**摘要**
Reproducing research results from papers and released code is central to scientific progress. Existing works have introduced benchmarks to evaluate whether LLM agents can assist with reproducibility, but they are difficult to scale due to their reliance on substantial manual effort for data curation and evaluation. We introduce ReproRepo, a scalable framework for reproducibility evaluation that le
👤 作者: Shanda Li, Qiuhong Anna Wei, Jingwu Tang, Valerie Chen, Nihar B Shah, Tim Dettmers, Yiming Yang, Ameet Talwalkar

---
🔗 **[ReproRepo ：使用GitHub存储库问题扩展可重现性审计](https://arxiv.org/abs/2606.18237v1)**

> ReproRepo: Scaling Reproducibility Audits with GitHub Repository Issues
🏷️ 来源: ArXiv cs.AI
⏱️ 2026-06-17 14:00