AIBullisharXiv – CS AI · 7h ago6/10
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Skill or Skip? Learning Selective Skill Invocation in Agentic Tasks via Dual-Granularity Preference Learning
Researchers propose SelSkill, a machine learning framework that improves how AI agents decide whether to invoke specific skills during task execution. The method demonstrates significant performance improvements on benchmark tasks by learning when to use skills versus skip them, addressing a gap in existing agentic AI systems that struggle with unnecessary skill invocations.