arXiv (All)
open access
StrucPhysVideo: Learning Physical Dynamics from Structured Captions and Robot Actions
Modeling physical dynamics, including how objects move, interact, and change state, is central to video world models for embodied AI. We present StrucPhysVideo, a family of video world models that bridges physics-focused data curation with language- and action-conditioned prediction of scene evoluti
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models#928000
- ActionGround: Training-Free Runtime Refinement of Frozen VLA Policies#1117968
- WorldAttention: An Efficient Attention Architecture for Interactive Video World Models#1128868
- PhyProbe: Rethinking Physical Consistency Evaluation in Generated Videos#1142978
- A Sim-to-Real Integration Pipeline for Training and Deployment of Chunk-Based VLA Manipulation Policies#1036206
Record · ID 1012616
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive