Datasets:
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README.md
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XModBench is a comprehensive benchmark designed to evaluate the cross-modal capabilities and consistency of omni-language models. It systematically assesses model performance across multiple modalities (text, vision, audio) and various cognitive tasks, revealing critical gaps in current state-of-the-art models.
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- [x] Release data evaluation code
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**Note**: XModBench is actively maintained and regularly updated with new models and evaluation metrics. For the latest updates, please check our [releases](https://github.com/XingruiWang/XModBench/releases) page.
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---
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license: apache-2.0
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task_categories:
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- multiple-choice
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language:
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- en
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- zh
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tags:
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- audio-visual
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- omnimodality
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- multi-modality
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- benchmark
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pretty_name: 'XModBench '
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size_categories:
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- 10K<n<100K
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---
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<h1 align="center">
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XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models
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</h1>
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<p align="center">
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<img src="https://xingruiwang.github.io/projects/XModBench/static/images/teaser.png" width="90%" alt="XModBench teaser">
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</p>
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<p align="center">
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<a href="https://arxiv.org/abs/2510.15148">
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<img src="https://img.shields.io/badge/Paper-arXiv-red.svg" alt="Paper">
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</a>
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<a href="https://xingruiwang.github.io/projects/XModBench/">
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<img src="https://img.shields.io/badge/Website-XModBench-0a7aca?logo=globe&logoColor=white" alt="Website">
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</a>
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<a href="https://huggingface.co/datasets/RyanWW/XModBench">
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<img src="https://img.shields.io/badge/Dataset-XModBench-FFD21E?logo=huggingface" alt="Dataset">
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</a>
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<a href="https://github.com/XingruiWang/XModBench">
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<img src="https://img.shields.io/badge/Code-XModBench-181717?logo=github&logoColor=white" alt="GitHub Repo">
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</a>
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<a href="https://opensource.org/licenses/MIT">
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<img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT">
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</a>
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</p>
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XModBench is a comprehensive benchmark designed to evaluate the cross-modal capabilities and consistency of omni-language models. It systematically assesses model performance across multiple modalities (text, vision, audio) and various cognitive tasks, revealing critical gaps in current state-of-the-art models.
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- [x] Release data evaluation code
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---
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**Note**: XModBench is actively maintained and regularly updated with new models and evaluation metrics. For the latest updates, please check our [releases](https://github.com/XingruiWang/XModBench/releases) page.
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