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News/Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
arxiv
PublishedJuly 22, 2026 at 4:00 AM
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Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents

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arXiv:2607.19190v1 Announce Type: cross Abstract: Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover scene geometries and object states, infer physical parameters, and as

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arxivMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation27marxivCounterfactual Model Testing Under Distribution Shift27marxivCentralized Critics for N-Agent Ad Hoc Teamwork27marxivWhere and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning27m
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