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REPRO-Bench is a novel benchmark designed to evaluate the capability of agentic AI systems in automating the assessment of social science paper reproducibility. It addresses limitations of existing benchmarks by providing a collection of 112 task instances, each representing a social science paper with a publicly available reproduction report. The benchmark features end-to-end evaluation tasks on reproducibility with complexity comparable to real-world assessments, encompassing diverse data formats and programming languages.
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**Official Codebase:** [https://github.com/
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## 📦 Dataset Structure
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REPRO-Bench is a novel benchmark designed to evaluate the capability of agentic AI systems in automating the assessment of social science paper reproducibility. It addresses limitations of existing benchmarks by providing a collection of 112 task instances, each representing a social science paper with a publicly available reproduction report. The benchmark features end-to-end evaluation tasks on reproducibility with complexity comparable to real-world assessments, encompassing diverse data formats and programming languages.
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**Official Codebase:** [https://github.com/uiuc-kang-lab/REPRO-Bench](https://github.com/uiuc-kang-lab/REPRO-Bench)
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## 📦 Dataset Structure
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