density Ratios for Online Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning	❌	✅	✅	✅	✅	❌	✅	5
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains	✅	✅	✅	✅	✅	❌	✅	6
Headless Language Models: Learning without Predicting with Contrastive Weight Tying	✅	✅	✅	✅	✅	❌	✅	6
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate	✅	✅	✅	✅	✅	❌	✅	6
HiGen: Hierarchical Graph Generative Networks	✅	✅	✅	✅	✅	❌	✅	6
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning	✅	✅	✅	✅	✅	✅	✅	7
Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs	✅	✅	✅	✅	✅	❌	✅	6
High-dimensional SGD aligns with emerging outlier eigenspaces	❌	❌	❌	❌	❌	❌	✅	1
Hindsight PRIORs for Reward Learning from Human Preferences	❌	❌	✅	❌	❌	❌	✅	2
HoloNets: Spectral Convolutions do extend to Directed Graphs	✅	✅	✅	✅	✅	❌	✅	6
Horizon-Free Regret for Linear Markov Decision Processes	✅	❌	❌	❌	❌	❌	❌	1
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs	✅	❌	❌	❌	❌	❌	❌	1
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations	❌	✅	❌	✅	❌	❌	✅	3
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?	✅	✅	✅	❌	✅	✅	✅	6
How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models	✅	❌	✅	❌	✅	❌	❌	3
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?	❌	❌	❌	❌	❌	❌	✅	1
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization	❌	❌	❌	❌	❌	❌	✅	1
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data	❌	✅	✅	✅	❌	❌	✅	4
How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?	❌	✅	✅	✅	❌	❌	❌	3
How connectivity structure shapes rich and lazy learning in neural circuits	❌	❌	✅	❌	❌	❌	❌	1
How do Language Models Bind Entities in Context?	❌	✅	❌	❌	❌	❌	✅	2
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation	✅	❌	❌	❌	❌	❌	❌	1
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions	✅	✅	✅	❌	❌	❌	✅	4
How to Fine-Tune Vision Models with SGD	❌	❌	✅	✅	✅	❌	✅	4
Human Feedback is not Gold Standard	❌	✅	✅	❌	❌	❌	✅	3
Human Motion Diffusion as a Generative Prior	✅	✅	✅	❌	✅	❌	✅	5
Hybrid Directional Graph Neural Network for Molecules	❌	✅	✅	❌	❌	❌	✅	3
Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners	❌	✅	✅	❌	✅	❌	✅	4
Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response	❌	❌	❌	❌	✅	❌	✅	2
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing	❌	✅	✅	✅	✅	❌	✅	5
Hybrid Sharing for Multi-Label Image Classification	✅	❌	✅	✅	✅	❌	✅	5
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs	✅	✅	✅	✅	✅	❌	✅	6
Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty	✅	✅	✅	✅	❌	❌	✅	5
HyperAttention: Long-context Attention in Near-Linear Time	✅	❌	✅	❌	✅	❌	✅	4
HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion	❌	✅	✅	❌	✅	❌	✅	4
Hypergraph Dynamic System	✅	❌	✅	✅	❌	❌	✅	4
Hypothesis Search: Inductive Reasoning with Language Models	✅	❌	✅	❌	❌	❌	✅	3
I-PHYRE: Interactive Physical Reasoning	❌	❌	❌	✅	✅	❌	✅	3
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection	❌	❌	✅	✅	✅	❌	✅	4
INViTE: INterpret and Control Vision-Language Models with Text Explanations	❌	✅	✅	✅	✅	❌	✅	5
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks	❌	✅	✅	❌	✅	❌	✅	4
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs	✅	✅	✅	✅	✅	❌	✅	6
Idempotence and Perceptual Image Compression	❌	✅	✅	✅	✅	❌	✅	5
Idempotent Generative Network	✅	❌	✅	❌	❌	❌	✅	3
Identifiable Latent Polynomial Causal Models through the Lens of Change	❌	❌	✅	❌	❌	❌	✅	2
Identifying Policy Gradient Subspaces	❌	✅	✅	❌	❌	❌	✅	3
Identifying Representations for Intervention Extrapolation	✅	✅	❌	❌	❌	❌	✅	3
Identifying the Risks of LM Agents with an LM-Emulated Sandbox	❌	✅	❌	❌	❌	❌	✅	2
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks	✅	✅	✅	❌	✅	❌	✅	5
Image Background Serves as Good Proxy for Out-of-distribution Data	❌	❌	✅	❌	✅	❌	✅	3
Image Clustering Conditioned on Text Criteria	✅	✅	✅	❌	❌	✅	✅	5
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models	✅	✅	✅	✅	✅	❌	✅	6
Image Inpainting via Iteratively Decoupled Probabilistic Modeling	❌	✅	✅	✅	✅	❌	✅	5
Image Inpainting via Tractable Steering of Diffusion Models	✅	✅	✅	✅	❌	❌	✅	5
Image Translation as Diffusion Visual Programmers	✅	✅	✅	❌	✅	✅	✅	6
Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval	❌	❌	✅	✅	✅	❌	✅	4
ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms	❌	✅	✅	❌	❌	❌	❌	2
ImagenHub: Standardizing the evaluation of conditional image generation models	❌	✅	✅	❌	❌	❌	✅	3
Imitation Learning from Observation with Automatic Discount Scheduling	✅	✅	✅	❌	❌	❌	✅	4
Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control	❌	✅	❌	❌	❌	❌	✅	2
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds	❌	❌	❌	✅	❌	❌	❌	1
Implicit Maximum a Posteriori Filtering via Adaptive Optimization	✅	✅	✅	✅	❌	❌	✅	5
Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning	✅	❌	✅	✅	❌	❌	✅	4
Implicit Neural Representations and the Algebra of Complex Wavelets	❌	❌	✅	❌	❌	❌	✅	2
Implicit bias of SGD in $L_2$-regularized linear DNNs: One-way jumps from high to low rank	❌	❌	❌	❌	❌	❌	✅	1
Implicit regularization of deep residual networks towards neural ODEs	❌	✅	✅	❌	❌	❌	✅	3
ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering	✅	✅	✅	✅	❌	❌	✅	5
Improved Active Learning via Dependent Leverage Score Sampling	✅	❌	❌	❌	❌	❌	✅	2
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model	✅	❌	❌	❌	❌	❌	❌	1
Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling	❌	✅	✅	✅	❌	❌	✅	4
Improved Probabilistic Image-Text Representations	✅	✅	✅	✅	✅	❌	✅	6
Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning	✅	❌	✅	❌	❌	❌	✅	3
Improved Techniques for Training Consistency Models	❌	❌	✅	❌	✅	❌	✅	3
Improved algorithm and bounds for successive projection	✅	✅	❌	❌	❌	❌	✅	3
Improved sampling via learned diffusions	✅	✅	✅	❌	❌	❌	✅	4
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data	❌	❌	❌	❌	❌	❌	✅	1
Improving Convergence and Generalization Using Parameter Symmetries	✅	✅	✅	❌	❌	❌	✅	4
Improving Domain Generalization with Domain Relations	✅	❌	✅	✅	❌	❌	✅	4
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning	✅	❌	✅	❌	✅	❌	✅	4
Improving Intrinsic Exploration by Creating Stationary Objectives	✅	❌	✅	❌	❌	❌	✅	3
Improving LoRA in Privacy-preserving Federated Learning	❌	❌	✅	✅	✅	❌	✅	4
Improving Non-Transferable Representation Learning by Harnessing Content and Style	✅	✅	✅	✅	✅	✅	✅	7
Improving Offline RL by Blending Heuristics	✅	❌	✅	❌	✅	❌	✅	4
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis	❌	✅	✅	❌	✅	❌	✅	4
Improving protein optimization with smoothed fitness landscapes	✅	✅	✅	❌	✅	❌	✅	5
Improving the Convergence of Dynamic NeRFs via Optimal Transport	✅	✅	✅	❌	❌	❌	✅	4
In defense of parameter sharing for model-compression	❌	❌	✅	❌	✅	❌	✅	3
In-Context Learning Dynamics with Random Binary Sequences	❌	✅	✅	❌	✅	✅	✅	5
In-Context Learning Learns Label Relationships but Is Not Conventional Learning	❌	✅	✅	❌	❌	❌	✅	3
In-Context Learning through the Bayesian Prism	❌	✅	❌	❌	✅	❌	✅	3
In-Context Pretraining: Language Modeling Beyond Document Boundaries	✅	✅	✅	❌	✅	❌	✅	5
In-context Autoencoder for Context Compression in a Large Language Model	❌	✅	✅	❌	✅	✅	✅	5
In-context Exploration-Exploitation for Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
Incentive-Aware Federated Learning with Training-Time Model Rewards	✅	✅	✅	❌	✅	❌	✅	5
Incentivized Truthful Communication for Federated Bandits	✅	❌	❌	❌	❌	❌	✅	2
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning	❌	✅	✅	✅	✅	✅	✅	6
Incremental Randomized Smoothing Certification	✅	✅	✅	❌	✅	✅	✅	6
Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference	✅	❌	✅	❌	❌	❌	✅	3
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images	✅	✅	✅	❌	✅	❌	✅	5
Influencer Backdoor Attack on Semantic Segmentation	✅	✅	✅	✅	❌	❌	✅	5
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning	❌	✅	✅	✅	✅	❌	✅	5
InfoCon: Concept Discovery with Generative and Discriminative Informativeness	✅	✅	✅	✅	❌	❌	✅	5
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression	✅	✅	✅	❌	✅	❌	✅	5
Information Retention via Learning Supplemental Features	✅	✅	✅	✅	❌	❌	✅	5
Inherently Interpretable Time Series Classification via Multiple Instance Learning	❌	✅	✅	❌	✅	✅	✅	5
Initializing Models with Larger Ones	✅	✅	✅	❌	❌	❌	✅	4
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models	✅	❌	✅	✅	✅	❌	✅	5
Input-gradient space particle inference for neural network ensembles	✅	✅	✅	❌	✅	❌	✅	5
Ins-DetCLIP: Aligning Detection Model to Follow Human-Language Instruction	❌	❌	✅	✅	✅	❌	✅	4
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules	✅	❌	✅	❌	✅	✅	✅	5
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation	✅	✅	✅	❌	✅	✅	✅	6
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model	❌	❌	✅	❌	✅	❌	✅	3
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists	❌	✅	✅	✅	✅	✅	✅	6
InstructDET: Diversifying Referring Object Detection with Generalized Instructions	❌	✅	✅	✅	✅	❌	✅	5
InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image	❌	✅	✅	❌	✅	❌	✅	4
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior	❌	✅	✅	✅	✅	❌	✅	5
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions	✅	❌	✅	❌	❌	❌	✅	3
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures	✅	❌	❌	❌	❌	✅	✅	3
Intelligent Switching for Reset-Free RL	✅	✅	✅	❌	❌	❌	✅	4
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation	✅	✅	✅	✅	✅	❌	✅	6
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning	✅	✅	✅	❌	✅	❌	✅	5
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes	✅	❌	✅	✅	✅	❌	✅	5
Interpretable Diffusion via Information Decomposition	❌	✅	✅	✅	❌	✅	✅	5
Interpretable Meta-Learning of Physical Systems	✅	✅	❌	❌	❌	❌	✅	3
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction	✅	❌	✅	✅	❌	❌	✅	4
Interpreting CLIP's Image Representation via Text-Based Decomposition	✅	✅	✅	✅	❌	❌	✅	5
Interpreting Robustness Proofs of Deep Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach	✅	❌	✅	✅	❌	❌	✅	4
Intriguing Properties of Data Attribution on Diffusion Models	❌	✅	✅	✅	✅	✅	✅	6
Intriguing Properties of Generative Classifiers	✅	❌	✅	❌	❌	❌	✅	3
Invariance-based Learning of Latent Dynamics	❌	✅	✅	✅	✅	❌	✅	5
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Investigating the Benefits of Projection Head for Representation Learning	❌	❌	✅	❌	❌	❌	✅	2
Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video	❌	✅	✅	✅	✅	❌	✅	5
Is Self-Repair a Silver Bullet for Code Generation?	✅	✅	✅	❌	❌	✅	✅	5
Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching	❌	❌	✅	❌	❌	❌	✅	2
Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability	❌	✅	✅	✅	❌	❌	✅	4
It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition	❌	❌	✅	✅	❌	❌	✅	3
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting	❌	❌	❌	❌	❌	❌	❌	0
Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models	✅	❌	✅	❌	✅	❌	✅	4
JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention	❌	✅	✅	❌	❌	❌	✅	3
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling	❌	❌	✅	✅	✅	❌	✅	4
Jointly Training Large Autoregressive Multimodal Models	❌	❌	✅	❌	✅	❌	✅	3
Jointly-Learned Exit and Inference for a Dynamic Neural Network	✅	✅	✅	✅	❌	❌	✅	5
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX	✅	✅	✅	✅	✅	❌	✅	6
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval	❌	❌	✅	❌	❌	❌	✅	2
KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement	✅	✅	✅	✅	✅	❌	✅	6
Kalman Filter for Online Classification of Non-Stationary Data	✅	❌	✅	❌	❌	❌	✅	3
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies	✅	❌	✅	✅	✅	❌	✅	5
Kernelised Normalising Flows	❌	❌	✅	✅	✅	❌	✅	4
Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning	✅	✅	✅	❌	✅	❌	✅	5
Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models	✅	✅	✅	❌	✅	❌	✅	5
Knowledge Distillation Based on Transformed Teacher Matching	✅	✅	✅	✅	❌	❌	✅	5
Knowledge Fusion of Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
KoLA: Carefully Benchmarking World Knowledge of Large Language Models	❌	✅	✅	❌	✅	✅	✅	5
Koopman-based generalization bound: New aspect for full-rank weights	❌	❌	✅	❌	❌	✅	✅	3
Kosmos-G: Generating Images in Context with Multimodal Large Language Models	❌	❌	✅	✅	✅	❌	✅	4
L2MAC: Large Language Model Automatic Computer for Extensive Code Generation	✅	✅	✅	❌	❌	✅	✅	5
L2P-MIP: Learning to Presolve for Mixed Integer Programming	❌	✅	✅	❌	✅	✅	✅	5
LCOT: Linear Circular Optimal Transport	❌	❌	❌	❌	❌	❌	✅	1
LDReg: Local Dimensionality Regularized Self-Supervised Learning	✅	✅	✅	✅	✅	❌	✅	6
LEAP: Liberate Sparse-View 3D Modeling from Camera Poses	❌	✅	✅	✅	❌	❌	✅	4
LEGO-Prover: Neural Theorem Proving with Growing Libraries	✅	✅	✅	✅	❌	✅	✅	6
LEMON: Lossless model expansion	❌	❌	✅	✅	✅	❌	✅	4
LILO: Learning Interpretable Libraries by Compressing and Documenting Code	✅	✅	✅	❌	✅	❌	✅	5
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer	❌	✅	✅	✅	✅	✅	✅	6
LLM Augmented LLMs: Expanding Capabilities through Composition	❌	❌	✅	❌	❌	❌	❌	1
LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts	✅	✅	✅	❌	✅	✅	✅	6
LLM-Assisted Code Cleaning For Training Accurate Code Generators	❌	❌	✅	❌	✅	❌	✅	3
LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation	❌	✅	✅	❌	✅	❌	✅	4
