The Rationale MCTS dataset consists of intermediate assessment rationales generated by large language models (LLMs). These rationales are "noisy," meaning they might contain errors or approximate reasoning, tailored for step-by-step explainable assessment of student answers in science and biology. The dataset targets questions from the The Hewlett Foundation: Short Answer Scoring competition, available… See the full description on the dataset page:
https://huggingface.co/datasets/jiazhengli/Rationale_MCTS.
