arXiv (All)
open access
ECoMEM: Explicit Concept Memory for Memory-Dependent Robot Control
A robot may lose sight of an object it must later retrieve, need to recall what a person demonstrated earlier, or track which steps of a task it has already completed. Current vision-language-action (VLA) policies often fail once the information needed for action disappears from the current observat
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
- Memory for Attention: Language-Conditioned Re-Perception with a Vision--Language--Motion Map#1070889
- Reasoning Without Inference Cost: Latent Semantic Scaffolding for Robot VLA Policies#971554
- PerSeM: Persistent Semantic Memory for Long-Horizon Open-Vocabulary UAV Mapping#1035640
- Memory-guided selective attention: Evidence for context-specific control using the trial-unique Stroop task.#151604
- DolphinBench: Mapping the Pareto Frontier of Agent Memory#1061064
Record · ID 1155736
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