FactReview extracts claims from ML papers, positions them via literature retrieval, and verifies them through code execution, labeling each as Supported, Partially supported, or In conflict, as shown in a CompGCN case study.
A step toward quantifying independently reproducible machine learning research.ArXiv, abs/1909.06674
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Proposes extending preregistration practices to AI agent experiments and supplies a tailored template to limit researcher degrees of freedom.
citing papers explorer
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FactReview: Evidence-Grounded Reviews with Literature Positioning and Execution-Based Claim Verification
FactReview extracts claims from ML papers, positions them via literature retrieval, and verifies them through code execution, labeling each as Supported, Partially supported, or In conflict, as shown in a CompGCN case study.
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Preregistration for Experiments with AI Agents
Proposes extending preregistration practices to AI agent experiments and supplies a tailored template to limit researcher degrees of freedom.