LLM-grounded Video Diffusion Models	❌	❌	✅	❌	❌	❌	✅	2
LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors	❌	❌	✅	✅	✅	❌	✅	4
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention	❌	✅	✅	✅	✅	❌	✅	5
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset	❌	✅	✅	❌	✅	✅	✅	5
LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units	❌	✅	✅	✅	✅	❌	✅	5
LOQA: Learning with Opponent Q-Learning Awareness	✅	✅	✅	❌	✅	❌	✅	5
LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning	✅	✅	✅	✅	✅	❌	✅	6
LRM: Large Reconstruction Model for Single Image to 3D	❌	❌	✅	❌	✅	❌	✅	3
LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks	❌	✅	✅	✅	✅	❌	✅	5
LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition	❌	✅	✅	✅	✅	❌	✅	5
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models	❌	✅	✅	❌	✅	✅	✅	5
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models	✅	✅	✅	❌	✅	✅	✅	6
Label-Focused Inductive Bias over Latent Object Features in Visual Classification	❌	✅	✅	✅	✅	❌	✅	5
Label-Noise Robust Diffusion Models	✅	✅	✅	❌	✅	✅	✅	6
Label-free Node Classification on Graphs with Large Language Models (LLMs)	❌	✅	✅	✅	❌	❌	✅	4
LabelDP-Pro: Learning with Label Differential Privacy via Projections	✅	❌	✅	❌	✅	❌	✅	4
Lagrangian Flow Networks for Conservation Laws	❌	✅	✅	✅	✅	✅	✅	6
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving	❌	✅	✅	✅	✅	❌	✅	5
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited	❌	❌	❌	❌	❌	❌	✅	1
Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks	✅	✅	✅	❌	✅	❌	✅	5
Language Model Beats Diffusion - Tokenizer is key to visual generation	❌	❌	✅	❌	❌	❌	✅	2
Language Model Cascades: Token-Level Uncertainty And Beyond	❌	❌	✅	✅	❌	❌	✅	3
Language Model Decoding as Direct Metrics Optimization	✅	❌	✅	✅	✅	❌	✅	5
Language Model Detectors Are Easily Optimized Against	❌	✅	✅	❌	❌	❌	✅	3
Language Model Inversion	✅	✅	✅	❌	❌	❌	✅	4
Language Model Self-improvement by Reinforcement Learning Contemplation	✅	❌	✅	❌	✅	❌	✅	4
Language Modeling Is Compression	❌	✅	✅	❌	❌	❌	✅	3
Language Models Represent Space and Time	❌	✅	✅	✅	❌	❌	✅	4
Language-Informed Visual Concept Learning	❌	❌	❌	❌	✅	❌	✅	2
Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication	✅	❌	✅	❌	❌	✅	✅	4
LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment	❌	❌	✅	✅	❌	❌	✅	3
Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI	❌	✅	✅	✅	✅	✅	✅	6
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior	❌	❌	✅	❌	❌	❌	❌	1
Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning	❌	✅	✅	✅	❌	✅	✅	5
Large Language Models Are Not Robust Multiple Choice Selectors	✅	✅	✅	❌	✅	❌	✅	5
Large Language Models Cannot Self-Correct Reasoning Yet	❌	❌	✅	❌	❌	❌	✅	2
Large Language Models are Efficient Learners of Noise-Robust Speech Recognition	✅	✅	✅	✅	✅	❌	✅	6
Large Language Models as Analogical Reasoners	✅	❌	✅	❌	❌	❌	✅	3
Large Language Models as Automated Aligners for benchmarking Vision-Language Models	❌	❌	✅	✅	❌	❌	✅	3
Large Language Models as Generalizable Policies for Embodied Tasks	❌	✅	✅	❌	✅	❌	✅	4
Large Language Models as Optimizers	❌	✅	✅	✅	❌	❌	✅	4
Large Language Models as Tool Makers	✅	✅	✅	✅	❌	❌	✅	5
Large Language Models to Enhance Bayesian Optimization	❌	✅	✅	❌	✅	✅	✅	5
Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages	❌	✅	✅	❌	❌	❌	✅	3
Large-Vocabulary 3D Diffusion Model with Transformer	❌	❌	✅	❌	❌	❌	❌	1
Large-scale Training of Foundation Models for Wearable Biosignals	✅	❌	❌	✅	✅	❌	✅	4
Latent 3D Graph Diffusion	✅	✅	✅	✅	❌	❌	❌	4
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video	✅	❌	❌	❌	✅	❌	✅	3
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck	❌	❌	✅	✅	✅	❌	✅	4
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time	✅	✅	✅	✅	❌	✅	✅	6
Layer-wise linear mode connectivity	❌	✅	✅	❌	❌	❌	✅	3
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Learning 3D Particle-based Simulators from RGB-D Videos	✅	❌	✅	❌	❌	❌	✅	3
Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network	✅	✅	✅	✅	✅	❌	✅	6
Learning Conditional Invariances through Non-Commutativity	❌	✅	✅	❌	❌	❌	❌	2
Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior	✅	❌	❌	❌	✅	✅	✅	4
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings	❌	✅	✅	❌	❌	❌	✅	3
Learning Energy Decompositions for Partial Inference in GFlowNets	✅	✅	✅	❌	✅	❌	✅	5
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood	✅	❌	✅	❌	✅	❌	✅	4
Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer	❌	✅	✅	✅	❌	❌	✅	4
Learning From Simplicial Data Based on Random Walks and 1D Convolutions	❌	✅	✅	❌	❌	❌	✅	3
Learning Grounded Action Abstractions from Language	✅	✅	✅	❌	❌	❌	✅	4
Learning Hierarchical Image Segmentation For Recognition and By Recognition	✅	✅	✅	✅	✅	❌	✅	6
Learning Hierarchical Polynomials with Three-Layer Neural Networks	✅	❌	❌	❌	✅	❌	✅	3
Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics	✅	✅	✅	❌	❌	❌	✅	4
Learning Implicit Representation for Reconstructing Articulated Objects	✅	✅	✅	❌	✅	❌	✅	5
Learning Interactive Real-World Simulators	❌	❌	✅	✅	✅	❌	✅	4
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG	❌	✅	✅	❌	❌	❌	✅	3
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach	✅	✅	✅	❌	❌	❌	✅	4
Learning Multi-Agent Communication from Graph Modeling Perspective	✅	✅	✅	❌	❌	❌	✅	4
Learning Multi-Agent Communication with Contrastive Learning	❌	❌	❌	❌	❌	❌	✅	1
Learning Multi-Faceted Prototypical User Interests	✅	✅	✅	✅	✅	❌	✅	6
Learning Nash Equilibria in Rank-1 Games	✅	✅	❌	❌	❌	❌	❌	2
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s)	✅	✅	✅	✅	✅	❌	✅	6
Learning Optimal Contracts: How to Exploit Small Action Spaces	✅	❌	❌	❌	❌	❌	❌	1
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks	❌	✅	✅	✅	✅	❌	✅	5
Learning Performance-Improving Code Edits	❌	✅	✅	✅	✅	✅	✅	6
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients	✅	✅	✅	✅	✅	❌	✅	6
Learning Planning Abstractions from Language	❌	✅	✅	❌	❌	❌	✅	3
Learning Polynomial Problems with $SL(2, \mathbb{R})$-Equivariance	✅	✅	❌	✅	✅	❌	✅	5
Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation	❌	❌	✅	❌	✅	❌	✅	3
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning	❌	✅	✅	✅	✅	❌	✅	5
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling	❌	✅	✅	❌	✅	❌	✅	4
Learning Thresholds with Latent Values and Censored Feedback	❌	❌	❌	❌	❌	❌	✅	1
Learning dynamic representations of the functional connectome in neurobiological networks	❌	✅	✅	❌	❌	❌	✅	3
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions	✅	❌	✅	❌	❌	❌	✅	3
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation	✅	❌	✅	✅	✅	❌	✅	5
Learning from Sparse Offline Datasets via Conservative Density Estimation	✅	✅	✅	❌	✅	❌	✅	5
Learning in reverse causal strategic environments with ramifications on two sided markets	✅	❌	❌	❌	❌	✅	✅	3
Learning interpretable control inputs and dynamics underlying animal locomotion	❌	❌	✅	✅	✅	❌	✅	4
Learning invariant representations of time-homogeneous stochastic dynamical systems	✅	✅	✅	✅	❌	❌	✅	5
Learning model uncertainty as variance-minimizing instance weights	✅	❌	✅	✅	❌	❌	✅	4
Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.	❌	✅	❌	❌	✅	❌	✅	3
Learning the greatest common divisor: explaining transformer predictions	❌	✅	❌	❌	✅	❌	✅	3
Learning to Act from Actionless Videos through Dense Correspondences	❌	✅	✅	✅	✅	❌	✅	5
Learning to Act without Actions	❌	✅	✅	❌	❌	❌	✅	3
Learning to Compose: Improving Object Centric Learning by Injecting Compositionality	❌	❌	✅	✅	❌	✅	✅	4
Learning to Embed Time Series Patches Independently	❌	✅	✅	✅	❌	❌	✅	4
Learning to Jointly Understand Visual and Tactile Signals	❌	❌	❌	❌	✅	✅	✅	3
Learning to Make Adherence-aware Advice	✅	❌	❌	❌	❌	❌	✅	2
Learning to Reject Meets Long-tail Learning	✅	❌	✅	✅	❌	❌	✅	4
Learning to Reject with a Fixed Predictor: Application to Decontextualization	❌	❌	✅	✅	❌	✅	✅	4
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances	✅	✅	❌	❌	❌	❌	✅	3
Learning to Solve Bilevel Programs with Binary Tender	✅	❌	❌	❌	❌	❌	✅	2
Learning to design protein-protein interactions with enhanced generalization	✅	✅	✅	✅	✅	❌	✅	6
Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model	✅	❌	❌	❌	✅	❌	✅	3
Learning with Language-Guided State Abstractions	❌	❌	✅	❌	✅	❌	✅	3
Learning with Mixture of Prototypes for Out-of-Distribution Detection	✅	✅	✅	❌	✅	❌	✅	5
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction	❌	❌	✅	✅	❌	❌	✅	3
Leave-one-out Distinguishability in Machine Learning	❌	✅	✅	✅	❌	❌	✅	4
Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models	✅	✅	✅	✅	✅	❌	✅	6
Lemur: Harmonizing Natural Language and Code for Language Agents	❌	✅	✅	❌	✅	❌	✅	4
Lemur: Integrating Large Language Models in Automated Program Verification	✅	✅	✅	❌	❌	❌	✅	4
Less is More: Fewer Interpretable Region via Submodular Subset Selection	✅	✅	✅	✅	✅	❌	✅	6
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs	✅	✅	✅	✅	✅	❌	✅	6
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation	❌	✅	✅	✅	✅	❌	✅	5
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation	❌	✅	✅	❌	❌	❌	✅	3
Let Models Speak Ciphers: Multiagent Debate through Embeddings	✅	❌	✅	✅	✅	❌	✅	5
Let's Verify Step by Step	❌	✅	✅	✅	❌	❌	✅	4
Let's do the time-warp-attend: Learning topological invariants of dynamical systems	❌	✅	✅	❌	✅	✅	✅	5
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data	❌	✅	✅	❌	❌	❌	✅	3
Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design	✅	✅	✅	❌	✅	❌	✅	5
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control	❌	❌	✅	✅	❌	❌	✅	3
Leveraging Optimization for Adaptive Attacks on Image Watermarks	✅	❌	✅	❌	✅	❌	✅	4
Leveraging Uncertainty Estimates To Improve Classifier Performance	✅	❌	✅	✅	✅	❌	✅	5
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency	❌	✅	✅	✅	✅	❌	✅	5
Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning	❌	✅	✅	❌	✅	❌	✅	4
Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments	✅	✅	✅	❌	❌	❌	✅	4
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection	✅	✅	✅	✅	✅	❌	✅	6
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures	❌	❌	✅	✅	❌	❌	✅	3
Lie Group Decompositions for Equivariant Neural Networks	❌	✅	✅	❌	❌	❌	✅	3
Lifting Architectural Constraints of Injective Flows	❌	✅	✅	✅	✅	✅	✅	6
Light Schrödinger Bridge	❌	✅	✅	❌	❌	❌	✅	3
Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset	✅	✅	✅	❌	✅	✅	❌	5
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference	✅	❌	✅	✅	✅	❌	✅	5
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds	❌	❌	✅	✅	❌	❌	✅	3
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps	❌	✅	✅	❌	✅	❌	✅	4
Linear Log-Normal Attention with Unbiased Concentration	❌	✅	✅	❌	❌	❌	✅	3
Linear attention is (maybe) all you need (to understand Transformer optimization)	❌	❌	❌	❌	❌	❌	✅	1
Linearity of Relation Decoding in Transformer Language Models	❌	✅	✅	❌	✅	❌	✅	4
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts	❌	❌	✅	❌	❌	❌	✅	2
LipSim: A Provably Robust Perceptual Similarity Metric	❌	❌	✅	❌	❌	❌	✅	2
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading	✅	✅	✅	❌	✅	❌	✅	5
Lipschitz Singularities in Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance	❌	✅	✅	✅	✅	❌	✅	5
Listen, Think, and Understand	❌	✅	✅	✅	✅	❌	✅	5
LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses	❌	✅	✅	✅	✅	❌	✅	5
Llemma: An Open Language Model for Mathematics	❌	✅	✅	✅	✅	❌	✅	5
LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents	❌	✅	✅	✅	✅	❌	✅	5
Local Composite Saddle Point Optimization	✅	❌	✅	❌	❌	❌	✅	3
Local Graph Clustering with Noisy Labels	❌	❌	✅	✅	✅	❌	✅	4
Local Search GFlowNets	✅	✅	✅	❌	❌	❌	✅	4
Locality Sensitive Sparse Encoding for Learning World Models Online	✅	✅	✅	✅	❌	❌	✅	5
Locality-Aware Graph Rewiring in GNNs	✅	✅	✅	✅	✅	❌	✅	6
Localizing and Editing Knowledge In Text-to-Image Generative Models	❌	✅	✅	❌	❌	❌	✅	3
LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints	✅	✅	✅	❌	✅	❌	✅	5
Logical Languages Accepted by Transformer Encoders with Hard Attention	❌	❌	❌	❌	❌	❌	❌	0
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation	✅	✅	✅	✅	✅	❌	✅	6
Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data	❌	✅	✅	✅	✅	❌	✅	5
Long-tailed Diffusion Models with Oriented Calibration	✅	✅	✅	✅	❌	❌	✅	5
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models	❌	❌	✅	❌	✅	❌	✅	3
Looped Transformers are Better at Learning Learning Algorithms	❌	✅	✅	✅	❌	❌	✅	4
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time	✅	❌	❌	❌	❌	❌	❌	1
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering	✅	✅	✅	✅	✅	✅	✅	7
MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
MAP IT to Visualize Representations	❌	✅	✅	❌	❌	❌	✅	3
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding	✅	✅	✅	✅	✅	✅	✅	7
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning	❌	❌	✅	❌	❌	❌	✅	2
MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods	❌	❌	✅	✅	✅	❌	✅	4
MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data	❌	✅	✅	❌	✅	✅	✅	5
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning	❌	✅	✅	✅	✅	✅	✅	6
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training	✅	❌	✅	✅	✅	❌	✅	5
