SOURCE-LINKED INTELLIGENCE
GraphSkillEvo: Evolutionary Optimization of Graph-Structured Agent Skills
Skills can improve the performance of Large Language Model (LLM) agents by providing task-specific procedural guidance, while skill optimization further improves their effectiveness through iterative refinement. However, existing skill optimization methods typically represent skills as unstructured natural-language instructions, creating two key challenges: 1) Unstructured skills often lack explicit workflow-level guidance and contain substantial redundancy, making them difficult for LLMs to execute; 2) the vast search space of unconstrained natural-language skills makes skill optimization ine
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T13:24:33.000Z
First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.