RLHF

[nagataka]

Key papers (as of Nov 2023)

• Deep reinforcement learning from human preferences
• Scalable agent alignment via reward modeling: a research direction
• Fine-Tuning Language Models from Human Preferences
• Learning to summarize from human feedback
• Training language models to follow instructions with human feedback
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• A General Theoretical Paradigm to Understand Learning from Human Preferences