arXiv (All)
open access
GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation
Robot manipulation policies often struggle to generalize beyond their demonstrations, even when new instructions involve familiar objects and behaviors. When language and scenes are strongly correlated during training, a policy can learn a fixed visual-action mapping rather than respond to the reque
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
- Key-Gram: Extensible World Knowledge for Embodied Manipulation#200538
- SkelWAM: A Skeleton-Guided World-Action Model for Zero-Shot Cross-Embodiment Manipulation#1036371
- TFP: Temporally Conditioned Memory-Fusion Policies for Visuomotor Learning#793774
- TFP: Temporally Conditioned Memory-Fusion Policies for Visuomotor Learning#789769
- LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies#973686
Record · ID 1012546
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