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction	✅	✅	✅	❌	✅	❌	✅	5
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process	✅	✅	✅	❌	✅	❌	✅	5
MINDE: Mutual Information Neural Diffusion Estimation	✅	✅	✅	❌	❌	❌	✅	4
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback	❌	✅	✅	❌	❌	❌	✅	3
MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations	❌	✅	✅	✅	✅	✅	✅	6
MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy	✅	✅	✅	✅	❌	❌	✅	5
MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning	✅	✅	✅	✅	✅	❌	✅	6
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design	✅	✅	✅	✅	❌	✅	✅	6
MOFI: Learning Image Representations from Noisy Entity Annotated Images	❌	✅	✅	✅	❌	❌	✅	4
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records	❌	✅	✅	✅	✅	✅	✅	6
MT-Ranker: Reference-free machine translation evaluation by inter-system ranking	❌	✅	✅	✅	✅	❌	✅	5
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following	❌	✅	✅	✅	✅	✅	✅	6
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data	✅	✅	✅	✅	❌	❌	✅	5
MVDream: Multi-view Diffusion for 3D Generation	✅	❌	✅	✅	✅	✅	✅	6
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo	❌	✅	✅	✅	✅	❌	✅	5
MaGIC: Multi-modality Guided Image Completion	✅	❌	✅	✅	✅	❌	✅	5
Machine Unlearning for Image-to-Image Generative Models	✅	✅	✅	✅	✅	❌	✅	6
Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors	❌	✅	✅	❌	✅	✅	✅	5
MagicDrive: Street View Generation with Diverse 3D Geometry Control	❌	✅	✅	✅	✅	❌	✅	5
Magnitude Invariant Parametrizations Improve Hypernetwork Learning	❌	✅	✅	✅	❌	❌	✅	4
Magnushammer: A Transformer-Based Approach to Premise Selection	✅	❌	✅	✅	✅	❌	✅	5
Making LLaMA SEE and Draw with SEED Tokenizer	❌	✅	✅	✅	✅	❌	✅	5
Making Pre-trained Language Models Great on Tabular Prediction	❌	✅	✅	✅	✅	✅	✅	6
Making RL with Preference-based Feedback Efficient via Randomization	✅	❌	❌	❌	❌	❌	❌	1
Making Retrieval-Augmented Language Models Robust to Irrelevant Context	❌	✅	✅	❌	❌	❌	✅	3
Manifold Diffusion Fields	✅	❌	✅	✅	✅	❌	✅	5
Manifold Preserving Guided Diffusion	✅	✅	✅	❌	✅	❌	✅	5
Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems	❌	❌	✅	✅	✅	❌	✅	4
Mask-Based Modeling for Neural Radiance Fields	❌	✅	✅	❌	✅	❌	✅	4
Masked Audio Generation using a Single Non-Autoregressive Transformer	✅	❌	✅	✅	✅	❌	✅	5
Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners	✅	✅	✅	✅	✅	❌	✅	6
Masked Completion via Structured Diffusion with White-Box Transformers	✅	✅	✅	❌	❌	❌	✅	4
Masked Distillation Advances Self-Supervised Transformer Architecture Search	✅	❌	✅	✅	❌	❌	✅	4
Masked Structural Growth for 2x Faster Language Model Pre-training	❌	✅	✅	✅	✅	❌	✅	5
Masks, Signs, And Learning Rate Rewinding	❌	❌	✅	❌	✅	❌	✅	3
Massive Editing for Large Language Models via Meta Learning	✅	✅	✅	✅	✅	❌	✅	6
Massively Scalable Inverse Reinforcement Learning in Google Maps	✅	❌	❌	✅	✅	❌	✅	4
Mastering Memory Tasks with World Models	✅	✅	✅	❌	✅	❌	✅	5
Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching	❌	✅	✅	✅	❌	❌	✅	4
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning	❌	❌	✅	❌	✅	❌	✅	3
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts	✅	❌	✅	✅	❌	❌	✅	4
Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem	❌	❌	✅	❌	❌	❌	✅	2
Matrix Manifold Neural Networks++	✅	❌	✅	✅	✅	❌	✅	5
Matryoshka Diffusion Models	✅	✅	✅	✅	✅	❌	✅	6
Maximum Entropy Heterogeneous-Agent Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Maximum Entropy Model Correction in Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift	❌	❌	❌	❌	❌	❌	❌	0
Mayfly: a Neural Data Structure for Graph Stream Summarization	✅	✅	✅	❌	✅	❌	✅	5
Mean Field Theory in Deep Metric Learning	✅	❌	✅	✅	✅	❌	✅	5
Meaning Representations from Trajectories in Autoregressive Models	✅	✅	✅	✅	❌	❌	✅	5
Measuring Vision-Language STEM Skills of Neural Models	❌	✅	✅	✅	✅	❌	✅	5
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks	✅	❌	✅	❌	❌	❌	✅	3
Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games	❌	❌	✅	❌	✅	❌	❌	2
Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis	❌	❌	✅	✅	✅	❌	✅	4
Memorization Capacity of Multi-Head Attention in Transformers	❌	✅	✅	❌	✅	❌	✅	4
Memorization in Self-Supervised Learning Improves Downstream Generalization	❌	❌	✅	✅	✅	❌	✅	4
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation	❌	❌	✅	❌	✅	❌	✅	3
Memory-Consistent Neural Networks for Imitation Learning	✅	✅	✅	❌	✅	❌	✅	5
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy	✅	✅	✅	✅	✅	❌	✅	6
Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction	✅	✅	✅	✅	❌	❌	✅	5
Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis	✅	❌	❌	✅	❌	❌	✅	3
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer	✅	❌	✅	❌	❌	✅	✅	4
Meta-Learning Priors Using Unrolled Proximal Networks	✅	✅	✅	✅	✅	❌	✅	6
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes	❌	❌	✅	❌	❌	❌	✅	2
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation	❌	✅	✅	✅	❌	❌	❌	3
MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework	❌	✅	✅	❌	❌	❌	✅	3
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning	❌	✅	❌	✅	❌	❌	✅	3
MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use	❌	✅	✅	❌	❌	❌	✅	3
MgNO: Efficient Parameterization of Linear Operators via Multigrid	✅	✅	✅	✅	✅	❌	✅	6
Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning	✅	✅	✅	✅	✅	❌	✅	6
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
MiniLLM: Knowledge Distillation of Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods	❌	❌	❌	❌	❌	❌	❌	0
Minimum width for universal approximation using ReLU networks on compact domain	❌	❌	❌	❌	❌	❌	❌	0
Mirage: Model-agnostic Graph Distillation for Graph Classification	✅	✅	✅	✅	✅	❌	✅	6
Mitigating Emergent Robustness Degradation while Scaling Graph Learning	❌	✅	✅	✅	✅	❌	✅	5
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning	❌	✅	✅	❌	✅	❌	❌	3
Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing	✅	✅	✅	✅	❌	❌	✅	5
MixSATGEN: Learning Graph Mixing for SAT Instance Generation	✅	✅	✅	❌	✅	❌	✅	5
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection	❌	✅	✅	✅	✅	❌	❌	4
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space	✅	✅	✅	✅	✅	❌	✅	6
Mixture of LoRA Experts	❌	✅	✅	❌	❌	❌	✅	3
Mixture of Weak and Strong Experts on Graphs	✅	✅	✅	✅	✅	❌	✅	6
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models	❌	❌	✅	✅	✅	❌	✅	4
Model Merging by Uncertainty-Based Gradient Matching	❌	❌	✅	❌	❌	❌	✅	2
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs	✅	✅	✅	❌	✅	❌	✅	5
Modeling Boundedly Rational Agents with Latent Inference Budgets	❌	❌	✅	✅	❌	❌	✅	3
Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems	✅	❌	✅	✅	✅	❌	✅	5
Modelling complex vector drawings with stroke-clouds	❌	✅	✅	❌	✅	❌	✅	4
ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis	❌	✅	✅	✅	✅	❌	✅	5
Modulate Your Spectrum in Self-Supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects	✅	✅	✅	❌	❌	❌	✅	4
MogaNet: Multi-order Gated Aggregation Network	❌	✅	✅	✅	✅	❌	✅	5
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Momentum Benefits Non-iid Federated Learning Simply and Provably	✅	❌	✅	❌	❌	❌	✅	3
Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.	✅	✅	✅	❌	❌	❌	✅	4
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory	❌	✅	✅	❌	✅	❌	✅	4
Most discriminative stimuli for functional cell type clustering	✅	✅	✅	✅	❌	❌	✅	5
Motif: Intrinsic Motivation from Artificial Intelligence Feedback	❌	✅	✅	✅	✅	❌	✅	5
Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators	❌	✅	✅	❌	✅	✅	✅	5
MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field	❌	❌	✅	❌	✅	❌	✅	3
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning	✅	✅	✅	❌	✅	❌	❌	4
MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images	❌	✅	✅	❌	✅	❌	✅	4
Multi-Resolution Diffusion Models for Time Series Forecasting	✅	❌	✅	❌	✅	❌	✅	4
Multi-Scale Representations by Varying Window Attention for Semantic Segmentation	❌	✅	✅	✅	✅	❌	✅	5
Multi-Source Diffusion Models for Simultaneous Music Generation and Separation	✅	✅	✅	✅	✅	✅	✅	7
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts	✅	✅	✅	❌	❌	❌	✅	4
Multi-View Causal Representation Learning with Partial Observability	❌	✅	✅	❌	❌	❌	✅	3
Multi-View Representation is What You Need for Point-Cloud Pre-Training	❌	❌	✅	✅	✅	❌	✅	4
Multi-granularity Correspondence Learning from Long-term Noisy Videos	❌	✅	✅	❌	✅	✅	✅	5
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data	❌	✅	✅	✅	✅	❌	✅	5
Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction	❌	✅	✅	✅	✅	❌	✅	5
Multi-task Learning with 3D-Aware Regularization	❌	✅	✅	❌	❌	❌	✅	3
Multilinear Operator Networks	❌	✅	✅	✅	✅	❌	✅	5
Multilingual Jailbreak Challenges in Large Language Models	✅	❌	✅	❌	❌	❌	✅	3
Multimarginal Generative Modeling with Stochastic Interpolants	✅	❌	✅	❌	❌	❌	✅	3
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications	❌	✅	✅	❌	✅	❌	✅	4
Multimodal Molecular Pretraining via Modality Blending	❌	❌	✅	✅	❌	❌	✅	3
Multimodal Patient Representation Learning with Missing Modalities and Labels	✅	✅	✅	✅	✅	✅	✅	7
Multimodal Web Navigation with Instruction-Finetuned Foundation Models	❌	✅	✅	❌	✅	❌	✅	4
Multiscale Positive-Unlabeled Detection of AI-Generated Texts	❌	✅	✅	✅	✅	❌	✅	5
Multisize Dataset Condensation	✅	✅	✅	✅	❌	❌	✅	5
NECO: NEural Collapse Based Out-of-distribution detection	✅	✅	✅	❌	❌	❌	✅	4
NEFTune: Noisy Embeddings Improve Instruction Finetuning	✅	✅	✅	❌	✅	❌	✅	5
NOLA: Compressing LoRA using Linear Combination of Random Basis	❌	✅	✅	✅	✅	❌	✅	5
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers	❌	❌	✅	❌	✅	❌	✅	3
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace	❌	✅	✅	❌	❌	❌	❌	2
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation	❌	✅	✅	❌	❌	❌	✅	3
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation	❌	❌	✅	✅	✅	❌	✅	4
NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis	✅	❌	✅	❌	✅	✅	✅	5
Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss	✅	❌	❌	❌	❌	❌	❌	1
Near-Optimal Solutions of Constrained Learning Problems	✅	❌	✅	❌	❌	❌	✅	3
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization	❌	❌	❌	❌	❌	❌	❌	0
Negative Label Guided OOD Detection with Pretrained Vision-Language Models	✅	✅	✅	✅	✅	✅	✅	7
Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation	✅	✅	✅	❌	✅	❌	✅	5
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models	✅	✅	✅	❌	❌	❌	✅	4
NetInfoF Framework: Measuring and Exploiting Network Usable Information	✅	✅	✅	✅	✅	❌	✅	6
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings	✅	❌	✅	✅	✅	✅	✅	6
Neur2RO: Neural Two-Stage Robust Optimization	✅	✅	✅	✅	✅	✅	✅	7
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization	✅	✅	✅	❌	✅	❌	✅	5
Neural Active Learning Beyond Bandits	✅	❌	✅	✅	❌	❌	✅	4
Neural Architecture Retrieval	✅	❌	✅	❌	❌	❌	✅	3
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel	✅	✅	✅	❌	✅	❌	✅	5
Neural Auto-designer for Enhanced Quantum Kernels	✅	✅	✅	✅	✅	❌	✅	6
Neural Common Neighbor with Completion for Link Prediction	❌	✅	✅	✅	✅	❌	✅	5
Neural Contractive Dynamical Systems	✅	❌	✅	❌	❌	❌	✅	3
Neural Field Classifiers via Target Encoding and Classification Loss	❌	✅	✅	✅	✅	❌	✅	5
Neural Fine-Tuning Search for Few-Shot Learning	✅	✅	✅	✅	❌	❌	✅	5
Neural Fourier Transform: A General Approach to Equivariant Representation Learning	✅	✅	✅	✅	✅	❌	✅	6
Neural Language of Thought Models	❌	❌	✅	✅	✅	❌	✅	4
Neural Neighborhood Search for Multi-agent Path Finding	❌	❌	✅	✅	✅	❌	✅	4
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization	✅	❌	❌	❌	❌	❌	❌	1
Neural Optimal Transport with General Cost Functionals	✅	✅	✅	❌	✅	❌	✅	5
Neural Polynomial Gabor Fields for Macro Motion Analysis	❌	❌	❌	❌	✅	❌	❌	1
Neural Processing of Tri-Plane Hybrid Neural Fields	❌	✅	✅	✅	✅	❌	✅	5
Neural Rate Control for Learned Video Compression	❌	❌	✅	❌	❌	❌	✅	2
Neural SDF Flow for 3D Reconstruction of Dynamic Scenes	❌	✅	✅	❌	✅	❌	✅	4
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries	❌	❌	✅	❌	❌	❌	✅	2
Neural Spectral Methods: Self-supervised learning in the spectral domain	❌	✅	❌	❌	❌	❌	✅	2
Neural structure learning with stochastic differential equations	✅	✅	✅	❌	❌	❌	❌	3
Neural-Symbolic Recursive Machine for Systematic Generalization	✅	❌	✅	✅	✅	❌	✅	5
Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning	✅	✅	✅	✅	✅	❌	✅	6
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data	❌	✅	❌	❌	❌	❌	✅	2
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization	❌	✅	✅	✅	✅	✅	✅	6
Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice	❌	❌	✅	✅	❌	❌	✅	3
Neurosymbolic Grounding for Compositional World Models	✅	✅	✅	✅	✅	❌	✅	6
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors	❌	✅	✅	✅	✅	❌	✅	5
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions	✅	❌	✅	❌	✅	❌	✅	4
NfgTransformer: Equivariant Representation Learning for Normal-form Games	❌	✅	❌	❌	❌	❌	✅	2
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space	✅	✅	✅	✅	✅	❌	✅	6
Noise Map Guidance: Inversion with Spatial Context for Real Image Editing	❌	✅	✅	✅	❌	❌	✅	4
Noise-free Score Distillation	❌	❌	✅	❌	❌	❌	✅	2
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation	❌	✅	✅	❌	❌	❌	✅	3
