Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration
cs.AI, cs.RO
Submitted: 2026-10-12
Updated: 2026-10-12
Code: https://github.com/szlAdrian/observe-share-or-predict
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- LLM Multi-Agent Systems: Challenges and Open Problems
- PerspAct: Enhancing LLM Situated Collaboration Skills through Perspective Taking and Active Vision
- From the Fluency Fallacy to the Micro-to-Macro Validity Gap: Opportunities and Pitfalls of LLMs in Social Simulation
- Multi-Agent LLM Actor-Critic Framework for Social Robot Navigation
- Collaborative Belief Reasoning with LLMs for Efficient Multi-Agent Collaboration
- Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
- Large Language Models as Theory of Mind Aware Generative Agents with Counterfactual Reflection
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems