Observation-Free Attacks on Stochastic Bandits. - Yinglun Xu; Bhuvesh Kumar; Jacob D. Abernethy (NeurIPS, 2021)

Black-Box Targeted Reward Poisoning Attack Against Online Deep Reinforcement Learning. - Yinglun Xu; Gagandeep Singh 001 (CoRR, 2023)

On the Robustness of Epoch-Greedy in Multi-Agent Contextual Bandit Mechanisms. - Yinglun Xu; Bhuvesh Kumar; Jacob D. Abernethy (CoRR, 2023)

Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learning. - Yinglun Xu; Qi Zeng 001; Gagandeep Singh 001 (Trans. Mach. Learn. Res., 2023)

Efficient Two-Phase Offline Deep Reinforcement Learning from Preference Feedback. - Yinglun Xu; Gagandeep Singh 001 (CoRR, 2024)

Reward Poisoning Attack Against Offline Reinforcement Learning. - Yinglun Xu; Rohan Gumaste; Gagandeep Singh 001 (CoRR, 2024)

Optimal Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning. - Yinglun Xu; David Zhu; Rohan Gumaste; Gagandeep Singh 001 (CoRR, 2024)

Robust Thompson Sampling Algorithms Against Reward Poisoning Attacks. - Yinglun Xu; Zhiwei Wang; Gagandeep Singh 001 (CoRR, 2024)

Improving Assembly Code Performance with Large Language Models via Reinforcement Learning. - Anjiang Wei; Tarun Suresh; Huanmi Tan; Yinglun Xu; Gagandeep Singh 001; Ke Wang; Alex Aiken (CoRR, 2025)

Learning a Pessimistic Reward Model in RLHF. - Yinglun Xu; Hangoo Kang; Tarun Suresh; Yuxuan Wan; Gagandeep Singh 001 (CoRR, 2025)