✨TCAndon-Router: Adaptive Reasoning Router for Multi-Agent Collaboration

📝 Summary:
TCAndon-Router TCAR is an adaptive reasoning router for multi-agent systems. It overcomes limitations of existing task routers by supporting dynamic agent onboarding and generating natural language reasoning chains to select agents. TCAR significantly improves routing accuracy, reduces conflicts,...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04544
• PDF: https://arxiv.org/pdf/2601.04544
• Github: https://github.com/Tencent/TCAndon-Router

🔹 Models citing this paper:
• https://huggingface.co/tencent/TCAndon-Router

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✨Step-level Optimization for Efficient Computer-use Agents

📝 Summary:
Computer-use agents are inefficient when using large models for every step. This paper proposes an event-driven cascade that uses small policies by default, escalating to stronger models only when lightweight monitors detect high risk like stalls or semantic drift, thereby optimizing compute.

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27151
• PDF: https://arxiv.org/pdf/2604.27151
• Github: https://github.com/yale-nlp/StepWise

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