Noisy Interpolation Learning with Shallow Univariate ReLU Networks	❌	❌	❌	❌	❌	❌	❌	0
Non-Exchangeable Conformal Risk Control	❌	✅	✅	✅	❌	❌	✅	4
Non-negative Contrastive Learning	❌	✅	✅	❌	❌	❌	✅	3
Nougat: Neural Optical Understanding for Academic Documents	❌	✅	✅	❌	✅	❌	✅	4
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations	❌	✅	✅	❌	❌	✅	❌	3
NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling	❌	✅	✅	❌	✅	❌	✅	4
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference	✅	✅	✅	✅	✅	❌	✅	6
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers	❌	✅	✅	✅	✅	❌	✅	5
ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update	✅	✅	✅	❌	❌	❌	✅	4
OMNI: Open-endedness via Models of human Notions of Interestingness	✅	❌	✅	❌	✅	❌	✅	4
OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS	❌	❌	❌	❌	❌	❌	❌	0
OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning	✅	✅	✅	❌	❌	❌	✅	4
OWL: A Large Language Model for IT Operations	❌	✅	✅	✅	❌	❌	✅	4
Object centric architectures enable efficient causal representation learning	❌	✅	❌	✅	✅	❌	✅	4
Object-Aware Inversion and Reassembly for Image Editing	❌	❌	❌	❌	✅	❌	✅	2
Object-Centric Learning with Slot Mixture Module	✅	✅	✅	✅	❌	❌	✅	5
Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE	❌	✅	✅	❌	✅	❌	✅	4
OctoPack: Instruction Tuning Code Large Language Models	❌	✅	✅	❌	❌	❌	❌	2
Off-Policy Primal-Dual Safe Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees	✅	✅	✅	❌	❌	❌	✅	4
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity	✅	❌	✅	❌	✅	❌	✅	4
OmniControl: Control Any Joint at Any Time for Human Motion Generation	✅	❌	✅	❌	✅	❌	✅	4
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation	✅	❌	✅	❌	✅	❌	✅	4
On Adversarial Training without Perturbing all Examples	❌	✅	✅	✅	❌	❌	✅	4
On Bias-Variance Alignment in Deep Models	❌	❌	✅	❌	❌	❌	✅	2
On Differentially Private Federated Linear Contextual Bandits	✅	❌	✅	❌	❌	❌	✅	3
On Diffusion Modeling for Anomaly Detection	✅	✅	✅	❌	✅	❌	✅	5
On Double Descent in Reinforcement Learning with LSTD and Random Features	❌	❌	❌	❌	❌	❌	✅	1
On Error Propagation of Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
On Harmonizing Implicit Subpopulations	❌	✅	✅	✅	✅	✅	✅	6
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation	✅	❌	❌	❌	❌	❌	❌	1
On Representation Complexity of Model-based and Model-free Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
On Stationary Point Convergence of PPO-Clip	❌	❌	❌	❌	❌	❌	❌	0
On Trajectory Augmentations for Off-Policy Evaluation	❌	❌	✅	❌	✅	❌	✅	3
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models	❌	❌	❌	❌	❌	❌	✅	1
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection	❌	❌	✅	❌	❌	❌	✅	2
On the Effect of Batch Size in Byzantine-Robust Distributed Learning	✅	✅	✅	❌	✅	❌	✅	5
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning	❌	❌	❌	❌	❌	❌	❌	0
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing	✅	✅	✅	❌	❌	❌	✅	4
On the Foundations of Shortcut Learning	❌	❌	✅	✅	❌	❌	✅	3
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations	❌	✅	❌	❌	❌	❌	✅	2
On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback	✅	❌	❌	❌	❌	❌	❌	1
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs	❌	✅	✅	❌	✅	❌	✅	4
On the Joint Interaction of Models, Data, and Features	✅	❌	✅	❌	✅	❌	✅	4
On the Learnability of Watermarks for Language Models	❌	✅	✅	✅	✅	❌	✅	5
On the Limitations of Temperature Scaling for Distributions with Overlaps	❌	✅	✅	✅	✅	❌	✅	5
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods	❌	✅	✅	✅	❌	❌	✅	4
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting	✅	✅	✅	❌	✅	❌	✅	5
On the Parameterization of Second-Order Optimization Effective towards the Infinite Width	❌	❌	✅	❌	❌	❌	✅	2
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification	✅	✅	✅	❌	❌	❌	✅	4
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters	❌	❌	❌	❌	❌	❌	❌	0
On the Provable Advantage of Unsupervised Pretraining	✅	❌	❌	❌	❌	❌	❌	1
On the Reliability of Watermarks for Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
On the Role of Discrete Tokenization in Visual Representation Learning	❌	✅	✅	❌	❌	❌	✅	3
On the Role of General Function Approximation in Offline Reinforcement Learning	❌	❌	❌	❌	❌	❌	❌	0
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
On the Stability of Expressive Positional Encodings for Graphs	❌	✅	✅	✅	✅	❌	✅	5
On the Stability of Iterative Retraining of Generative Models on their own Data	✅	✅	✅	❌	❌	❌	✅	4
On the Variance of Neural Network Training with respect to Test Sets and Distributions	❌	✅	✅	✅	❌	❌	✅	4
On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks	✅	❌	✅	✅	✅	❌	✅	5
On the generalization capacity of neural networks during generic multimodal reasoning	❌	✅	✅	✅	✅	✅	✅	6
On the hardness of learning under symmetries	❌	❌	✅	❌	❌	❌	✅	2
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes	✅	❌	✅	✅	✅	❌	✅	5
One For All: Towards Training One Graph Model For All Classification Tasks	❌	✅	✅	✅	❌	❌	✅	4
One Forward is Enough for Neural Network Training via Likelihood Ratio Method	✅	❌	✅	❌	✅	✅	✅	5
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention	❌	❌	❌	❌	❌	❌	✅	1
One-hot Generalized Linear Model for Switching Brain State Discovery	❌	✅	✅	❌	❌	❌	✅	3
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models	✅	✅	✅	❌	✅	❌	✅	5
One-shot Empirical Privacy Estimation for Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Online Continual Learning for Interactive Instruction Following Agents	✅	✅	✅	✅	❌	❌	✅	5
Online GNN Evaluation Under Test-time Graph Distribution Shifts	✅	✅	✅	✅	✅	❌	✅	6
Online Information Acquisition: Hiring Multiple Agents	✅	❌	❌	❌	❌	❌	❌	1
Online Stabilization of Spiking Neural Networks	✅	✅	✅	❌	✅	✅	✅	6
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling	✅	❌	❌	❌	❌	❌	✅	2
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy	❌	✅	✅	✅	❌	❌	✅	4
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data	❌	✅	✅	❌	❌	❌	✅	3
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views	❌	❌	✅	❌	❌	❌	✅	2
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners	❌	❌	✅	❌	❌	✅	✅	3
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text	❌	✅	✅	❌	✅	❌	✅	4
Optimal Sample Complexity for Average Reward Markov Decision Processes	✅	❌	✅	❌	❌	❌	✅	3
Optimal Sample Complexity of Contrastive Learning	❌	❌	✅	✅	❌	✅	✅	4
Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms	✅	❌	✅	❌	✅	❌	✅	4
Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime	❌	❌	❌	❌	❌	❌	✅	1
Optimal transport based adversarial patch to leverage large scale attack transferability	❌	❌	✅	✅	✅	❌	✅	4
Optimistic Bayesian Optimization with Unknown Constraints	✅	✅	✅	❌	❌	❌	❌	3
Oracle Efficient Algorithms for Groupwise Regret	✅	✅	✅	❌	❌	❌	❌	3
Orbit-Equivariant Graph Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Order-Preserving GFlowNets	✅	✅	✅	✅	❌	❌	✅	5
Out-Of-Domain Unlabeled Data Improves Generalization	✅	❌	✅	❌	❌	✅	✅	4
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness	❌	✅	✅	✅	✅	✅	✅	6
Out-of-Distribution Detection with Negative Prompts	✅	✅	✅	✅	✅	✅	✅	7
Out-of-Variable Generalisation for Discriminative Models	✅	✅	❌	❌	❌	❌	✅	3
Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization	❌	❌	✅	❌	❌	❌	✅	2
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization	❌	✅	✅	❌	❌	❌	✅	3
Overthinking the Truth: Understanding how Language Models Process False Demonstrations	❌	✅	✅	❌	❌	❌	❌	2
P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering	✅	✅	✅	❌	✅	❌	✅	5
P2Seg: Pointly-supervised Segmentation via Mutual Distillation	❌	✅	✅	✅	❌	❌	✅	4
PAC Prediction Sets Under Label Shift	✅	✅	✅	✅	❌	❌	✅	5
PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images	✅	✅	✅	✅	✅	✅	✅	7
PAE: Reinforcement Learning from External Knowledge for Efficient Exploration	✅	❌	✅	❌	✅	✅	✅	5
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback	✅	❌	✅	❌	❌	❌	✅	3
PB-LLM: Partially Binarized Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
PBADet: A One-Stage Anchor-Free Approach for Part-Body Association	❌	❌	✅	✅	✅	❌	✅	4
PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction	❌	✅	✅	❌	✅	❌	✅	4
PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation	✅	❌	✅	❌	❌	❌	❌	2
PINNACLE: PINN Adaptive ColLocation and Experimental points selection	✅	✅	✅	❌	✅	❌	✅	5
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
PORF: POSE RESIDUAL FIELD FOR ACCURATE NEURAL SURFACE RECONSTRUCTION	❌	❌	✅	❌	✅	❌	✅	3
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
PRIME: Prioritizing Interpretability in Failure Mode Extraction	❌	❌	✅	✅	❌	❌	✅	3
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation	✅	❌	✅	✅	✅	❌	✅	5
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration	✅	✅	✅	✅	✅	❌	✅	6
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization	❌	❌	✅	✅	✅	❌	✅	4
PanoDiffusion: 360-degree Panorama Outpainting via Diffusion	❌	✅	✅	✅	❌	❌	✅	4
Parallelizing non-linear sequential models over the sequence length	✅	✅	✅	✅	✅	❌	✅	6
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization	✅	❌	✅	✅	✅	✅	✅	6
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization	❌	✅	✅	✅	✅	❌	✅	5
Parametric Augmentation for Time Series Contrastive Learning	✅	✅	✅	❌	✅	✅	✅	6
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution	✅	✅	✅	❌	✅	✅	✅	6
Parsing neural dynamics with infinite recurrent switching linear dynamical systems	✅	✅	✅	❌	✅	❌	✅	5
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models	❌	✅	✅	✅	❌	❌	✅	4
Partitioning Message Passing for Graph Fraud Detection	✅	✅	✅	✅	✅	❌	✅	6
Patched Denoising Diffusion Models For High-Resolution Image Synthesis	❌	✅	✅	❌	❌	❌	✅	3
Path Choice Matters for Clear Attributions in Path Methods	✅	✅	✅	❌	✅	❌	✅	5
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
PeFLL: Personalized Federated Learning by Learning to Learn	✅	✅	✅	✅	❌	❌	✅	5
Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts	✅	✅	✅	❌	❌	❌	✅	4
Perceptual Group Tokenizer: Building Perception with Iterative Grouping	✅	❌	✅	❌	✅	❌	✅	4
Perceptual Scales Predicted by Fisher Information Metrics	❌	✅	❌	❌	❌	❌	✅	2
Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model	❌	✅	❌	❌	❌	❌	❌	1
Periodicity Decoupling Framework for Long-term Series Forecasting	❌	✅	✅	✅	❌	❌	✅	4
Personalize Segment Anything Model with One Shot	❌	✅	✅	✅	✅	❌	✅	5
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement	❌	✅	✅	✅	❌	❌	✅	4
PhyloGFN: Phylogenetic inference with generative flow networks	❌	✅	✅	❌	✅	❌	✅	4
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings	✅	✅	✅	❌	❌	✅	✅	5
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning	✅	❌	✅	❌	✅	❌	✅	4
PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis	❌	✅	✅	❌	✅	❌	✅	4
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning	✅	✅	✅	❌	❌	❌	✅	4
Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks	✅	✅	✅	❌	❌	✅	✅	5
Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents	❌	✅	✅	✅	✅	❌	✅	5
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models	❌	✅	✅	✅	✅	❌	✅	5
Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Plugin estimators for selective classification with out-of-distribution detection	✅	❌	✅	✅	❌	❌	✅	4
PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code	✅	✅	❌	❌	✅	❌	✅	4
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training	❌	✅	✅	❌	✅	✅	✅	5
Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds	❌	✅	✅	✅	✅	❌	✅	5
Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection	❌	✅	✅	❌	❌	❌	✅	3
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Poly-View Contrastive Learning	✅	❌	✅	✅	❌	❌	✅	4
PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters	✅	✅	✅	✅	✅	❌	✅	6
PolyVoice: Language Models for Speech to Speech Translation	❌	❌	✅	❌	✅	❌	✅	3
Polynomial Width is Sufficient for Set Representation with High-dimensional Features	❌	❌	❌	❌	❌	❌	❌	0
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time	✅	✅	✅	✅	✅	❌	✅	6
Pooling Image Datasets with Multiple Covariate Shift and Imbalance	✅	✅	✅	✅	❌	❌	✅	5
Pose Modulated Avatars from Video	❌	✅	✅	❌	✅	❌	✅	4
Post-hoc bias scoring is optimal for fair classification	✅	✅	✅	✅	❌	❌	✅	5
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel	✅	✅	✅	❌	❌	❌	✅	4
Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning	❌	❌	✅	✅	❌	❌	✅	3
Pre-Training and Fine-Tuning Generative Flow Networks	✅	❌	✅	❌	❌	❌	✅	3
Pre-training LiDAR-based 3D Object Detectors through Colorization	❌	✅	✅	✅	❌	❌	✅	4
Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning	❌	❌	✅	✅	✅	❌	✅	4
Pre-training with Random Orthogonal Projection Image Modeling	✅	✅	✅	✅	✅	❌	✅	6
Pre-training with Synthetic Data Helps Offline Reinforcement Learning	❌	❌	✅	❌	✅	❌	✅	3
Predicting Emergent Abilities with Infinite Resolution Evaluation	❌	✅	✅	❌	❌	❌	✅	3
Prediction Error-based Classification for Class-Incremental Learning	✅	✅	✅	✅	✅	❌	✅	6
Prediction without Preclusion: Recourse Verification with Reachable Sets	✅	❌	✅	❌	❌	❌	❌	2
Predictive auxiliary objectives in deep RL mimic learning in the brain	❌	❌	✅	❌	❌	❌	✅	2
