Learning what to retain: gated-memory routing for efficient collaboration in multi-agent LLM systems
Read the original at arxiv.org→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...
Original headline: "Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems"
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- Sep 2, 04:00 UTC arXiv cs.AI lead source Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems