✳flâneur — a map of the web's best reading
The Nature of Preferences | RLHF Book by Nathan Lambert
rlhfbook.com · 4,068 words · saved by 1 readers
The Reinforcement Learning from Human Feedback Book
--> RLHF Book --> The Nature of Preferences | RLHF and Post-Training Book by Nathan Lambert Reinforcement Learning from Human Feedback A short introduction to RLHF and post-training focused on language models. Nathan Lambert Lecture 8: On “Preferences” and Preference Data The Nature of Preferences Reinforcement learning from human feedback, also referred to as reinforcement learning from human preferences in early literature, emerged to optimize machine learning models in domains where specifically designing a reward function is hard. The word preferences , which was present in early literatur
Explore this link on the map →related reading
- RLHF & Post-Training Course by Nathan Lambertrlhfbook.com
- RLHF: Reinforcement Learning from Human Feedbackhuyenchip.com
- Deep Reinforcement Learning from Human Preferencesproceedings.neurips.cc
- Reinforcement learning from human feedback - Wikipediaen.wikipedia.org
- [2305.18290] Direct Preference Optimization: Your Language Model is Secretly a Reward Modelarxiv.org
- rlhfbook.com/book.pdfrlhfbook.com
- Nash Learning from Human Feedbackarxiv.org
- Reward is not the optimization target — LessWronglesswrong.com
- RLHF Bookrlhfbook.com
- A Crash Course in the Neuroscience of Human Motivation — LessWronglesswrong.com
- Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts | RLHFlowrlhflow.github.io
- How RLHF actually works - by Nathan Lambertinterconnects.ai