CoMIC is a parameter-free cloud-edge framework that circulates memory and insights between edge agents and a central critic to improve long-horizon LLM agent performance on symbolic and text tasks.
A llm-based controllable, scalable, human-involved user simulator framework for conversational recommender systems
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CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems
CoMIC is a parameter-free cloud-edge framework that circulates memory and insights between edge agents and a central critic to improve long-horizon LLM agent performance on symbolic and text tasks.