19 citations · 31 across the 5 of their papers we have counts for
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cs.CL2023★ 3 cited
ALLURE: Auditing and Improving LLM-based Evaluation of Text using Iterative In-Context-Learning
Hosein Hasanbeig, Hiteshi Sharma, Leo Betthauser +2
From grading papers to summarizing medical documents, large language models (LLMs) are evermore used for evaluation of text generated by humans and AI alike. However, despite their…
cs.CL2023★ 5 cited
Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Banghua Zhu, Hiteshi Sharma, Felipe Vieira Frujeri +4
Reinforcement learning from human feedback (RLHF) has emerged as a reliable approach to aligning large language models (LLMs) to human preferences. Among the plethora of RLHF techn…