- $H$-Consistency Bounds for Pairwise Misranking Loss Surrogates
- $_pi$-Tuning_ Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation
- 2D-Shapley_ A Framework for Fragmented Data Valuation
- A Category-theoretical Meta-analysis of Definitions of Disentanglement
- A Closer Look at Few-shot Classification Again
- A Closer Look at Self-Supervised Lightweight Vision Transformers
- A Closer Look at the Intervention Procedure of Concept Bottleneck Models
- A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests
- A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging
- A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
- A Coupled Flow Approach to Imitation Learning
- A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification
- A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment
- A Deep Conjugate Direction Method for Iteratively Solving Linear Systems
- A Distribution Optimization Framework for Confidence Bounds of Risk Measures
- A Fast Optimistic Method for Monotone Variational Inequalities
- A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
- A Flexible Diffusion Model
- A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback
- A Fully First-Order Method for Stochastic Bilevel Optimization
- A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
- A General Representation Learning Framework with Generalization Performance Guarantees
- A Generalization of ViT_MLP-Mixer to Graphs
- A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
- A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
- A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer
- A Kernel Stein Test of Goodness of Fit for Sequential Models
- A Kernel-Based View of Language Model Fine-Tuning
- A Kernelized Stein Discrepancy for Biological Sequences
- A Large-Scale Study of Probabilistic Calibration in Neural Network Regression
- A Law of Robustness beyond Isoperimetry
- A Mathematical Model for Curriculum Learning for Parities
- A Model-Based Method for Minimizing CVaR and Beyond
- A Model-free Closeness-of-influence Test for Features in Supervised Learning
- A Modern Look at the Relationship between Sharpness and Generalization
- A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
- A Nearly-Optimal Bound for Fast Regression with $_ell_∞$ Guarantee
- A Neural PDE Solver with Temporal Stencil Modeling
- A New PHO-rmula for Improved Performance of Semi-Structured Networks
- A Picture of the Space of Typical Learnable Tasks
- A Reinforcement Learning Framework for Dynamic Mediation Analysis
- A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
- A Robust Test for the Stationarity Assumption in Sequential Decision Making
- A Scalable Frank-Wolfe-Based Algorithm for the Max-Cut SDP
- A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
- A Statistical Perspective on Retrieval-Based Models
- A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs
- A Study on Transformer Configuration and Training Objective
- A Theoretical Analysis of the Learning Dynamics under Class Imbalance
- A Three-regime Model of Network Pruning