opendilab/awesome-RLHF
A continually updated, curated list of essential resources for Reinforcement Learning with Human Feedback (RLHF), encompassing research papers, codebases, datasets, and related materials.
Core Features
Detailed Introduction
Reinforcement Learning with Human Feedback (RLHF) is a pivotal machine learning paradigm that leverages human input to optimize AI models, aligning their behavior with complex human values. This project serves as a critical, dynamic repository for researchers and practitioners, offering a structured compilation of cutting-edge RLHF resources. It meticulously curates papers, code, datasets, and blogs, facilitating the exploration and advancement of RLHF techniques across diverse applications, from large language models to game AI. Its commitment to continuous updates ensures users remain at the forefront of this rapidly evolving field.