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  Building upon on our original [**MMEB**](https://arxiv.org/abs/2410.05160), **MMEB-V2** expands the evaluation scope to include five new tasks: four video-based tasks — Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval. This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings.
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- **This Hugging Face repository contains only the raw image and video files used in MMEB-V2, which need to be downloaded in advance.**
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- The test data for each task in MMEB-V2 is available [here](https://huggingface.co/VLM2Vec) and will be automatically downloaded and used by our code. More details on how to set it up are provided in the following sections.
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  ## 🚀 What's New
 
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  Building upon on our original [**MMEB**](https://arxiv.org/abs/2410.05160), **MMEB-V2** expands the evaluation scope to include five new tasks: four video-based tasks — Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval. This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings.
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+ **This Hugging Face repository contains only the image and video files used in MMEB-V2, which need to be downloaded in advance.**
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+ **For the video component, please note that this repository contains both sampled frames and raw videos. Typically, the sampled frames are sufficient for use with our evaluation suite. However, we’ve also included the raw videos to accommodate any specific needs from users. If you prefer not to download the large raw video files, please use ```git lfs``` carefully.**
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+ The test data for each task in MMEB-V2 is available [here](https://huggingface.co/VLM2Vec) and will be automatically downloaded and used by our code.
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  ## 🚀 What's New