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SkillOpt: Executive Strategy for Self-Evolving Agent Skills research paper by Microsoft, 2026

Microsoft · May 22, 2026 · Agents and evaluation · 85 citations · 263 upvotes · unverified

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What it shows

SkillOpt introduces a systematic text-space optimizer for agent skills that trains skills as external agent state with stable updates and zero deployment inference overhead, achieving superior performance across multiple benchmarks and execution environments.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Yifan Yang, Ziyang Gong, Weiquan Huang and 12 more
arXiv
2605.23904 · PDF
Venue
arXiv.org
Citations
85, 17 influential · Semantic Scholar
Upvotes
263 · Hugging Face
Code
github.com/microsoft/SkillOpt
Lab
Microsoft · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

What changed
Influential citationsfirst count: 17Sep 25, 2026
Citationsfirst count: 85Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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