arXiv (All)
open access
D$^2$-VLA: Dual-Memory Dual-Frequency Vision-Language-Action Model For Long Dynamic Manipulation
Long-horizon manipulation requires robots to remember cues that are no longer in view while responding to moving objects. Yet vision-language-action (VLA) policies often rely on the latest observation, and refreshing their visual context typically requires another costly vision-language model (VLM)
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
- Towards High-DoF Dexterous Manipulation through VLA Post-Training#1014254
- Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model#1144961
- TFP: Temporally Conditioned Memory-Fusion Policies for Visuomotor Learning#793774
- TFP: Temporally Conditioned Memory-Fusion Policies for Visuomotor Learning#789769
- Divide-and-Remember: Recursive Action-Relevant Memory for Long-Horizon VLA Policies#1155917
Record · ID 1129410
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