Predictive, scalable and interpretable knowledge tracing on structured domains	❌	✅	✅	✅	❌	❌	✅	4
Principled Architecture-aware Scaling of Hyperparameters	❌	✅	✅	❌	❌	❌	✅	3
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting	✅	✅	✅	✅	✅	❌	✅	6
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
Privacy Amplification for Matrix Mechanisms	✅	✅	✅	❌	❌	❌	❌	3
Privacy-Preserving In-Context Learning for Large Language Models	✅	✅	✅	✅	❌	❌	✅	5
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation	✅	✅	✅	❌	❌	❌	✅	4
Private Zeroth-Order Nonsmooth Nonconvex Optimization	✅	❌	❌	❌	❌	❌	❌	1
Privately Aligning Language Models with Reinforcement Learning	✅	❌	✅	✅	❌	❌	✅	4
Privileged Sensing Scaffolds Reinforcement Learning	❌	✅	❌	❌	✅	❌	✅	3
Probabilistic Adaptation of Black-Box Text-to-Video Models	✅	✅	✅	❌	✅	❌	✅	5
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization	❌	✅	✅	✅	✅	❌	✅	5
Probabilistically Rewired Message-Passing Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Procedural Fairness Through Decoupling Objectionable Data Generating Components	✅	✅	✅	❌	❌	❌	✅	4
Progressive Fourier Neural Representation for Sequential Video Compilation	✅	✅	✅	❌	✅	❌	✅	5
Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts	❌	✅	✅	❌	✅	✅	✅	5
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features	✅	❌	✅	✅	❌	❌	✅	4
Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models	❌	✅	✅	❌	✅	❌	✅	4
Prompt Gradient Projection for Continual Learning	✅	✅	✅	❌	✅	❌	✅	5
Prompt Learning with Quaternion Networks	❌	✅	✅	✅	✅	❌	✅	5
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization	✅	✅	✅	✅	❌	❌	✅	5
PromptTTS 2: Describing and Generating Voices with Text Prompt	❌	❌	✅	❌	❌	❌	✅	2
Proper Laplacian Representation Learning	❌	✅	❌	❌	❌	❌	✅	2
Protein Discovery with Discrete Walk-Jump Sampling	✅	✅	✅	✅	❌	✅	✅	6
Protein Multimer Structure Prediction via Prompt Learning	✅	✅	✅	✅	✅	❌	✅	6
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models	✅	✅	✅	❌	✅	❌	✅	5
Protein-ligand binding representation learning from fine-grained interactions	✅	❌	✅	✅	✅	❌	✅	5
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction	❌	✅	✅	✅	✅	❌	✅	5
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes	✅	❌	❌	❌	❌	❌	❌	1
Provable Compositional Generalization for Object-Centric Learning	❌	✅	❌	✅	❌	✅	✅	4
Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Provable Offline Preference-Based Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Provable Reward-Agnostic Preference-Based Reinforcement Learning	✅	❌	❌	❌	❌	❌	❌	1
Provable Robust Watermarking for AI-Generated Text	✅	✅	✅	❌	✅	❌	✅	5
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo	✅	✅	✅	❌	✅	❌	✅	5
Provably Efficient CVaR RL in Low-rank MDPs	✅	❌	❌	❌	❌	❌	❌	1
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback	✅	❌	❌	❌	❌	❌	✅	2
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations	✅	❌	❌	❌	❌	❌	❌	1
Provably Robust Conformal Prediction with Improved Efficiency	❌	✅	✅	✅	✅	❌	✅	5
Proving Test Set Contamination in Black-Box Language Models	✅	✅	✅	❌	✅	❌	✅	5
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Pseudo-Generalized Dynamic View Synthesis from a Video	❌	✅	✅	❌	❌	❌	✅	3
PubDef: Defending Against Transfer Attacks From Public Models	❌	✅	✅	✅	✅	❌	✅	5
Pushing Boundaries: Mixup's Influence on Neural Collapse	❌	❌	✅	❌	❌	❌	✅	2
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning	✅	✅	✅	❌	✅	❌	✅	5
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision	✅	✅	✅	✅	❌	❌	✅	5
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models	✅	✅	✅	❌	✅	❌	✅	5
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Quadratic models for understanding catapult dynamics of neural networks	❌	❌	✅	❌	✅	❌	✅	3
Quality-Diversity through AI Feedback	❌	✅	✅	❌	❌	✅	✅	4
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting	✅	✅	✅	❌	❌	❌	✅	4
Quantifying and Enhancing Multi-modal Robustness with Modality Preference	❌	❌	✅	❌	❌	❌	❌	1
Quantifying the Plausibility of Context Reliance in Neural Machine Translation	✅	✅	✅	✅	❌	❌	✅	5
Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification	❌	❌	❌	❌	❌	❌	❌	0
Quasi-Monte Carlo for 3D Sliced Wasserstein	✅	✅	✅	❌	✅	❌	✅	5
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL	❌	✅	✅	❌	✅	❌	✅	4
Query-Policy Misalignment in Preference-Based Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Querying Easily Flip-flopped Samples for Deep Active Learning	✅	✅	✅	✅	❌	❌	✅	5
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How	✅	✅	✅	✅	✅	❌	✅	6
R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation	❌	✅	✅	❌	❌	❌	✅	3
R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning	❌	✅	✅	✅	✅	✅	✅	6
R-MAE: Regions Meet Masked Autoencoders	❌	✅	✅	✅	❌	❌	✅	4
RA-DIT: Retrieval-Augmented Dual Instruction Tuning	❌	✅	✅	✅	✅	❌	✅	5
RAIN: Your Language Models Can Align Themselves without Finetuning	✅	✅	✅	❌	❌	❌	✅	4
RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering	✅	❌	✅	✅	✅	❌	✅	5
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval	✅	✅	✅	❌	✅	❌	✅	5
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design	❌	✅	✅	✅	✅	✅	✅	6
REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning	✅	✅	✅	✅	❌	❌	✅	5
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations	✅	✅	✅	❌	✅	❌	✅	5
RECOMP: Improving Retrieval-Augmented LMs with Context Compression and Selective Augmentation	✅	✅	✅	✅	✅	❌	✅	6
REFACTOR: Learning to Extract Theorems from Proofs	✅	✅	✅	❌	✅	❌	✅	5
RETSim: Resilient and Efficient Text Similarity	❌	✅	✅	❌	✅	❌	✅	4
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes	❌	❌	✅	❌	❌	❌	✅	2
RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment	❌	✅	✅	✅	❌	❌	✅	4
RLIF: Interactive Imitation Learning as Reinforcement Learning	✅	✅	✅	❌	✅	✅	✅	6
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches	❌	❌	✅	❌	❌	❌	✅	2
RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation	❌	❌	✅	✅	✅	✅	✅	5
Raidar: geneRative AI Detection viA Rewriting	✅	✅	✅	✅	❌	❌	✅	5
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks	❌	❌	✅	❌	❌	❌	✅	2
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection	✅	✅	✅	✅	❌	❌	✅	5
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion	❌	✅	✅	✅	✅	❌	✅	5
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models	❌	❌	✅	✅	✅	❌	✅	4
ReLoRA: High-Rank Training Through Low-Rank Updates	✅	✅	✅	❌	✅	❌	✅	5
ReMasker: Imputing Tabular Data with Masked Autoencoding	✅	✅	✅	❌	❌	❌	✅	4
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation	❌	✅	✅	✅	✅	❌	✅	5
ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift	❌	❌	✅	✅	✅	❌	✅	4
Real-Fake: Effective Training Data Synthesis Through Distribution Matching	❌	✅	✅	❌	❌	✅	✅	4
Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting	❌	❌	✅	❌	❌	❌	✅	2
Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis	❌	❌	✅	✅	✅	❌	✅	4
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments	❌	✅	✅	✅	❌	❌	✅	4
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning	✅	✅	✅	❌	✅	❌	✅	5
Reasoning with Latent Diffusion in Offline Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces	✅	✅	✅	❌	❌	❌	✅	4
Reconciling Spatial and Temporal Abstractions for Goal Representation	✅	✅	✅	❌	❌	✅	✅	5
Recursive Generalization Transformer for Image Super-Resolution	❌	✅	✅	❌	✅	❌	✅	4
Reinforcement Symbolic Regression Machine	✅	✅	✅	✅	❌	❌	✅	5
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization	✅	✅	✅	❌	✅	❌	✅	5
Relay Diffusion: Unifying diffusion process across resolutions for image synthesis	✅	✅	✅	❌	✅	❌	✅	5
Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment	❌	✅	✅	✅	❌	❌	✅	4
Removing Biases from Molecular Representations via Information Maximization	❌	✅	✅	❌	❌	❌	✅	3
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning	✅	✅	✅	❌	✅	❌	✅	5
Repelling Random Walks	✅	✅	✅	❌	❌	❌	✅	4
Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models	❌	✅	✅	✅	❌	❌	✅	4
Replay across Experiments: A Natural Extension of Off-Policy RL	❌	❌	✅	❌	❌	❌	✅	2
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems	❌	✅	✅	❌	❌	❌	✅	3
Representation Deficiency in Masked Language Modeling	❌	✅	✅	✅	✅	❌	✅	5
ResFields: Residual Neural Fields for Spatiotemporal Signals	❌	✅	✅	✅	✅	✅	✅	6
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition	✅	❌	✅	✅	❌	❌	✅	4
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL	✅	✅	✅	❌	❌	❌	✅	4
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective	✅	✅	✅	❌	❌	❌	✅	4
Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework	✅	✅	✅	✅	✅	✅	✅	7
Rethinking CNN’s Generalization to Backdoor Attack from Frequency Domain	❌	❌	✅	❌	❌	❌	✅	2
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators	❌	✅	✅	✅	✅	❌	✅	5
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models	✅	✅	✅	✅	✅	❌	✅	6
Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors	✅	✅	✅	✅	❌	❌	✅	5
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds	❌	✅	✅	✅	✅	❌	✅	5
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks	❌	✅	✅	✅	✅	❌	✅	5
Rethinking Model Ensemble in Transfer-based Adversarial Attacks	✅	✅	✅	❌	❌	❌	✅	4
Rethinking and Extending the Probabilistic Inference Capacity of GNNs	✅	❌	✅	✅	❌	❌	✅	4
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability	❌	✅	✅	✅	✅	❌	✅	5
Rethinking the Uniformity Metric in Self-Supervised Learning	❌	✅	✅	✅	✅	❌	✅	5
Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms	✅	❌	✅	❌	✅	❌	✅	4
Retrieval is Accurate Generation	❌	❌	✅	✅	✅	❌	✅	4
Retrieval meets Long Context Large Language Models	❌	❌	✅	✅	❌	❌	✅	3
Retrieval-Enhanced Contrastive Vision-Text Models	❌	❌	✅	❌	✅	❌	✅	3
Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization	✅	❌	✅	✅	✅	❌	✅	5
Retrieval-based Disentangled Representation Learning with Natural Language Supervision	✅	✅	✅	❌	✅	❌	✅	5
Retro-fallback: retrosynthetic planning in an uncertain world	✅	✅	✅	❌	❌	❌	✅	4
RetroBridge: Modeling Retrosynthesis with Markov Bridges	✅	✅	✅	✅	✅	❌	✅	6
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization	✅	✅	✅	✅	✅	❌	✅	6
Reverse Diffusion Monte Carlo	✅	❌	❌	❌	❌	❌	✅	2
Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency	❌	✅	✅	❌	✅	❌	✅	4
Revisit and Outstrip Entity Alignment: A Perspective of Generative Models	✅	✅	✅	✅	✅	❌	✅	6
Revisiting Data Augmentation in Deep Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation	✅	✅	✅	✅	✅	❌	✅	6
Revisiting Link Prediction: a data perspective	❌	✅	✅	✅	✅	✅	✅	6
Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages	✅	✅	✅	❌	❌	❌	✅	4
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods	✅	❌	❌	❌	❌	❌	❌	1
Reward Design for Justifiable Sequential Decision-Making	❌	✅	✅	✅	❌	❌	✅	4
Reward Model Ensembles Help Mitigate Overoptimization	❌	✅	✅	✅	✅	❌	✅	5
Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning	✅	✅	✅	✅	✅	❌	✅	6
Reward-Free Curricula for Training Robust World Models	✅	✅	✅	❌	✅	✅	✅	6
Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction	❌	✅	✅	✅	✅	❌	✅	5
Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?	❌	✅	✅	❌	❌	❌	✅	3
RingAttention with Blockwise Transformers for Near-Infinite Context	✅	✅	✅	❌	✅	❌	✅	5
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression	❌	❌	❌	❌	❌	❌	✅	1
Robot Fleet Learning via Policy Merging	✅	✅	✅	❌	❌	❌	✅	4
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula	✅	✅	✅	❌	✅	❌	✅	5
Robust Angular Synchronization via Directed Graph Neural Networks	✅	✅	✅	❌	✅	❌	✅	5
Robust Classification via Regression for Learning with Noisy Labels	❌	✅	✅	✅	❌	❌	✅	4
Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control	✅	❌	✅	❌	❌	❌	✅	3
Robust Model-Based Optimization for Challenging Fitness Landscapes	❌	✅	✅	❌	❌	❌	✅	3
Robust NAS under adversarial training: benchmark, theory, and beyond	✅	❌	✅	❌	✅	❌	✅	4
Robust Similarity Learning with Difference Alignment Regularization	✅	❌	✅	✅	✅	❌	✅	5
Robust Training of Federated Models with Extremely Label Deficiency	✅	✅	✅	✅	❌	❌	✅	5
Robust agents learn causal world models	✅	❌	❌	❌	❌	❌	❌	1
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies	✅	✅	✅	❌	✅	❌	✅	5
Robustifying State-space Models for Long Sequences via Approximate Diagonalization	❌	❌	✅	❌	❌	❌	✅	2
Robustifying and Boosting Training-Free Neural Architecture Search	✅	✅	✅	✅	✅	❌	✅	6
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks	✅	✅	✅	✅	❌	❌	✅	5
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs	✅	❌	✅	❌	❌	❌	✅	3
Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification	❌	❌	✅	❌	❌	❌	✅	2
S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic	✅	✅	✅	❌	❌	❌	✅	4
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation	✅	❌	✅	❌	❌	❌	✅	3
SALMON: Self-Alignment with Instructable Reward Models	❌	✅	✅	❌	❌	❌	✅	3
SALMONN: Towards Generic Hearing Abilities for Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer	✅	✅	✅	❌	❌	❌	✅	4
SAS: Structured Activation Sparsification	✅	✅	✅	❌	✅	❌	✅	5
SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos	❌	✅	✅	❌	✅	❌	✅	4
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis	✅	❌	✅	❌	❌	❌	✅	3
SE(3)-Stochastic Flow Matching for Protein Backbone Generation	✅	✅	✅	❌	✅	❌	✅	5
