3 papers
cs.LG2026
When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
Jose Efraim Aguilar Escamilla, Haoyang Hong, Jiawei Li +4
We study reward poisoning attacks in reinforcement learning (RL), where an adversary manipulates rewards within constrained budgets to force the target RL agent to adopt a policy t…
cs.LG2025
Avoiding scaling in RLHF through Preference-based Exploration
Mingyu Chen, Yiding Chen, Wen Sun +1
Reinforcement Learning from Human Feedback (RLHF) has emerged as a pivotal technique for large language model (LLM) alignment. This paper studies the setting of online RLHF and foc…
cs.LG2025
Accelerating RL for LLM Reasoning with Optimal Advantage Regression
Kianté Brantley, Mingyu Chen, Zhaolin Gao +4
Reinforcement learning (RL) has emerged as a powerful tool for fine-tuning large language models (LLMs) to improve complex reasoning abilities. However, state-of-the-art policy opt…