arXiv (All)
open access
LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation
Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodiments. Modern vision-language models (VLMs) already encode spatial priors for visual grounding, spatial reasoning, and pointing, but these capabilitie
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
- LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation#631407
- LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation#622574
- Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack#271893
- Show-Harness: Just a VLM Agent Can Play Robots#997394
- Are Frontier VLM Agents Ready to Be Robot Generalists? An Empirical Study with the Embodied Agent Arena#1155789
Record · ID 987825
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