Automatically optimizing agent skill files on a branching lakehouse improved held-out validation accuracy by 31.9% on 25 synthetic-but-trace-anchored tasks.
arXiv preprint arXiv:2505.00026 , year=
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A survey arguing that multi-agent AI systems remain task-centric and lack integrated computational models of human cognition, culture, values, and social cooperation.
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"Skill Issues'': Data-Centric Optimization of Lakehouse Agents
Automatically optimizing agent skill files on a branching lakehouse improved held-out validation accuracy by 31.9% on 25 synthetic-but-trace-anchored tasks.
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Toward Human-Centered Multi-Agent Systems: Integrating Cognition, Culture, Values, and Cooperation in AI Agents
A survey arguing that multi-agent AI systems remain task-centric and lack integrated computational models of human cognition, culture, values, and social cooperation.