arXiv AI July 13, 2026 By Vardhan Dongre, Dilek Hakkani-T\"ur

Embodied Multi-Agent Coordination by Aligning World Models Through Dialogue

arXiv:2605. 12920v3 Announce Type: replace-cross Abstract: Effective collaboration between embodied agents requires more than acting in a shared environment; it demands communication grounded in each agent's evolving understanding of the world.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jun 29

LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior

arXiv:2606. 28182v1 Announce Type: cross Abstract: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years.

By Qinhong Zhou, Chuang Gan, Anoop Cherian

llms agents robotics fine-tuning benchmarks

arXiv AI

Sep 21

Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue

The paper examines how conversational AI, specifically ChatGPT, displays aspects of cooperative dialogue such as morality, politeness, and alignment compared to human-human conversations. Using over 26,000 multi‑turn dialogues and mixed‑effects modeling, the authors find that AI mimics the surface features of cooperation—like warmth and hedging—yet lacks the underlying social architecture that drives mutual adaptation. Key findings include a dissociation between AI’s moral output and human negotiation, a decline in linguistic convergence, and a reversal of typical human accommodation mechanisms when interacting with AI.

By Marina Mitiaeva, Lu Xiao

llms safety

arXiv AI

2d ago

Aligned but Not Partner-Specific: How Multimodal LLM Agents Succeed in Reference Games Without Forming Conceptual Pacts

arXiv:2606.08081v2 Announce Type: replace-cross Abstract: Repeated reference games test whether interlocutors replace their initially long descriptions with shorter, partner-specific expressions grou...

By Po-Ya Angela Wang, Chinmaya Mishra, Asl{\i} \"Ozy\"urek, Paula Rubio-Fern\'andez, Esam Ghaleb

llms agents multimodal safety

arXiv AI

Jun 9

Aligned but Not Partner-Specific: Distinguishing How Multimodal LLM Agents Succeed in Reference Games Without Human-Like Conventions

arXiv:2606. 08081v1 Announce Type: cross Abstract: Repeated reference games test whether interlocutors replace their initially long descriptions with shorter, partner-specific conventions grounded in shared interaction history.

By Po-Ya Angela Wang, Chinmaya Mishra, Asl{\i} \"Ozy\"urek, Paula Rubio-Fern\'andez, Esam Ghaleb

llms agents multimodal safety

arXiv AI

Aug 11

Illusion of Alignment: Detecting Hidden Disagreement in Collaborative Dialogue

arXiv:2608. 08210v1 Announce Type: new Abstract: Collaborative dialogue can end with apparent agreement while participants still differ on goals, assumptions, or execution plans, creating an \textbf{illusion of alignment (IoA)}.

By Kaiming Liu, Fuwen Luo, Ziyue Wang, Jinrui Ju, Yuxuan Liu, Xuanyu Lei, Yunghwei Lai, Peng Li, Yang Liu

llms agents safety

arXiv AI

Jul 13

Communication-Efficient Digital-Twin Coordination for Heterogeneous LLM Embodied Agents over Computing Power Networks

arXiv:2607. 09330v1 Announce Type: new Abstract: Embodied agent teams powered by heterogeneous large language models (LLMs) are being widely deployed in physical artificial intelligence such as smart factories, warehouses, and service robotics.

By Nuocheng Yang, Sihua Wang, Zihan Chen, Tony Q. S. Quek, Changchuan Yin

llms agents reinforcement-learning robotics

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Related stories

LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior

Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue

Aligned but Not Partner-Specific: How Multimodal LLM Agents Succeed in Reference Games Without Forming Conceptual Pacts

Aligned but Not Partner-Specific: Distinguishing How Multimodal LLM Agents Succeed in Reference Games Without Human-Like Conventions

Illusion of Alignment: Detecting Hidden Disagreement in Collaborative Dialogue

Communication-Efficient Digital-Twin Coordination for Heterogeneous LLM Embodied Agents over Computing Power Networks