AI RESEARCH
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
arXiv CS.AI
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ArXi:2603.12056v1 Announce Type: new Multimodal agents can now tackle complex reasoning tasks with diverse tools, yet they still suffer from inefficient tool use and inflexible orchestration in open-ended settings. A central challenge is enabling such agents to continually improve without parameter updates by learning from past trajectories.