9 citations · 14 across the 3 of their papers we have counts for
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cs.LG2023★ 4 cited
Learning to Generate Better Than Your LLM
Jonathan D. Chang, Kiante Brantley, Rajkumar Ramamurthy +2
Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning Large Language Models (LLMs) for text generation. In particular, recent LLMs such as ChatGPT and GPT-…
cs.LG2022★ 1 cited
Learning Bellman Complete Representations for Offline Policy Evaluation
Jonathan D. Chang, Kaiwen Wang, Nathan Kallus +1
We study representation learning for Offline Reinforcement Learning (RL), focusing on the important task of Offline Policy Evaluation (OPE). Recent work shows that, in contrast to…