Hugging Face organized a large-scale challenge to reproduce papers from the International Conference on Machine Learning (ICML) 2026, aiming to assess research reproducibility in the age of AI agents. Over 1,200 participants used various AI coding agents, including Claude Code and Codex, to attempt reproductions, resulting in over 6,800 logbooks published. The challenge successfully reproduced or attempted to reproduce 34% of the conference's accepted papers, with an automated judge evaluating the claims made in each logbook. AI
IMPACT Highlights the potential for AI agents to improve the reproducibility of scientific research and manage the increasing volume of academic submissions.
RANK_REASON The cluster describes a large-scale reproduction effort of academic papers, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
- Claude Code
- codex
- Cursor
- GLM-5.2
- Hugging Face
- International Conference on Machine Learning
- OpenResearch
- Trackio
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