Shadow Evaluations: AI Agents' Open-Ended Research Rejected by Original Authors

A recent preprint introduces a testing framework called 'Shadow Evaluations' to examine whether frontier AI agents can handle open-ended scientific research. In the experiment, agents took on core open problems from two unpublished NeurIPS papers, with 6 days and thousands of dollars in API and compute resources for autonomous exploration. Ultimately, the original paper authors reviewed the AI-generated research papers and rejected them all. The study highlights clear bottlenecks for agents in open-ended research, providing an important counterweight to overly optimistic narratives of 'automated AI science'.

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2026-07-30 ~ 2026-08-01 · 12 related posts

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