Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF
Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy +3
Reinforcement learning from human feedback (RLHF) has emerged as a central tool for language model alignment. We consider online exploration in RLHF, which exploits interactive acc…
cs.LG2024
The Power of Resets in Online Reinforcement Learning
Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
Simulators are a pervasive tool in reinforcement learning, but most existing algorithms cannot efficiently exploit simulator access -- particularly in high-dimensional domains that…