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.
over-compression
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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UNVERDICTED 2representative citing papers
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.
citing papers explorer
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Enabling Agents to Communicate Entirely in Latent Space
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.
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What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems
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.