Introduces a 3-axis taxonomy (what info, alignment, fusion) for latent communication in multi-agent LLMs and identifies five design patterns from 18 methods.
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3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Interlat lets LLM agents exchange last hidden states in latent space for communication, outperforming CoT baselines across models while enabling up to 24x faster inference via compression.
Introduces PACT protocol that projects agent outputs into action-state records, yielding comparable or better task performance with substantially fewer tokens in multi-agent LLM systems and production harnesses.
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Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems
Introduces a 3-axis taxonomy (what info, alignment, fusion) for latent communication in multi-agent LLMs and identifies five design patterns from 18 methods.