Papers
11,015 papers found
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention
Arvind V. Mahankali, Tatsunori Hashimoto, Tengyu Ma
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
Christian Horvat, Jean-Pascal Pfister
On Harmonizing Implicit Subpopulations
Feng Hong, Jiangchao Yao, Yueming Lyu et al.
Online Continual Learning for Interactive Instruction Following Agents
Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi
Online GNN Evaluation Under Test-time Graph Distribution Shifts
Xin Zheng, Dongjin Song, Qingsong Wen et al.
Online Information Acquisition: Hiring Multiple Agents
Federico Cacciamani, Matteo Castiglioni, Nicola Gatti
Online Stabilization of Spiking Neural Networks
Yaoyu Zhu, Jianhao Ding, Tiejun Huang et al.
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Aadirupa Saha, Branislav Kveton
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright et al.
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Rishabh Agarwal, Nino Vieillard, Yongchao Zhou et al.
On Representation Complexity of Model-based and Model-free Reinforcement Learning
Hanlin Zhu, Baihe Huang, Stuart Russell
On Stationary Point Convergence of PPO-Clip
Ruinan Jin, Shuai Li, Baoxiang Wang
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection
Chaohua Shi, Kexin Huang, Lu GAN et al.
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
Rohan Subramani, Marcus Williams, Max Heitmann et al.
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto et al.
On the Foundations of Shortcut Learning
Katherine Hermann, Hossein Mobahi, Thomas FEL et al.
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Linus Bleistein, Agathe Guilloux
On the generalization capacity of neural networks during generic multimodal reasoning
Takuya Ito, Soham Dan, Mattia Rigotti et al.
On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning
Ziyi Chen, Yi Zhou, Heng Huang
On the hardness of learning under symmetries
Bobak Kiani, Thien Le, Hannah Lawrence et al.
On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
Ziwei Guan, Yi Zhou, Yingbin Liang
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
Jen-tse Huang, Wenxuan Wang, Eric John Li et al.
On the Joint Interaction of Models, Data, and Features
Yiding Jiang, Christina Baek, J Zico Kolter
On the Learnability of Watermarks for Language Models
Chenchen Gu, Xiang Lisa Li, Percy Liang et al.