AI RESEARCH
Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
arXiv CS.CL
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ArXi:2602.16485v2 Announce Type: replace Existing Multi-Agent Systems (MAS) typically rely on homogeneous model configurations, failing to exploit the diverse expertise inherent in different post-trained architectures. We propose Team-of-Thoughts, a heterogeneous MAS framework that treats diverse models as specialized tools within an orchestrator-driven paradigm. Team-of-Thoughts