SEA: Sparse Linear Attention with Estimated Attention Mask	❌	✅	✅	❌	✅	✅	✅	5
SEABO: A Simple Search-Based Method for Offline Imitation Learning	✅	✅	✅	❌	✅	✅	✅	6
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution	✅	✅	✅	✅	❌	❌	✅	5
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases	❌	❌	✅	✅	✅	❌	✅	4
SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction	❌	✅	✅	❌	❌	❌	✅	3
SEPT: Towards Efficient Scene Representation Learning for Motion Prediction	❌	❌	✅	✅	✅	❌	✅	4
SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation	✅	✅	✅	❌	✅	❌	✅	5
SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem	❌	❌	❌	❌	❌	❌	❌	0
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore	❌	❌	✅	✅	✅	❌	✅	4
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models	❌	❌	✅	❌	✅	❌	✅	3
SLiMe: Segment Like Me	❌	✅	✅	✅	❌	✅	✅	5
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training	❌	✅	✅	❌	❌	❌	✅	3
SOHES: Self-supervised Open-world Hierarchical Entity Segmentation	❌	❌	✅	❌	✅	❌	✅	3
SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models	❌	❌	✅	❌	✅	❌	✅	3
SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents	❌	✅	✅	❌	❌	✅	✅	4
SPDER: Semiperiodic Damping-Enabled Object Representation	❌	✅	✅	❌	✅	❌	✅	4
SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning	❌	✅	✅	✅	✅	❌	✅	5
SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores	✅	✅	✅	❌	✅	✅	✅	6
STARC: A General Framework For Quantifying Differences Between Reward Functions	❌	❌	❌	❌	✅	❌	❌	1
STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models	✅	❌	✅	❌	❌	❌	✅	3
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction	✅	✅	✅	✅	❌	❌	✅	5
SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS	✅	✅	✅	✅	✅	❌	✅	6
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning	✅	✅	✅	❌	✅	❌	✅	5
SWE-bench: Can Language Models Resolve Real-world Github Issues?	❌	✅	✅	✅	✅	❌	✅	5
SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning	✅	✅	✅	❌	✅	❌	✅	5
SaNN: Simple Yet Powerful Simplicial-aware Neural Networks	❌	❌	✅	✅	❌	❌	✅	3
SaProt: Protein Language Modeling with Structure-aware Vocabulary	❌	✅	✅	✅	✅	❌	✅	5
Safe Collaborative Filtering	✅	✅	✅	✅	✅	❌	✅	6
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model	✅	✅	✅	❌	✅	❌	✅	5
Safe RLHF: Safe Reinforcement Learning from Human Feedback	❌	✅	✅	❌	✅	✅	✅	5
Safe and Robust Watermark Injection with a Single OoD Image	❌	✅	✅	❌	❌	❌	✅	3
SafeDreamer: Safe Reinforcement Learning with World Models	✅	✅	✅	❌	✅	✅	✅	6
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions	❌	✅	✅	✅	✅	❌	✅	5
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation	✅	✅	✅	✅	❌	❌	✅	5
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks	✅	❌	✅	❌	❌	❌	✅	3
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity	✅	❌	❌	❌	❌	❌	❌	1
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight	✅	❌	❌	❌	❌	❌	❌	1
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data	✅	❌	❌	❌	❌	❌	✅	2
Sample-Efficient Multi-Agent RL: An Optimization Perspective	✅	❌	❌	❌	❌	❌	❌	1
Sample-Efficient Quality-Diversity by Cooperative Coevolution	✅	✅	✅	❌	✅	❌	✅	5
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation	✅	❌	❌	❌	❌	❌	❌	1
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization	❌	❌	❌	❌	❌	❌	✅	1
Scalable Diffusion for Materials Generation	❌	✅	✅	✅	✅	❌	✅	5
Scalable Language Model with Generalized Continual Learning	✅	✅	✅	✅	✅	❌	✅	6
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing	✅	✅	✅	✅	✅	❌	✅	6
Scalable Monotonic Neural Networks	❌	✅	✅	✅	✅	✅	✅	6
Scalable Neural Network Kernels	❌	✅	✅	✅	✅	❌	✅	5
Scalable and Effective Implicit Graph Neural Networks on Large Graphs	✅	❌	✅	✅	✅	❌	✅	5
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis	❌	✅	✅	✅	✅	❌	✅	5
ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models	❌	❌	✅	❌	✅	❌	✅	3
Scaling Convex Neural Networks with Burer-Monteiro Factorization	❌	❌	✅	❌	✅	❌	✅	3
Scaling Laws for Associative Memories	❌	❌	❌	❌	❌	❌	✅	1
Scaling Laws for Sparsely-Connected Foundation Models	✅	✅	✅	❌	❌	❌	✅	4
Scaling Laws of RoPE-based Extrapolation	❌	✅	✅	❌	✅	❌	✅	4
Scaling Supervised Local Learning with Augmented Auxiliary Networks	❌	✅	✅	✅	✅	❌	✅	5
Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement	❌	✅	✅	✅	❌	❌	✅	4
Scaling physics-informed hard constraints with mixture-of-experts	❌	✅	✅	❌	✅	❌	✅	4
Score Models for Offline Goal-Conditioned Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Score Regularized Policy Optimization through Diffusion Behavior	✅	✅	✅	✅	✅	❌	✅	6
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions	❌	❌	❌	❌	❌	❌	❌	0
Searching for High-Value Molecules Using Reinforcement Learning and Transformers	❌	❌	✅	❌	✅	✅	✅	4
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective	❌	✅	✅	❌	❌	❌	✅	3
Seer: Language Instructed Video Prediction with Latent Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
Select to Perfect: Imitating desired behavior from large multi-agent data	❌	✅	✅	❌	✅	❌	✅	4
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives	✅	✅	✅	✅	✅	❌	✅	6
Selective Visual Representations Improve Convergence and Generalization for Embodied AI	❌	✅	✅	✅	✅	❌	✅	5
Self-Alignment with Instruction Backtranslation	❌	❌	✅	❌	❌	❌	✅	2
Self-Consuming Generative Models Go MAD	❌	❌	✅	❌	❌	❌	✅	2
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning	✅	✅	✅	✅	❌	❌	✅	5
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection	✅	✅	✅	✅	✅	❌	✅	6
Self-Supervised Contrastive Learning for Long-term Forecasting	✅	✅	✅	✅	❌	❌	✅	5
Self-Supervised Dataset Distillation for Transfer Learning	✅	✅	✅	❌	❌	❌	✅	4
Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View	✅	✅	✅	❌	❌	❌	✅	4
Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes	❌	✅	✅	❌	❌	❌	✅	3
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech	❌	❌	✅	✅	❌	❌	✅	3
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation	✅	✅	✅	✅	✅	❌	✅	6
Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment	✅	✅	✅	✅	✅	❌	✅	6
Self-supervised Representation Learning from Random Data Projectors	✅	✅	✅	❌	✅	❌	✅	5
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning	❌	❌	✅	❌	❌	✅	✅	3
Semantic Flow: Learning Semantic Fields of Dynamic Scenes from Monocular Videos	❌	✅	✅	❌	✅	❌	✅	4
SemiReward: A General Reward Model for Semi-supervised Learning	✅	✅	✅	✅	✅	❌	✅	6
Sentence-level Prompts Benefit Composed Image Retrieval	❌	✅	✅	✅	✅	❌	✅	5
Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation	✅	❌	✅	❌	✅	❌	✅	4
Separating common from salient patterns with Contrastive Representation Learning	❌	✅	✅	✅	❌	❌	✅	4
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking	✅	❌	✅	✅	✅	❌	✅	5
Set Learning for Accurate and Calibrated Models	✅	✅	✅	✅	✅	❌	✅	6
SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings	✅	❌	✅	✅	❌	❌	✅	4
Shadow Cones: A Generalized Framework for Partial Order Embeddings	❌	✅	✅	✅	❌	❌	✅	4
Sharpness-Aware Data Poisoning Attack	✅	✅	✅	❌	❌	❌	✅	4
Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning	✅	❌	✅	✅	❌	❌	✅	4
Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning	✅	✅	✅	✅	✅	❌	✅	6
Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation	❌	❌	✅	❌	✅	❌	✅	3
Simple Hierarchical Planning with Diffusion	✅	❌	✅	✅	✅	❌	✅	5
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity	✅	❌	✅	✅	❌	❌	✅	4
Simplicial Representation Learning with Neural $k$-Forms	✅	✅	✅	✅	❌	❌	✅	5
Simplifying Transformer Blocks	❌	✅	✅	✅	✅	❌	✅	5
Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape	❌	✅	✅	❌	✅	❌	✅	4
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations	❌	✅	✅	✅	✅	❌	✅	5
Single Motion Diffusion	❌	✅	✅	❌	✅	❌	✅	4
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation	❌	✅	✅	❌	✅	✅	✅	5
Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Skill or Luck? Return Decomposition via Advantage Functions	✅	❌	✅	❌	✅	❌	✅	4
Skip-Attention: Improving Vision Transformers by Paying Less Attention	❌	✅	✅	✅	✅	❌	✅	5
SliceGPT: Compress Large Language Models by Deleting Rows and Columns	✅	✅	✅	❌	✅	✅	✅	6
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method	✅	✅	✅	✅	✅	✅	✅	7
Sliced Wasserstein Estimation with Control Variates	✅	✅	✅	❌	✅	❌	✅	5
Small-scale proxies for large-scale Transformer training instabilities	❌	❌	✅	❌	✅	❌	✅	3
SmartPlay : A Benchmark for LLMs as Intelligent Agents	❌	✅	✅	❌	❌	❌	✅	3
Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing	✅	✅	✅	✅	❌	❌	✅	5
Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community	❌	✅	❌	✅	✅	❌	✅	4
Social-Transmotion: Promptable Human Trajectory Prediction	❌	✅	✅	✅	✅	❌	✅	5
SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series	❌	✅	✅	❌	❌	❌	✅	3
Soft Contrastive Learning for Time Series	❌	✅	✅	✅	❌	❌	✅	4
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models	✅	✅	✅	❌	❌	❌	❌	3
Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity	✅	❌	❌	❌	❌	❌	❌	1
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification	❌	❌	✅	❌	❌	❌	✅	2
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution	❌	❌	✅	❌	✅	❌	✅	3
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes	❌	✅	❌	❌	✅	❌	✅	3
Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution	❌	❌	✅	❌	✅	❌	✅	3
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency	✅	✅	✅	✅	✅	❌	✅	6
Some Fundamental Aspects about Lipschitz Continuity of Neural Networks	❌	✅	✅	✅	❌	❌	✅	4
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training	✅	❌	✅	✅	✅	❌	✅	5
Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation	❌	❌	✅	❌	✅	❌	✅	3
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression	✅	❌	✅	❌	✅	❌	✅	4
SpaCE: The Spatial Confounding Environment	✅	✅	✅	✅	✅	✅	✅	7
Space Group Constrained Crystal Generation	❌	✅	✅	✅	❌	❌	✅	4
Space and time continuous physics simulation from partial observations	❌	❌	✅	✅	❌	❌	✅	3
Sparse Autoencoders Find Highly Interpretable Features in Language Models	❌	✅	✅	❌	✅	❌	✅	4
Sparse MoE with Language Guided Routing for Multilingual Machine Translation	✅	✅	✅	✅	✅	✅	✅	7
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging	✅	✅	✅	✅	❌	❌	✅	5
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN	✅	❌	✅	✅	❌	❌	✅	4
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning	✅	✅	✅	✅	✅	✅	✅	7
SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation	❌	✅	✅	❌	✅	❌	✅	4
SparseFormer: Sparse Visual Recognition via Limited Latent Tokens	❌	✅	✅	✅	✅	❌	✅	5
Sparsistency for inverse optimal transport	❌	✅	❌	❌	❌	❌	✅	2
Spatially-Aware Transformers for Embodied Agents	✅	✅	✅	❌	✅	❌	✅	5
Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers	✅	✅	✅	❌	❌	❌	✅	4
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation	✅	✅	✅	❌	✅	❌	✅	5
Spectrally Transformed Kernel Regression	✅	✅	✅	✅	❌	❌	✅	5
SpeechTokenizer: Unified Speech Tokenizer for Speech Language Models	❌	✅	✅	✅	✅	❌	✅	5
Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips	❌	✅	✅	✅	❌	❌	✅	4
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition	✅	❌	✅	✅	✅	✅	✅	6
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM	❌	❌	✅	❌	✅	❌	✅	3
Spurious Feature Diversification Improves Out-of-distribution Generalization	❌	❌	✅	❌	❌	❌	✅	2
Stabilizing Backpropagation Through Time to Learn Complex Physics	❌	✅	❌	❌	❌	❌	✅	2
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data	❌	✅	✅	❌	✅	❌	✅	4
Stable Anisotropic Regularization	✅	✅	✅	✅	✅	❌	✅	6
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data	✅	✅	✅	✅	✅	❌	✅	6
Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns	✅	✅	✅	✅	✅	❌	✅	6
State Representation Learning Using an Unbalanced Atlas	✅	✅	✅	❌	✅	✅	✅	6
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts	❌	❌	❌	❌	❌	❌	✅	1
Statistical Rejection Sampling Improves Preference Optimization	✅	❌	✅	✅	❌	❌	✅	4
Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming	✅	❌	✅	❌	❌	❌	✅	3
Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds	❌	✅	✅	❌	❌	❌	❌	2
Stochastic Controlled Averaging for Federated Learning with Communication Compression	✅	❌	✅	❌	❌	❌	✅	3
Stochastic Gradient Descent for Gaussian Processes Done Right	✅	✅	✅	✅	✅	✅	✅	7
Stochastic Modified Equations and Dynamics of Dropout Algorithm	❌	❌	✅	❌	❌	❌	✅	2
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling	✅	✅	✅	❌	✅	❌	✅	5
Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects	❌	✅	✅	❌	✅	❌	✅	4
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning	❌	✅	✅	❌	✅	❌	✅	4
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability	✅	❌	✅	❌	❌	❌	❌	2
Structural Fairness-aware Active Learning for Graph Neural Networks	✅	✅	✅	❌	❌	❌	✅	4
Structural Inference with Dynamics Encoding and Partial Correlation Coefficients	✅	✅	✅	✅	✅	❌	✅	6
Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding	❌	❌	✅	✅	✅	❌	✅	4
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning	✅	✅	✅	❌	✅	❌	✅	5
Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets	✅	✅	✅	❌	❌	❌	✅	4
SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs	✅	✅	✅	✅	❌	✅	✅	6
Submodular Reinforcement Learning	✅	✅	✅	❌	❌	❌	✅	4
Subtractive Mixture Models via Squaring: Representation and Learning	✅	✅	✅	✅	✅	❌	✅	6
