Reproduce “Work2Skill: Capturing Human GUI Experience for Reusable Agent Skill Induction” on OpenResearch

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About this paper

Yuqi Huang, Hui Li, Yifei Cao, Zikun Cai, Tianci Xie, Yangfan Gao, Pinxue Guo, Chaoyun Zhang and 4 more

Work2Skill turns human GUI demonstrations into reusable procedural skills by linking actions to visual and available accessibility evidence, then letting an agent inspect that evidence while drafting and revising instructions. On 64 MyPCBench tasks, GPT-5.5 scores 85.27 versus 74.73 without skills. Across tested executors, gains appear on MyPCBench and a selected, non-random 286-task OSWorld-Verified subset.

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