AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning

In three linesAdaSwitch proposes a cloud-local collaborative paradigm where a local agent (small LLM) handles simple tasks and requests assistance from a cloud agent (large LLM) for complex reasoning. The adaptive mechanism detects local errors and dynamically switches. Evaluation on 7 benchmarks (mathematical reasoning, complex QA) shows performance improvement with reduced computational overhead.

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