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--- |
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dataset_info: |
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features: |
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- name: landmark_id |
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dtype: int64 |
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- name: country_code |
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dtype: string |
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|
- name: domestic_language_code |
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dtype: string |
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|
- name: language_code |
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|
dtype: string |
|
|
- name: landmark_name |
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dtype: string |
|
|
- name: prompt_idx |
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dtype: int64 |
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splits: |
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|
- name: test |
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num_bytes: 470104 |
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num_examples: 8100 |
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|
- name: debug |
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|
num_bytes: 548 |
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num_examples: 10 |
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download_size: 80893 |
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dataset_size: 470652 |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: data/test-* |
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- split: debug |
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path: data/debug-* |
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license: cc |
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task_categories: |
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- text-generation |
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language: |
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- ar |
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- zh |
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- en |
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|
- fr |
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|
- de |
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|
- it |
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|
- ja |
|
|
- pt |
|
|
- es |
|
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size_categories: |
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|
- 1K<n<10K |
|
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tags: |
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|
- Image |
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|
- Text |
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|
- Multilingual |
|
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--- |
|
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|
|
|
|
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|
<a href="https://arxiv.org/abs/2505.15075" target="_blank"> |
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<img alt="arXiv" src="https://img.shields.io/badge/arXiv-traveling--across--languages-red?logo=arxiv" height="20" /> |
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</a> |
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|
<a href="https://github.com/nlp-waseda/traveling-across-languages" target="_blank" style="display: inline-block; margin-right: 10px;"> |
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<img alt="GitHub Code" src="https://img.shields.io/badge/Code-traveling--across--languages-white?&logo=github&logoColor=white" /> |
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</a> |
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|
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# VisRecall |
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|
This repository contains the VisRecall benchmark, introduced in [Traveling Across Languages: Benchmarking Cross-Lingual Consistency in Multimodal LLMs](https://arxiv.org/abs/2505.15075). |
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|
|
|
## Dataset Description |
|
|
Imagine a tourist finished their journey in Japan and came back to France, eager to share the places they visited with their friends. |
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|
When portraying these experiences, the visual information they convey is inherently independent of language, meaning that descriptions created in different languages should ideally be highly similar. |
|
|
This concept extends to MLLMs as well. |
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|
While a model may demonstrate decent consistency in VQA tasks, any inconsistency in generation tasks would lead to a biased user experience (i.e., a knowing vs saying distinction). |
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|
To assess the cross-lingual consistency of "visual memory" in MLLMs, we introduce VisRecall, a multilingual benchmark designed to evaluate visual description generation across 450 landmarks in 9 languages. |
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|
|
|
|
The dataset contains the following fields: |
|
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|
|
|
| Field Name | Description | |
|
|
| :----------------------- | :-------------------------------------------------------------------------- | |
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|
| `landmark_id` | Unique identifier for the landmark in the dataset. | |
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|
| `domestic_language_code` | ISO 639 language code of the official language spoken in the country where the landmark is located. | |
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|
| `language_code` | ISO 639 language code of the prompt. | |
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|
| `country_code` | ISO country code representing the location of the landmark. | |
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|
| `landmark_name` | Name of the landmark used for evaluation. | |
|
|
| `prompt_idx` | Index of the prompt used. Each language includes two distinct prompts. | |
|
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|
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|
Additionally, the following files are necessary for running evalutaion: |
|
|
| File Name | Description | |
|
|
| :-------------------- | :---------------------------------------------------------------------- | |
|
|
| `images.tar.gz` | Compressed archive containing images of landmarks, used for CLIPScore calculation. | |
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|
| `images_list.json` | List of image file paths included in the dataset. | |
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|
| `landmark_list.json` | Metadata for each landmark, including IDs, names, etc. | |
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|
|
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## Evaluation |
|
|
Please refer to our [GitHub repository](https://github.com/nlp-waseda/traveling-across-languages) for detailed information on the evaluation setup. |
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|
|
|
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## Citation |
|
|
|
|
|
```bibtex |
|
|
@misc{wang2025travelinglanguagesbenchmarkingcrosslingual, |
|
|
title={Traveling Across Languages: Benchmarking Cross-Lingual Consistency in Multimodal LLMs}, |
|
|
author={Hao Wang and Pinzhi Huang and Jihan Yang and Saining Xie and Daisuke Kawahara}, |
|
|
year={2025}, |
|
|
eprint={2505.15075}, |
|
|
archivePrefix={arXiv}, |
|
|
primaryClass={cs.CL}, |
|
|
url={https://arxiv.org/abs/2505.15075}, |
|
|
} |
|
|
``` |
