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---
license: apache-2.0
task_categories:
- question-answering
- multiple-choice
language:
- en
size_categories:
- n<1K
configs:
- config_name: benchmark
data_files:
- split: test
path: dataset.json
paperswithcode_id: mapeval-api
tags:
- geospatial
---
# MapEval-API
[MapEval](https://arxiv.org/abs/2501.00316)-API is created using [MapQaTor](https://arxiv.org/abs/2412.21015).
# Usage
```python
from datasets import load_dataset
# Load dataset
ds = load_dataset("MapEval/MapEval-API", name="benchmark")
# Generate better prompts
for item in ds["test"]:
# Start with a clear task description
prompt = (
"You are a highly intelligent assistant. "
"Answer the multiple-choice question by selecting the correct option.\n\n"
"Question:\n" + item["question"] + "\n\n"
"Options:\n"
)
# List the options more clearly
for i, option in enumerate(item["options"], start=1):
prompt += f"{i}. {option}\n"
# Add a concluding sentence to encourage selection of the answer
prompt += "\nSelect the best option by choosing its number."
# Use the prompt as needed
print(prompt) # Replace with your processing logic
```
## Leaderboard
| Model | Overall | Place Info | Nearby | Routing | Trip | Unanswerable |
|---------------------|:---------:|:------------:|:--------:|:---------:|:--------:|:--------------:|
| Claude-3.5-Sonnet | **64.00** | **68.75** | **55.42** | **65.15** | **71.64** | 55.00 |
| GPT-4-Turbo | 53.67 | 62.50 | 50.60 | 60.61 | 50.75 | 25.00 |
| GPT-4o | 48.67 | 59.38 | 40.96 | 50.00 | 56.72 | 15.00 |
| Gemini-1.5-Pro | 43.33 | 65.63 | 30.12 | 40.91 | 34.33 | **65.00** |
| Gemini-1.5-Flash | 41.67 | 51.56 | 38.55 | 46.97 | 34.33 | 30.00 |
| GPT-3.5-Turbo | 27.33 | 39.06 | 22.89 | 33.33 | 19.40 | 15.00 |
| GPT-4o-mini | 23.00 | 28.13 | 14.46 | 13.64 | 43.28 | 5.00 |
| Llama-3.2-90B | 39.67 | 54.69 | 37.35 | 39.39 | 35.82 | 15.00 |
| Llama-3.1-70B | 37.67 | 53.13 | 32.53 | 42.42 | 31.34 | 15.00 |
| Mixtral-8x7B | 27.67 | 32.81 | 18.07 | 27.27 | 38.81 | 15.00 |
| Gemma-2.0-9B | 27.00 | 35.94 | 14.46 | 28.79 | 26.87 | 45.00 |
#### Comparison between ReAct and Chameleon with GPT-3.5-Turbo
| Model | Overall | Place Info | Nearby | Routing | Trip | Unanswerable |
|----------------------------|:-------:|:----------:|:------:|:-------:|:------:|:------------:|
| ReAct | 27.33 | 39.06 | 22.89 | 33.33 | 19.40 | 15.00 |
| Chameleon | 49.33 | 54.69 | 54.21 | 51.51 | 43.28 | 25.00 |
## Citation
If you use this dataset, please cite the original paper:
```
@article{dihan2024mapeval,
title={MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models},
author={Dihan, Mahir Labib and Hassan, Md Tanvir and Parvez, Md Tanvir and Hasan, Md Hasebul and Alam, Md Almash and Cheema, Muhammad Aamir and Ali, Mohammed Eunus and Parvez, Md Rizwan},
journal={arXiv preprint arXiv:2501.00316},
year={2024}
}
``` |