--- license: other license_name: openearthmap-derived-mixed-source-dataset-license license_link: LICENSE pretty_name: NeSy-Route task_categories: - image-to-text - visual-question-answering language: - en tags: - remote-sensing - route-planning - benchmark - neural-symbolic - multimodal-large-language-models ---

NeSy-Route Dataset

A neural-symbolic benchmark for constrained route planning in remote-sensing imagery.

Project Page Project Page   |   arXiv Paper   |   GitHub Code

## Dataset Composition NeSy-Route is organized into three benchmark tasks for evaluating perception, symbolic reasoning, and constrained route planning over remote-sensing imagery. | Task | Setting | What It Evaluates | Split / Level | Samples | | --- | --- | --- | --- | ---: | | Task 1 | Few-shot | Semantic traversability and cost-vector prediction | Main set | 3,607 | | Task 2 | Zero-shot | Constraint-aware semantic and region reasoning | Level 1 | 7,659 | | Task 2 | Zero-shot | Constraint-aware semantic and region reasoning | Level 2 | 3,712 | | Task 2 | Zero-shot | Constraint-aware semantic and region reasoning | Level 3 | 1,604 | | Task 2 | Zero-shot | Constraint-aware semantic and region reasoning | Total | 12,975 | | Task 3 | Zero-shot | Constrained route planning with waypoint or trajectory outputs | Easy | 6,492 | | Task 3 | Zero-shot | Constrained route planning with waypoint or trajectory outputs | Medium | 2,705 | | Task 3 | Zero-shot | Constrained route planning with waypoint or trajectory outputs | Hard | 1,624 | | Task 3 | Zero-shot | Constrained route planning with waypoint or trajectory outputs | Total | 10,821 | Task 1 and Task 2 provide semantic constraint annotations for vector-based reasoning. Task 3 provides route-planning samples together with traversability maps, cost maps, ground-truth paths, and difficulty-level subsets. ## Evaluation Code Evaluation scripts, prompt templates, and running instructions are available in the GitHub repository: ## License NeSy-Route follows the same licensing policy as OpenEarthMap. Label data are released under the same license as the corresponding source RGB imagery when applicable. For data whose source imagery is public domain or whose license is otherwise unspecified, the released labels follow the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)**. Please also check the `LICENSE` file in this repository before using or redistributing the dataset.