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  "text": "Releasing a new \"Agentic Reviewer\" for research papers. I started coding this as a weekend project, and @jyx_su made it much better.\n\nI was inspired by a student who had a paper rejected 6 times over 3 years. Their feedback loop -- waiting ~6 months for feedback each time -- was painfully slow. We wanted to see if an agentic workflow can help researchers iterate faster.\n\nWhen we trained the system on ICLR 2025 reviews and measured Spearman correlation (higher is better) on the test set:\n- Correlation between two human reviewers: 0.41\n- Correlation between AI and a human reviewer: 0.42\n\nThis suggests agentic reviewing is approaching human-level performance.\n\nThe agent grounds its feedback by searching arXiv, so it works best in fields like AI where research is freely published there. It’s an experimental tool, but I hope it helps you with your research.\n\nCheck it out here: https://t.co/n7ctnDilJJ",
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