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README.md

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+---
+license: mit
+task_categories:
+  - question-answering
+language:
+  - en
+tags:
+  - geospatial
+  - gps
+  - benchmark
+  - geography
+  - spatial-reasoning
+  - coordinates
+size_categories:
+  - 10K<n<100K
+pretty_name: "GPSBench: GPS Reasoning Benchmark for LLMs"
+dataset_info:
+  - config_name: pure_gps
+    description: "Pure GPS track: coordinate manipulation tasks"
+  - config_name: applied
+    description: "Applied track: geographic reasoning tasks"
+---
+
+# GPSBench: Do Large Language Models Understand GPS Coordinates?
+
+GPSBench is a benchmark dataset of **57,800 samples** across **17 tasks** for evaluating geospatial reasoning in Large Language Models (LLMs).
+
+- **Paper**: [arXiv:2602.16105](https://arxiv.org/abs/2602.16105)
+- **Code**: [github.com/joey234/gpsbench](https://github.com/joey234/gpsbench)
+- **Leaderboard**: [gpsbench.github.io](https://gpsbench.github.io)
+
+## Benchmark Structure
+
+GPSBench is organized into two complementary evaluation tracks:
+
+### Pure GPS Track (9 tasks)
+Coordinate manipulation without geographic knowledge:
+- **Representation**: Format Conversion, Coordinate System Transformation
+- **Measurement**: Distance Calculation, Bearing Computation, Area & Perimeter
+- **Spatial Operations**: Coordinate Interpolation, Bounding Box, Route Geometry, Relative Position
+
+### Applied Track (9 tasks)
+Real-world geographic reasoning requiring world knowledge:
+- **Knowledge Retrieval**: Place Association, Name Disambiguation, Terrain Classification
+- **Spatial Reasoning**: Relative Position, Proximity & Nearest Neighbor, Boundary Analysis
+- **Pattern Analysis**: Route Analysis, Spatial Patterns, Missing Data Inference
+
+## Dataset Splits
+
+| Split | Ratio | Samples |
+|-------|-------|---------|
+| Train | 60%   | ~34,680 |
+| Dev   | 10%   | ~5,780  |
+| Test  | 30%   | ~17,340 |
+
+Each task contains approximately 3,400 samples (1,020 test).
+
+## Data Format
+
+Each sample is a JSON object containing:
+- `task`: Task identifier
+- `question`: Human-readable question/prompt
+- `ground_truth`: Expected answer with evaluation metrics
+- `coordinate(s)`: GPS coordinate data
+- `metadata`: Track, task description, and other context
+
+## Citation
+
+```bibtex
+@article{gpsbench2025,
+  title   = {GPSBench: Do Large Language Models Understand GPS Coordinates?},
+  author  = {Truong, Thinh Hung and Lau, Jey Han and Qi, Jianzhong},
+  journal = {arXiv preprint arXiv:2602.16105},
+  year    = {2025}
+}
+```