The study examines two problems in aligning language models to human preferences using reward models. Firstly, it questions if a certain monotone transformation of the reward model can preserve preference…
Continue readingThe article introduces ALIGN BENCH, a comprehensive benchmark for evaluating alignment in Large Language Models (LLMs) for the Chinese language. The benchmark utilizes a human-in-the-loop data curation pipeline and includes…
Continue readingThis paper by Abhilash Mishra investigates the challenges of aligning AI systems with human intentions and values using Reinforcement Learning with Human Feedback (RLHF). It discusses the issue of determining…
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