arXiv (All)
open access
ΔWAM: Distilling Action Tangent Fields into World Action Models
World Action Models (WAM) improve robot policies by augmenting sparse action supervision with dense future prediction. However, much of the predictable future is dominated by appearance and scene persistence rather than action-dependent dynamics. We observe that several recent WAM designs, including
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
- Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models#1035606
- FutureDuet: Decoupling Observation Access from Future Supervision in World Action Models#1119435
- WAVE-0: Bridging VLA Policies and WAMs with Lightweight Latent Future Prediction#1344069
- Beyond Actions: Learning Future Operation Targets for Vision-Language-Action Models#1297564
- Video Prediction Policy 2: Predict Better, Act Better#1234637
Record · ID 1234101
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