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arXiv 2610.28763 · cs.AI · 2026-10-20

Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?

Ming Zhong, Stacy Li, Nicholas Carlini, Matthew Jagielski

Anthropic

In latest · #265 Added on 2026-10-25

One-line takeaway

Anthropic's Agent4Sci tests whether frontier coding agents can beat published best models on 20 scientific-ML benchmarks across 11 domains; they beat every one (Claude Opus +10.4% mean relative), but mostly via ML-engineering tricks rather than research insight.

Anthropic 的 Agent4Sci 用 20 个基准、11 个领域测前沿编程 agent 能否刷新科学 ML 最佳模型:每项都超过了已发表最好结果,Claude Opus 平均相对提升 10.4%,但收益几乎全靠工程技巧而非科研洞见。

29HF upvotes
39GitHub stars
0Citations (Semantic Scholar)
48.9Buzz score

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Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.

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