Data as of Jul 25, 2026 · Based on 2,718,867 AI responses across 9,511 prompts · See how Parse measures this
TreeReviewgithub.com · Low evidenceTreeReview is an LLM-based framework for deep and efficient scientific peer review that generates comprehensive reviews through a dynamic tree of questions and a hierarchical question-answering process. It provides implementation code and a benchmark dataset, with setup instructions (Conda environment, Python 3.11) and a command-line workflow to generate a review from a paper ID and an MMD file. The project aims to enable structured, scalable peer review by guiding large language models through organized questions to assess scientific papers.
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