36 citations · 99 across the 15 of their papers we have counts for
4 papers · 1 filter
Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Yihe Deng, Weitong Zhang, Zixiang Chen +1
Misunderstandings arise not only in interpersonal communication but also between humans and Large Language Models (LLMs). Such discrepancies can make LLMs interpret seemingly unamb…
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Kaixuan Ji, Qingyue Zhao, Jiafan He +2
Recent studies have shown that episodic reinforcement learning (RL) is no harder than bandits when the total reward is bounded by , and proved regret bounds that have a polyloga…
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
Weitong Zhang, Jiafan He, Zhiyuan Fan +1
We study linear contextual bandits in the misspecified setting, where the expected reward function can be approximated by a linear function class up to a bounded misspecification l…
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
Junkai Zhang, Weitong Zhang, Quanquan Gu
We study reward-free reinforcement learning (RL) with linear function approximation, where the agent works in two phases: (1) in the exploration phase, the agent interacts with the…