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Collaborating action by action: A multi-agent LLM framework for embodied reasoning.arXiv preprint arXiv:2504.17950

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

years

2026 3

representative citing papers

Scaling Participation in Modular AI Systems

cs.AI · 2026-06-05 · unverdicted · novelty 6.0

Modular AI systems assembled from contributed small models outperform monolithic LLMs by up to 15.4% on 15 tasks including reasoning and factuality while showing emergent problem-solving and benefits from contributor diversity.

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Showing 3 of 3 citing papers.

  • Diagon: A Programmable Testbed for AI-Agent Cognitive Labor Markets cs.CE · 2026-04-08 · conditional · none · ref 21

    In a simulated economy of 25 LLM agents, a programmable market testbed shows that market rules and agent configuration reshape trade, quality, and wealth, with transparency and honesty norms backfiring.

  • Scaling Participation in Modular AI Systems cs.AI · 2026-06-05 · unverdicted · none · ref 121

    Modular AI systems assembled from contributed small models outperform monolithic LLMs by up to 15.4% on 15 tasks including reasoning and factuality while showing emergent problem-solving and benefits from contributor diversity.

  • Gated Coordination for Efficient Multi-Agent Collaboration in Minecraft Game cs.MA · 2026-04-21 · unverdicted · none · ref 33

    Gated escalation and partitioned states enable more efficient multi-agent collaboration in Minecraft by making communication selective rather than automatic.