✳flâneur — a map of the web's best reading
Preference Data | RLHF Book by Nathan Lambert
rlhfbook.com · 4,733 words · saved by 1 readers
The Reinforcement Learning from Human Feedback Book
--> RLHF Book --> Preference Data | 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 Preference Data Preference data is the engine of preference fine-tuning and reinforcement learning from human feedback. The core problem we’ve been trying to solve with RLHF is that we cannot precisely model human rewards and preferences for AI models’ outputs – that is, write clearly defined loss functions to optimize against – so pre
Explore this link on the map →related reading
- RLHF: Reinforcement Learning from Human Feedbackhuyenchip.com
- RLHF & Post-Training Course by Nathan Lambertrlhfbook.com
- rlhfbook.com/book.pdfrlhfbook.com
- How RLHF actually works - by Nathan Lambertinterconnects.ai
- [2305.18290] Direct Preference Optimization: Your Language Model is Secretly a Reward Modelarxiv.org
- RLHF Bookrlhfbook.com
- Reinforcement learning from human feedback - Wikipediaen.wikipedia.org
- Nash Learning from Human Feedbackarxiv.org
- The Only Important Technology Is The Internet - Kevin Lukevinlu.ai
- [2309.00267] RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedbackarxiv.org
- Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts | RLHFlowrlhflow.github.io
- Deep Reinforcement Learning from Human Preferencesproceedings.neurips.cc