NatureBench is a cross-discipline benchmark of 27 tasks distilled from peer-reviewed Nature-family publications, spanning 6 scientific domains. It is designed to evaluate whether AI coding agents can move beyond reproduction toward discovery: each task asks an agent to solve a real scientific machine-learning problem and is scored against the source paper's reported state of the art.

📄 arXiv paper: https://arxiv.org/abs/2606.24530 💻 GitHub code… See the full description on the dataset page: https://huggingface.co/datasets/JoeLiu996/NatureBench.