arXiv (All)
open access
Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation
Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions. Despite recent progress with vision-language models (VLMs), a critical semantic-geometric gap remains: while VLMs excel at language and 2D visual understandin
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
- Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering#1062256
- Guava: Distilling Frontier VLMs into a Compact Agent through a Robotic Manipulation Harness#1141573
- LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies#973686
- VLMs Can Describe, But Not Measure: Object-Centric Scene Understanding for Robotic Manipulation#1064728
- DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication#1161066
Record · ID 1012218
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