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Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems

This story is from 2026-09-02. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.00237v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems tackle complex reasoning by orchestrating how multiple agents are configured and how they collaborate. A central challenge is to adapt orchestration to the evolving collaboration state. Routing from…

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  1. 2026-09-02 04:00 · arXiv cs.AI
    Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems

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