Successor Heads: Recurring, Interpretable Attention Heads In The Wild	❌	❌	✅	✅	❌	❌	✅	3
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs	❌	❌	✅	❌	✅	✅	✅	4
Sufficient conditions for offline reactivation in recurrent neural networks	❌	✅	❌	❌	❌	✅	✅	3
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs	✅	✅	✅	✅	✅	✅	✅	7
Supervised Knowledge Makes Large Language Models Better In-context Learners	✅	✅	✅	✅	❌	❌	❌	4
SweetDreamer: Aligning Geometric Priors in 2D diffusion for Consistent Text-to-3D	❌	✅	✅	❌	✅	✅	✅	5
Symbol as Points: Panoptic Symbol Spotting via Point-based Representation	❌	✅	✅	❌	✅	❌	✅	4
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics	❌	✅	✅	✅	✅	❌	✅	5
Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems	✅	❌	❌	❌	❌	❌	✅	2
Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching	✅	❌	✅	❌	✅	❌	✅	4
Symmetric Single Index Learning	❌	❌	❌	❌	❌	❌	✅	1
Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation	✅	✅	✅	✅	✅	❌	✅	6
Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control	❌	✅	✅	❌	❌	✅	✅	4
Synaptic Weight Distributions Depend on the Geometry of Plasticity	❌	✅	✅	✅	✅	❌	✅	5
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image	❌	❌	✅	❌	✅	❌	✅	3
Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance	✅	✅	✅	❌	✅	✅	✅	6
T-MARS: Improving Visual Representations by Circumventing Text Feature Learning	✅	❌	✅	❌	✅	❌	✅	4
T-Rep: Representation Learning for Time Series using Time-Embeddings	❌	✅	✅	✅	✅	✅	✅	6
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series	❌	✅	✅	✅	✅	❌	✅	5
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models	❌	❌	✅	✅	✅	✅	✅	5
TD-MPC2: Scalable, Robust World Models for Continuous Control	❌	✅	✅	❌	✅	❌	✅	4
TEDDY: Trimming Edges with Degree-based Discrimination Strategy	✅	✅	✅	✅	✅	❌	✅	6
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series	✅	✅	✅	❌	✅	❌	✅	5
TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts	❌	✅	✅	✅	✅	❌	✅	5
THOUGHT PROPAGATION: AN ANALOGICAL APPROACH TO COMPLEX REASONING WITH LARGE LANGUAGE MODELS	✅	✅	✅	❌	❌	❌	❌	3
TOSS: High-quality Text-guided Novel View Synthesis from a Single Image	❌	❌	✅	✅	✅	✅	✅	5
TRAM: Bridging Trust Regions and Sharpness Aware Minimization	✅	✅	✅	✅	✅	❌	✅	6
TUVF: Learning Generalizable Texture UV Radiance Fields	✅	✅	✅	❌	✅	✅	✅	6
TabR: Tabular Deep Learning Meets Nearest Neighbors	❌	✅	✅	✅	✅	❌	✅	5
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration	✅	❌	✅	✅	✅	❌	✅	5
Tag2Text: Guiding Vision-Language Model via Image Tagging	❌	✅	✅	✅	✅	❌	✅	5
Tailoring Self-Rationalizers with Multi-Reward Distillation	❌	✅	✅	✅	✅	❌	✅	5
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models	❌	❌	✅	✅	❌	❌	✅	3
Talk like a Graph: Encoding Graphs for Large Language Models	❌	❌	✅	❌	✅	✅	✅	4
Tangent Transformers for Composition,Privacy and Removal	❌	✅	✅	❌	❌	❌	✅	3
TapMo: Shape-aware Motion Generation of Skeleton-free Characters	❌	❌	✅	✅	❌	❌	✅	3
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning	✅	❌	❌	❌	❌	❌	✅	2
Task Planning for Visual Room Rearrangement under Partial Observability	✅	❌	✅	✅	❌	❌	✅	4
Task structure and nonlinearity jointly determine learned representational geometry	❌	❌	✅	❌	❌	❌	❌	1
Teach LLMs to Phish: Stealing Private Information from Language Models	❌	❌	✅	❌	✅	❌	✅	3
Teaching Arithmetic to Small Transformers	✅	✅	✅	✅	✅	✅	✅	7
Teaching Language Models to Hallucinate Less with Synthetic Tasks	❌	❌	✅	✅	✅	❌	✅	4
Teaching Large Language Models to Self-Debug	❌	❌	✅	✅	❌	❌	✅	3
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs	✅	✅	✅	✅	✅	❌	✅	6
Temporal Generalization Estimation in Evolving Graphs	✅	❌	✅	❌	✅	❌	✅	4
Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks	✅	❌	✅	❌	❌	❌	✅	3
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game	❌	✅	✅	✅	❌	✅	✅	5
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models	❌	✅	✅	✅	✅	❌	✅	5
Test-Time Training on Nearest Neighbors for Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Test-time Adaptation against Multi-modal Reliability Bias	❌	✅	✅	❌	✅	❌	✅	4
Text-to-3D with Classifier Score Distillation	❌	✅	✅	❌	✅	❌	✅	4
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning	❌	❌	✅	❌	✅	✅	✅	4
TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields	❌	❌	✅	✅	✅	❌	✅	4
The Alignment Problem from a Deep Learning Perspective	❌	❌	✅	❌	❌	✅	✅	3
The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World	✅	✅	✅	❌	✅	❌	✅	5
The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing	✅	✅	✅	✅	✅	❌	✅	6
The Consensus Game: Language Model Generation via Equilibrium Search	❌	❌	✅	❌	❌	❌	✅	2
The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning	✅	❌	✅	✅	✅	❌	✅	5
The Curse of Diversity in Ensemble-Based Exploration	✅	✅	✅	❌	✅	✅	✅	6
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models	❌	✅	❌	❌	❌	❌	❌	1
The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models	✅	✅	✅	✅	✅	❌	✅	6
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images	❌	✅	✅	❌	❌	❌	✅	3
The Effective Horizon Explains Deep RL Performance in Stochastic Environments	✅	✅	✅	❌	❌	❌	✅	4
The Effectiveness of Random Forgetting for Robust Generalization	✅	✅	✅	✅	✅	❌	✅	6
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.	❌	✅	✅	✅	✅	✅	✅	6
The Expressive Power of Low-Rank Adaptation	❌	✅	✅	✅	✅	❌	✅	5
The Expressive Power of Transformers with Chain of Thought	❌	❌	❌	❌	❌	❌	❌	0
The False Promise of Imitating Proprietary Language Models	❌	✅	✅	❌	✅	❌	✅	4
The Generalization Gap in Offline Reinforcement Learning	❌	✅	✅	✅	✅	❌	✅	5
The Generative AI Paradox: “What It Can Create, It May Not Understand”	❌	❌	✅	❌	❌	❌	✅	2
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry	✅	❌	✅	✅	✅	❌	✅	5
The Hidden Language of Diffusion Models	❌	✅	✅	✅	✅	❌	✅	5
The Human-AI Substitution game: active learning from a strategic labeler	✅	❌	❌	❌	❌	❌	✅	2
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model	✅	❌	✅	❌	❌	❌	✅	3
The LLM Surgeon	✅	✅	✅	❌	❌	❌	✅	4
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing	✅	❌	✅	❌	✅	❌	✅	4
The Marginal Value of Momentum for Small Learning Rate SGD	❌	❌	✅	✅	❌	❌	✅	3
The Need for Speed: Pruning Transformers with One Recipe	✅	✅	✅	❌	✅	❌	✅	5
The Reasonableness Behind Unreasonable Translation Capability of Large Language Model	❌	✅	✅	✅	✅	❌	✅	5
The Reversal Curse: LLMs trained on “A is B” fail to learn “B is A”	❌	✅	❌	❌	✅	❌	✅	3
The Trickle-down Impact of Reward Inconsistency on RLHF	✅	❌	✅	✅	❌	❌	✅	4
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction	❌	✅	✅	✅	✅	❌	✅	5
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning	❌	✅	✅	❌	❌	❌	✅	3
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric	✅	✅	✅	✅	✅	❌	✅	6
The Update-Equivalence Framework for Decision-Time Planning	✅	❌	✅	❌	❌	❌	✅	3
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models	✅	✅	✅	❌	✅	❌	✅	5
The importance of feature preprocessing for differentially private linear optimization	✅	❌	✅	❌	❌	❌	✅	3
The mechanistic basis of data dependence and abrupt learning in an in-context classification task	❌	❌	✅	❌	❌	❌	✅	2
The optimality of kernel classifiers in Sobolev space	❌	❌	✅	❌	❌	❌	✅	2
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach	✅	✅	✅	✅	❌	❌	✅	5
Theoretical Understanding of Learning from Adversarial Perturbations	❌	✅	✅	❌	✅	❌	✅	4
Thin-Shell Object Manipulations With Differentiable Physics Simulations	❌	❌	❌	❌	✅	✅	✅	3
Think before you speak: Training Language Models With Pause Tokens	✅	❌	✅	❌	❌	❌	✅	3
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph	✅	✅	✅	❌	✅	❌	✅	5
Threaten Spiking Neural Networks through Combining Rate and Temporal Information	✅	✅	✅	❌	❌	❌	✅	4
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning	✅	❌	✅	✅	✅	❌	✅	5
TiC-CLIP: Continual Training of CLIP Models	❌	✅	✅	❌	❌	❌	✅	3
Tight Rates in Supervised Outlier Transfer Learning	❌	❌	❌	❌	❌	❌	❌	0
Time Fairness in Online Knapsack Problems	❌	✅	❌	❌	❌	❌	✅	2
Time Travel in LLMs: Tracing Data Contamination in Large Language Models	❌	✅	✅	✅	❌	✅	✅	5
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies	✅	✅	✅	❌	❌	❌	❌	3
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models	❌	✅	✅	✅	✅	❌	✅	5
Time-Varying Propensity Score to Bridge the Gap between the Past and Present	✅	❌	✅	✅	✅	✅	✅	6
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting	❌	✅	✅	✅	✅	❌	✅	5
To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets	❌	✅	❌	❌	✅	❌	✅	3
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination	❌	✅	✅	❌	❌	❌	❌	2
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving	✅	✅	✅	❌	❌	❌	✅	4
TokenFlow: Consistent Diffusion Features for Consistent Video Editing	✅	❌	✅	❌	❌	❌	✅	3
Tool-Augmented Reward Modeling	❌	✅	✅	❌	✅	❌	✅	4
ToolChain: Efficient Action Space Navigation in Large Language Models with A Search	✅	❌	✅	❌	✅	✅	✅	5
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs	❌	✅	✅	❌	❌	❌	✅	3
Topic Modeling as Multi-Objective Contrastive Optimization	✅	❌	✅	❌	❌	❌	✅	3
TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning	❌	✅	✅	❌	✅	❌	✅	4
Topological data analysis on noisy quantum computers	✅	❌	❌	✅	✅	❌	✅	4
TorchRL: A data-driven decision-making library for PyTorch	❌	✅	✅	❌	✅	✅	✅	5
Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games	✅	✅	✅	❌	✅	✅	✅	6
Toward Student-oriented Teacher Network Training for Knowledge Distillation	❌	❌	✅	❌	❌	❌	✅	2
Toward effective protection against diffusion-based mimicry through score distillation	✅	✅	✅	❌	✅	❌	✅	5
Towards 3D Molecule-Text Interpretation in Language Models	❌	✅	✅	✅	✅	❌	✅	5
Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints	❌	✅	✅	✅	❌	❌	✅	4
Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation	❌	✅	✅	❌	✅	✅	✅	5
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods	❌	❌	✅	❌	❌	❌	✅	2
Towards Category Unification of 3D Single Object Tracking on Point Clouds	❌	❌	✅	❌	✅	❌	✅	3
Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models	❌	✅	✅	✅	❌	❌	✅	4
Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators	❌	❌	✅	✅	✅	❌	✅	4
Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs	✅	✅	✅	❌	❌	❌	✅	4
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning	❌	❌	❌	✅	✅	✅	✅	4
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations	❌	✅	✅	✅	❌	❌	✅	4
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks	✅	✅	✅	❌	❌	❌	✅	4
Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework	✅	✅	✅	❌	❌	❌	✅	4
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach	✅	✅	✅	✅	✅	✅	✅	7
Towards Establishing Guaranteed Error for Learned Database Operations	❌	❌	❌	❌	❌	❌	❌	0
Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery	✅	✅	✅	✅	❌	❌	✅	5
Towards Faithful XAI Evaluation via Generalization-Limited Backdoor Watermark	✅	✅	✅	❌	✅	❌	✅	5
Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning	✅	✅	✅	✅	❌	❌	✅	5
Towards Foundation Models for Knowledge Graph Reasoning	❌	✅	✅	✅	✅	❌	✅	5
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets	❌	✅	✅	✅	✅	❌	✅	5
Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection	❌	✅	✅	✅	✅	❌	✅	5
Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation	❌	❌	✅	❌	❌	❌	✅	2
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach	❌	✅	✅	❌	✅	❌	✅	4
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach	✅	❌	✅	✅	✅	✅	✅	6
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark	❌	❌	✅	❌	❌	❌	✅	2
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching	✅	✅	✅	✅	✅	❌	✅	6
Towards Meta-Pruning via Optimal Transport	✅	✅	✅	✅	❌	❌	✅	5
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models	❌	❌	❌	❌	❌	❌	❌	0
Towards Offline Opponent Modeling with In-context Learning	✅	❌	✅	❌	❌	❌	✅	3
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection	❌	✅	✅	✅	✅	❌	✅	5
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback	✅	❌	❌	❌	❌	❌	❌	1
Towards Poisoning Fair Representations	✅	❌	✅	❌	❌	❌	✅	3
Towards Principled Representation Learning from Videos for Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features	✅	✅	✅	❌	✅	❌	✅	5
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks	✅	✅	✅	✅	✅	✅	✅	7
Towards Robust Multi-Modal Reasoning via Model Selection	❌	✅	✅	✅	❌	❌	✅	4
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption	✅	✅	✅	❌	❌	❌	✅	4
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness	✅	❌	✅	❌	❌	❌	✅	3
Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation	✅	✅	✅	❌	✅	❌	✅	5
Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition	❌	✅	✅	✅	✅	❌	✅	5
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion	❌	✅	✅	❌	❌	❌	✅	3
Towards Transparent Time Series Forecasting	✅	✅	✅	✅	✅	❌	✅	6
Towards Understanding Factual Knowledge of Large Language Models	❌	✅	✅	❌	❌	❌	❌	2
Towards Understanding Sycophancy in Language Models	❌	✅	✅	✅	❌	❌	✅	4
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond	❌	❌	✅	✅	✅	❌	✅	4
Towards a statistical theory of data selection under weak supervision	❌	✅	✅	✅	❌	❌	✅	4
Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization	✅	❌	✅	✅	✅	❌	✅	5
Towards image compression with perfect realism at ultra-low bitrates	❌	❌	✅	✅	✅	❌	✅	4
