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  - es
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  size_categories:
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  - 1K<n<10K
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - es
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  size_categories:
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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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+
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+ <a href="FIXME" 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](FIXME).
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+
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+ ## Dataset Description
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+ 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.
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+ 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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+
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+ The dataset contains the following fields:
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+
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+ | Field Name | Description |
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+ | :----------------------- | :-------------------------------------------------------------------------- |
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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. |
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+ | `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:
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+ | File Name | Description |
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+ | :-------------------- | :---------------------------------------------------------------------- |
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+ | `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
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+ 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
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+
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+ ```bibtex
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+ FIXME
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+ ```