The authors create the first large-scale dataset and taxonomy of failure modes in multi-agent LLM systems to explain their limited performance gains.
Learning attentional communication for multi-agent coopera- tion.Advances in neural information processing systems, 31
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SLIM decouples inter-agent communication from policy execution in MARL via a dedicated pathway and a normalized bandwidth budget β, yielding robust performance under tight communication limits on standard benchmarks.
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Why Do Multi-Agent LLM Systems Fail?
The authors create the first large-scale dataset and taxonomy of failure modes in multi-agent LLM systems to explain their limited performance gains.
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Decoupling Communication from Policy: Robust MARL under Bandwidth Constraints
SLIM decouples inter-agent communication from policy execution in MARL via a dedicated pathway and a normalized bandwidth budget β, yielding robust performance under tight communication limits on standard benchmarks.