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains	❌	❌	❌	❌	❌	❌	✅	1
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy	✅	❌	✅	❌	❌	❌	✅	3
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks	✅	✅	✅	✅	✅	❌	✅	6
Training Bayesian Neural Networks with Sparse Subspace Variational Inference	✅	✅	✅	❌	❌	❌	✅	4
Training Diffusion Models with Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Training Graph Transformers via Curriculum-Enhanced Attention Distillation	❌	❌	✅	✅	✅	❌	✅	4
Training Socially Aligned Language Models on Simulated Social Interactions	✅	✅	✅	❌	✅	❌	✅	5
Training Unbiased Diffusion Models From Biased Dataset	✅	✅	✅	❌	✅	❌	✅	5
Training-free Multi-objective Diffusion Model for 3D Molecule Generation	✅	❌	✅	✅	❌	❌	✅	4
Trajeglish: Traffic Modeling as Next-Token Prediction	✅	❌	✅	✅	✅	❌	✅	5
Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets	❌	✅	✅	✅	✅	❌	✅	5
Transferring Learning Trajectories of Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Transformer Fusion with Optimal Transport	❌	✅	✅	❌	✅	❌	✅	4
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting	✅	❌	✅	❌	✅	❌	✅	4
Transformer-VQ: Linear-Time Transformers via Vector Quantization	✅	✅	✅	✅	✅	❌	✅	6
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining	❌	✅	❌	❌	❌	❌	✅	2
Transformers can optimally learn regression mixture models	✅	✅	❌	❌	❌	❌	✅	3
Transport meets Variational Inference: Controlled Monte Carlo Diffusions	✅	✅	✅	✅	❌	❌	✅	5
Traveling Waves Encode The Recent Past and Enhance Sequence Learning	✅	✅	✅	✅	✅	❌	✅	6
Treatment Effects Estimation By Uniform Transformer	✅	❌	❌	❌	✅	❌	✅	3
Tree Cross Attention	✅	✅	✅	❌	✅	❌	✅	5
Tree Search-Based Policy Optimization under Stochastic Execution Delay	✅	✅	✅	❌	✅	❌	✅	5
Tree-Planner: Efficient Close-loop Task Planning with Large Language Models	✅	❌	✅	✅	❌	❌	✅	4
True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning	❌	✅	❌	❌	✅	❌	✅	3
Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning	❌	❌	✅	✅	✅	❌	✅	4
Turning large language models into cognitive models	❌	✅	✅	✅	❌	❌	✅	4
Two-stage LLM Fine-tuning with Less Specialization and More Generalization	❌	❌	✅	✅	✅	❌	✅	4
Two-timescale Extragradient for Finding Local Minimax Points	❌	❌	❌	❌	❌	❌	❌	0
UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving	❌	❌	✅	❌	✅	❌	✅	3
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models	✅	✅	✅	❌	❌	✅	✅	5
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields	❌	✅	✅	❌	✅	❌	✅	4
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation	✅	✅	✅	❌	✅	✅	✅	6
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation	✅	✅	✅	❌	❌	❌	✅	4
Unbiased Watermark for Large Language Models	✅	❌	✅	❌	✅	❌	✅	4
Uncertainty Quantification via Stable Distribution Propagation	✅	✅	✅	✅	✅	✅	✅	7
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Uncertainty-aware Graph-based Hyperspectral Image Classification	✅	✅	✅	✅	✅	❌	✅	6
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning	✅	✅	✅	❌	✅	❌	✅	5
Understanding Addition in Transformers	✅	✅	❌	❌	✅	❌	✅	4
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression	❌	✅	✅	❌	✅	❌	✅	4
Understanding Catastrophic Forgetting in Language Models via Implicit Inference	❌	✅	✅	❌	❌	❌	✅	3
Understanding Certified Training with Interval Bound Propagation	❌	✅	✅	✅	❌	❌	✅	4
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory	❌	✅	✅	❌	✅	❌	✅	4
Understanding Domain Generalization: A Noise Robustness Perspective	❌	✅	✅	✅	❌	❌	✅	4
Understanding Expressivity of GNN in Rule Learning	✅	✅	✅	✅	✅	❌	✅	6
Understanding In-Context Learning from Repetitions	❌	✅	✅	❌	✅	❌	✅	4
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions	✅	✅	❌	❌	✅	❌	✅	4
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation	✅	✅	✅	❌	✅	❌	✅	5
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP	❌	✅	✅	✅	✅	❌	✅	5
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks	❌	❌	✅	❌	✅	❌	✅	3
Understanding prompt engineering may not require rethinking generalization	✅	❌	✅	❌	❌	❌	✅	3
Understanding the Effects of RLHF on LLM Generalisation and Diversity	❌	✅	✅	✅	❌	❌	✅	4
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift	❌	❌	✅	✅	✅	❌	✅	4
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks	✅	✅	✅	✅	❌	❌	✅	5
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates	✅	✅	✅	❌	✅	❌	✅	5
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization	✅	✅	✅	❌	✅	❌	✅	5
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback	❌	✅	✅	✅	❌	❌	✅	4
Uni3D: Exploring Unified 3D Representation at Scale	❌	✅	✅	✅	✅	❌	✅	5
UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling	❌	✅	✅	✅	✅	❌	✅	5
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science	❌	❌	✅	✅	✅	✅	✅	5
Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks	✅	✅	✅	✅	❌	❌	✅	5
Unified Human-Scene Interaction via Prompted Chain-of-Contacts	❌	✅	✅	❌	❌	❌	✅	3
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization	❌	✅	✅	✅	✅	❌	✅	5
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization	✅	✅	❌	❌	✅	✅	✅	5
Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence	❌	❌	✅	✅	❌	❌	❌	2
Universal Backdoor Attacks	✅	✅	✅	✅	❌	❌	✅	5
Universal Guidance for Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Universal Humanoid Motion Representations for Physics-Based Control	✅	❌	✅	❌	❌	❌	✅	3
Universal Jailbreak Backdoors from Poisoned Human Feedback	❌	✅	✅	❌	❌	❌	❌	2
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition	❌	✅	✅	✅	❌	❌	✅	4
Unknown Domain Inconsistency Minimization for Domain Generalization	✅	✅	✅	✅	❌	❌	✅	5
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation	❌	✅	✅	✅	❌	❌	✅	4
Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND	❌	✅	✅	✅	✅	❌	✅	5
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
Unlocking the Power of Representations in Long-term Novelty-based Exploration	✅	❌	✅	❌	✅	❌	✅	4
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models	❌	✅	✅	❌	❌	✅	❌	3
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge	❌	✅	✅	❌	✅	❌	✅	4
Unprocessing Seven Years of Algorithmic Fairness	❌	✅	✅	✅	✅	❌	✅	5
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space	❌	✅	✅	❌	❌	❌	✅	3
Unraveling the Key Components of OOD Generalization via Diversification	❌	✅	✅	✅	✅	❌	✅	5
Unsupervised Order Learning	✅	✅	✅	❌	✅	❌	✅	5
Unsupervised Pretraining for Fact Verification by Language Model Distillation	❌	✅	✅	✅	✅	❌	✅	5
Unveiling Options with Neural Network Decomposition	✅	✅	✅	❌	❌	❌	✅	4
Unveiling and Manipulating Prompt Influence in Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
Unveiling the Pitfalls of Knowledge Editing for Large Language Models	❌	✅	✅	❌	❌	❌	✅	3
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels	❌	❌	✅	❌	❌	❌	✅	2
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection	❌	❌	✅	✅	✅	❌	✅	4
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition	❌	❌	✅	✅	✅	✅	✅	5
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections	❌	✅	✅	✅	✅	❌	✅	5
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models	❌	✅	✅	✅	❌	✅	✅	5
VDT: General-purpose Video Diffusion Transformers via Mask Modeling	❌	✅	✅	❌	✅	❌	✅	4
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning	✅	✅	✅	✅	✅	❌	✅	6
VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE	❌	✅	✅	✅	✅	❌	✅	5
VQ-TR: Vector Quantized Attention for Time Series Forecasting	✅	❌	✅	❌	✅	❌	✅	4
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs	❌	✅	✅	✅	❌	❌	✅	4
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation	❌	✅	✅	✅	❌	❌	✅	4
Vanishing Gradients in Reinforcement Finetuning of Language Models	❌	✅	✅	✅	✅	❌	✅	5
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions	✅	✅	❌	❌	❌	❌	✅	3
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits	✅	✅	✅	❌	❌	❌	✅	4
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data	✅	✅	✅	❌	❌	❌	✅	4
Variational Bayesian Last Layers	✅	✅	✅	✅	✅	❌	✅	6
Variational Inference for SDEs Driven by Fractional Noise	❌	✅	✅	✅	✅	✅	✅	6
VeRA: Vector-based Random Matrix Adaptation	❌	❌	✅	✅	❌	❌	✅	3
VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation	❌	❌	✅	❌	✅	❌	✅	3
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks	✅	✅	✅	✅	✅	✅	✅	7
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation	❌	❌	✅	❌	❌	❌	✅	2
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models	❌	✅	✅	✅	✅	❌	❌	4
Video Decomposition Prior: Editing Videos Layer by Layer	❌	❌	✅	❌	✅	❌	✅	3
Video Language Planning	✅	✅	✅	❌	✅	❌	✅	5
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation	✅	❌	✅	✅	❌	❌	✅	4
Vision Transformers Need Registers	❌	❌	✅	❌	❌	❌	✅	2
Vision-Language Foundation Models as Effective Robot Imitators	❌	❌	✅	✅	✅	❌	✅	4
Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning	✅	✅	✅	❌	✅	❌	✅	5
Vision-by-Language for Training-Free Compositional Image Retrieval	❌	✅	✅	✅	✅	❌	✅	5
Visual Data-Type Understanding does not emerge from scaling Vision-Language Models	✅	✅	✅	❌	✅	✅	✅	6
Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis	✅	✅	✅	❌	✅	❌	✅	5
Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning	❌	❌	✅	❌	❌	❌	✅	2
Weaker MVI Condition: Extragradient Methods with Multi-Step Exploration	✅	❌	❌	❌	❌	❌	✅	2
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images	❌	✅	✅	✅	❌	✅	✅	5
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity	✅	✅	✅	❌	✅	❌	✅	5
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency	❌	✅	✅	✅	✅	❌	✅	5
WebArena: A Realistic Web Environment for Building Autonomous Agents	❌	✅	✅	❌	❌	❌	✅	3
What Algorithms can Transformers Learn? A Study in Length Generalization	✅	❌	❌	❌	❌	❌	✅	2
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning	✅	✅	✅	❌	✅	❌	✅	5
What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity	✅	✅	✅	❌	❌	❌	✅	4
What Matters to You? Towards Visual Representation Alignment for Robot Learning	❌	❌	✅	❌	❌	❌	✅	2
What does automatic differentiation compute for neural networks?	✅	❌	✅	❌	❌	❌	✅	3
What does the Knowledge Neuron Thesis Have to do with Knowledge?	❌	✅	✅	❌	❌	❌	❌	2
What's In My Big Data?	❌	✅	✅	✅	✅	❌	✅	5
What's in a Prior? Learned Proximal Networks for Inverse Problems	✅	✅	✅	❌	✅	✅	✅	6
When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations	❌	✅	✅	❌	❌	❌	✅	3
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method	❌	❌	✅	✅	❌	❌	✅	3
When Semantic Segmentation Meets Frequency Aliasing	❌	✅	✅	✅	❌	❌	✅	4
When can transformers reason with abstract symbols?	❌	✅	✅	✅	❌	❌	✅	4
When should we prefer Decision Transformers for Offline Reinforcement Learning?	❌	✅	✅	✅	✅	✅	✅	6
Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs	❌	✅	✅	❌	❌	❌	✅	3
Whittle Index with Multiple Actions and State Constraint for Inventory Management	✅	✅	❌	✅	✅	❌	✅	5
Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models	✅	✅	✅	❌	❌	❌	✅	4
Why is SAM Robust to Label Noise?	❌	❌	✅	❌	✅	❌	✅	3
WildChat: 1M ChatGPT Interaction Logs in the Wild	❌	❌	✅	✅	✅	❌	✅	4
WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space	❌	❌	✅	❌	✅	❌	✅	3
Win-Win: Training High-Resolution Vision Transformers from Two Windows	❌	❌	✅	✅	❌	❌	✅	3
Window Attention is Bugged: How not to Interpolate Position Embeddings	❌	✅	✅	✅	✅	✅	✅	6
WizardCoder: Empowering Code Large Language Models with Evol-Instruct	❌	❌	✅	✅	❌	❌	✅	3
WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions	❌	❌	✅	❌	✅	❌	✅	3
Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models	❌	✅	✅	❌	✅	❌	✅	4
Xformer: Hybrid X-Shaped Transformer for Image Denoising	❌	✅	✅	❌	✅	❌	✅	4
YaRN: Efficient Context Window Extension of Large Language Models	❌	✅	✅	❌	✅	❌	✅	4
Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML	❌	✅	✅	✅	✅	✅	✅	6
You Only Query Once: An Efficient Label-Only Membership Inference Attack	✅	✅	✅	✅	❌	❌	✅	5
ZeRO++: Extremely Efficient Collective Communication for Large Model Training	✅	✅	✅	❌	✅	❌	❌	4
Zero Bubble (Almost) Pipeline Parallelism	✅	✅	❌	❌	✅	❌	✅	4
Zero and Few-shot Semantic Parsing with Ambiguous Inputs	❌	✅	✅	✅	❌	❌	✅	4
Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs	✅	❌	✅	✅	✅	❌	✅	5
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models	❌	✅	✅	❌	❌	❌	✅	3
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models	✅	❌	✅	❌	✅	❌	✅	4
Zero-Shot Robustification of Zero-Shot Models	✅	✅	✅	✅	✅	❌	✅	6
ZeroFlow: Scalable Scene Flow via Distillation	✅	✅	✅	✅	✅	❌	❌	5
Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles	✅	❌	✅	❌	❌	❌	✅	3
ZipIt! Merging Models from Different Tasks without Training	❌	✅	✅	✅	❌	❌	✅	4
Zipformer: A faster and better encoder for automatic speech recognition	✅	✅	✅	❌	✅	❌	✅	5
Zoology: Measuring and Improving Recall in Efficient Language Models	✅	✅	✅	✅	✅	❌	✅	6
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization	✅	✅	✅	❌	❌	❌	✅	4
fairret: a Framework for Differentiable Fairness Regularization Terms	❌	✅	✅	✅	✅	❌	✅	5
iGraphMix: Input Graph Mixup Method for Node Classification	✅	❌	✅	✅	✅	✅	✅	6
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting	✅	✅	✅	✅	✅	❌	✅	6
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning	✅	❌	✅	❌	❌	❌	✅	3
sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows	✅	❌	✅	✅	❌	❌	✅	4