RLHF: Reinforcement Learning from Human Feedback

In literature discussing why ChatGPT is able to capture so much of our imagination, I often come across two narratives:

[ LinkedIn discussion , Twitter thread ] In literature discussing why ChatGPT is able to capture so much of our imagination, I often come across two narratives: Scale: throwing more data and compute at it. UX: moving from a prompt interface to a more natural chat interface. One narrative that is often glossed over is the incredible technical creativity that went into making models like ChatGPT work. One such cool idea is RLHF (Reinforcement Learning from Human Feedback): incorporating reinforcement learning and human feedback into NLP. RL has been notoriously difficult to work with, and theref

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• Eric Chang
• Yung-Hsuan Yang
• Micah Carroll
• Soham Shah
• Evan Cater
• Karan Dalal
• Manh Duc Hoang
• Hiệp Nguyễn Tuấn
• Danish

related reading

• rlhfbook.com/book.pdfrlhfbook.com
• RLHF & Post-Training Course by Nathan Lambertrlhfbook.com
• LLM Training: RLHF and Its Alternativesmagazine.sebastianraschka.com
• DeepSeek-R1arxiv.org
• State of RL for reasoning LLMs | A. Weersaweers.de
• [2305.18290] Direct Preference Optimization: Your Language Model is Secretly a Reward Modelarxiv.org
• Reinforcement learning from human feedback - Wikipediaen.wikipedia.org
• rl-for-llms.md · GitHubgist.github.com
• The N Implementation Details of RLHF with PPO | ICLR Blogposts 2024iclr-blogposts.github.io
• [2309.00267] RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedbackarxiv.org
• RLHF Bookrlhfbook.com
• GenAI Handbookgenai-handbook.github.io