Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
#MARL #Multi-Agent Systems #Agentic Systems #Orchestrator #Tool Calling #Heterogeneous Agents #Test‑time Scaling #Pre‑trained Models #Complementary Capabilities #MAS Architecture
📌 Key Takeaways
- Current MAS rely on static, homogeneous model configurations.
- Such homogeneity limits the ability to leverage distinct strengths of pre‑trained agents.
- Team‑of‑Thoughts introduces a heterogeneous agent architecture.
- An orchestrator‑tool paradigm is used to dynamically combine agents and tools during inference.
- The approach aims to enhance test‑time scaling and overall system performance.
📖 Full Retelling
The paper "Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling" was authored by a research group (publishing on arXiv) and released in February 2026. It addresses the problem that existing Multi-Agent Systems (MAS) normally use static, homogeneous models, which hinders the exploitation of the distinct strengths of different pretrained agents. By introducing a novel architecture called Team‑of‑Thoughts, the authors propose a heterogeneous agent framework that employs an orchestrator‑tool paradigm to dynamically pair agents and tools at test time, thereby improving overall system performance.
🏷️ Themes
Multi-Agent Systems, Agentic systems, Orchestrator and Tool Calling, Heterogeneous Agents, Test‑time Scaling, Complementary Model Strengths
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Original Source
arXiv:2602.16485v1 Announce Type: cross
Abstract: Existing Multi-Agent Systems (MAS) typically rely on static, homogeneous model configurations, limiting their ability to exploit the distinct strengths of differently post-trained models. To address this, we introduce Team-of-Thoughts, a novel MAS architecture that leverages the complementary capabilities of heterogeneous agents via an orchestrator-tool paradigm. Our framework introduces two key mechanisms to optimize performance: (1) an orchest
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