Hugging Face Trending Papers
Structured Maps for Landmark-Based Route Instructions with LLMs
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arXiv Computation and Language
Oct 28
Structured Maps for Landmark-Based Route Instructions with LLMs
The paper introduces a structured text representation using SVG to encode map geometry for landmark-based route instruction generation. It shows that large language models can use this representation to select landmarks at turns and near destinations, performing as well or better than image-based inputs. Fine‑tuning smaller local LLMs further improves accuracy, demonstrating the efficiency of structured text for spatial reasoning in navigation.
arXiv Computer Vision
Oct 1
KilometerVision: A New Frontier for Large-Scale Spatial Intelligence in VLMs
arXiv:2609.39588v1 Announce Type: new Abstract: We push the frontier of large-scale spatial intelligence in Vision-Language Models (VLMs) and introduce the first benchmark that probes geographical la...
arXiv AI
Jun 2
Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation
arXiv:2606. 00095v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions.
arXiv AI
Aug 25
Geo-VLA: Geometry-Aware Vision-Language-Action Planning via Internalization of Map Semantics
arXiv:2608.21440v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have advanced end-to-end autonomous driving by leveraging foundation models for semantic reasoning and long-tail...
arXiv AI
Sep 10
AirAnchor: Bridging Local and Global Spatial Information for Zero-Shot Aerial Vision-and-Language Navigation
arXiv:2609.08442v1 Announce Type: cross Abstract: Aerial Vision-and-Language Navigation requires drones to follow natural-language instructions and navigate through complex urban environments. Accura...
arXiv AI
Jul 21
Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding
arXiv:2607. 17999v1 Announce Type: new Abstract: Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic information.