Summary of R3hf: Reward Redistribution For Enhancing Reinforcement Learning From Human Feedback, by Jiahui Li et al.
R3HF: Reward Redistribution for Enhancing Reinforcement Learning from Human Feedback
by Jiahui Li, Tai-wei Chang, Fengda Zhang, Kun Kuang, Long Chen
First submitted to arxiv on: 13 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Reinforcement learning from human feedback (RLHF) is a technique for aligning large language models (LLMs) with human preferences. Initial training of a reward model using pairwise human feedback enables subsequent reinforcement learning to assess generated sentence scores and optimize LLMs. However, current methods allocate a single, sparse, and delayed reward to an entire sequence, potentially overlooking individual token contributions. Our proposed R3HF method addresses this limitation by redistributing rewards at the token level using regression-based reward prediction. This approach improves language nuance understanding, leading to enhanced performance. We demonstrate the effectiveness of our method through comprehensive experiments on diverse datasets and tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re teaching a computer how to understand human language. You want it to learn what’s good and what’s not by showing it examples. This is called “reinforcement learning.” But current methods have a problem: they only give the computer one reward or punishment for an entire piece of text, even though individual words might be great or terrible. Our solution is called R3HF, which breaks down rewards into smaller pieces so the computer can learn more about language. This helps it become better at understanding and producing natural-sounding text. We tested our method on many different texts and tasks, and it works really well. |
Keywords
» Artificial intelligence » Regression » Reinforcement learning » Reinforcement learning from human feedback » Rlhf » Token
