The project proposes Reinforcement Learning from Community Feedback (RLCF), a training paradigm that uses large-scale community signals as supervision to teach AI systems scientific taste. It formulates scientific taste learning as a preference modeling and alignment problem, enabling AI to judge and propose research ideas with high potential impact. The framework releases models and datasets on Hugging Face and includes an online demo for paper evaluation.