SkillMem: Compact External Skill Memory for Latent Multi-Agent Reasoning

arXiv cs.AIOctober 30, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.37935v1 Announce Type: new Abstract: Latent multi-agent systems reduce inference cost by keeping intermediate reasoning and inter-agent communication in continuous representations.\ Reusable skills, however, are commonly supplied as text or stored as layer-wise Key-Value states or skill-specific model parameters, introducing repeated processing or substantial per-skill storage.\ We introduce \textbf{SkillMem}, which represents each reusable skill as a small external latent memory and makes it directly available during latent multi-agent reasoning.\ A role-conditioned cross-attention reader allows the same memory to guide different agents according to their roles and current hidden

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