Papers
11,951 papers found
One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
Tao Liu, Kai Wang, Senmao Li et al.
One Step Diffusion via Shortcut Models
Kevin Frans, Danijar Hafner, Sergey Levine et al.
On Evaluating the Durability of Safeguards for Open-Weight LLMs
Xiangyu Qi, Boyi Wei, Nicholas Carlini et al.
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Jayden Teoh, Pradeep Varakantham, Peter Vamplew
On Large Language Model Continual Unlearning
Chongyang Gao, Lixu Wang, Kaize Ding et al.
On Linear Representations and Pretraining Data Frequency in Language Models
Jack Merullo, Noah A. Smith, Sarah Wiegreffe et al.
Online Clustering with Nearly Optimal Consistency
T-H. Hubert Chan, Shaofeng H.-C. Jiang, Tianyi Wu et al.
ONLINE EPSILON NET & PIERCING SET FOR GEOMETRIC CONCEPTS
Sujoy Bhore, Devdan Dey, Satyam Singh
Online Preference Alignment for Language Models via Count-based Exploration
Chenjia Bai, Yang Zhang, Shuang Qiu et al.
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.
Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V Albrecht et al.
On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
Roman Belaire, Arunesh Sinha, Pradeep Varakantham
On Quantizing Neural Representation for Variable-Rate Video Coding
Junqi Shi, Zhujia Chen, Hanfei Li et al.
On Rollouts in Model-Based Reinforcement Learning
Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.
On Scaling Up 3D Gaussian Splatting Training
Hexu Zhao, Haoyang Weng, Daohan Lu et al.
On Speeding Up Language Model Evaluation
Jin Peng Zhou, Christian K Belardi, Ruihan Wu et al.
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality
Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee et al.
On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime
Hengquan Guo, Xin Liu
On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
Marcus Williams, Micah Carroll, Adhyyan Narang et al.
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
Yongyi Su, Yushu Li, Nanqing Liu et al.
On the Adversarial Vulnerability of Label-Free Test-Time Adaptation
Shahriar Rifat, Jonathan Ashdown, Michael J. De Lucia et al.
On the Almost Sure Convergence of the Stochastic Three Points Algorithm
Taha EL BAKKALI EL KADI, Omar Saadi
On the Benefits of Attribute-Driven Graph Domain Adaptation
Ruiyi Fang, Bingheng Li, zhao kang et al.
On the Benefits of Memory for Modeling Time-Dependent PDEs
Ricardo Buitrago, Tanya Marwah, Albert Gu et al.
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux, Max Zimmer, Sebastian Pokutta