arXiv (All)
open access
GRAFT: Geometry-Aware Residual Adaptation for Foundation Trackers
Humanoid behavior foundation models (BFMs) provide reusable whole-body motion priors: given a kinematic reference, they generate coordinated joint commands for motion replay, teleoperation, and VLA control. However, trained primarily on flat-ground motion, BFMs lack an explicit mechanism to adapt fo
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
- Test-Time Compute for Humanoid Behavior Foundation Models#1325792
- RoboCode: Learning Reusable Action Primitives for Robot Manipulation#1447592
- Learning Force-Reactive Humanoid Loco-Manipulation#1466894
- Learning Force-Reactive Humanoid Loco-Manipulation#1450770
- ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning#1187449
Record · ID 1467831
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