11 citations · 21 across the 18 of their papers we have counts for
5 papers · 1 filter
When is Off-Policy Evaluation (Reward Modeling) Useful in Contextual Bandits? A Data-Centric Perspective
Hao Sun, Alex J. Chan, Nabeel Seedat +2
Evaluating the value of a hypothetical target policy with only a logged dataset is important but challenging. On the one hand, it brings opportunities for safe policy improvement u…
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
Hao Sun, Alihan Hüyük, Daniel Jarrett +1
Learning controllers with offline data in decision-making systems is an essential area of research due to its potential to reduce the risk of applications in real-world systems. Ho…
Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond
Hao Sun
Recent advancements in Large Language Models (LLMs) have garnered wide attention and led to successful products such as ChatGPT and GPT-4. Their proficiency in adhering to instruct…
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
In this study, we aim to enhance the arithmetic reasoning ability of Large Language Models (LLMs) through zero-shot prompt optimization. We identify a previously overlooked objecti…
ChatHaruhi: Reviving Anime Character in Reality via Large Language Model
Cheng Li, Ziang Leng, Chenxi Yan +11
Role-playing chatbots built on large language models have drawn interest, but better techniques are needed to enable mimicking specific fictional characters. We propose an algorith…