---
license: apache-2.0
---

# Dataset Card for MultiVENT 2.0

<!-- Provide a quick summary of the dataset. -->

This dataset card provides details about **MultiVENT 2.0**, a large-scale, multi-lingual event-centric video retrieval benchmark featuring a collection of more than 218,000 news videos and over 3,900 queries targeting specific world events.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

**MultiVENT 2.0** consists over 218,000 videos, with 108,500 videos for training (**MultiVENT Train**) and 109,800 for testing **MultiVENT Test**.

The collection contains all 2,400 videos from original **MultiVENT** dataset, a carefully curated set of **M**ultilingual **V**ideos of **E**vents with aligned **N**atural **T**ext, augmented with a subset of videos from **Internvid**, a corpus containing more than seven million YouTube videos and over 760,000 hours of content.

- **Created by:** The Human Language Technology Center of Excellence and Johns Hopkins University
- **Language(s) (NLP):** Arabic, Chinese, English, Korean, Russian, Spanish
- **License:** apache-2.0

### Download instructions

The dataset can be found on huggingface. However, you can't use the datasets library to access the videos because everything is tarred. Instead you need to locally download the dataset and then untar the videos (and audios if you use those).

#### Step 1: Install git-lfs

The first thing you need to do is make sure that git-lfs is installed, otherwise you won't be able to pull the video and audio tar files.

git lfs install

#### Step 2: Clone the dataset

After enabling git-lfs, you can now pull the dataset from huggingface.

git clone https://huggingface.co/datasets/hltcoe/MultiVENT2.0

Using tmux is recommended, as downloading all videos will take a while.

### Dataset Sources

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- **Repository:** https://github.com/katesanders9/multiVENT
- **Paper:** https://arxiv.org/abs/2410.11619
- **Workshop on Multimodal Augmented Generation via Multimodal Retreival (MAGMaR):** https://nlp.jhu.edu/magmar/

### Evaluation On Test Set (**UPDATED 8/6**)

The relevance judgments for the final corpus are provided in *multivent_2_test_judgments.jsonl*. Several example ranked lists of the baseline systems are also provided in the folder titled *ranked_lists/*.

The formal evaluation script is *evaluate_multivent_test.py*, note that you will need to install the *ir_measures* and *numpy* packages.

```
## Example call using a baseline ranked list
python evaluate_multivent_test.py \
-test_annotation_file multivent_2_test_judgments.jsonl \
-user_annotation_file ranked_lists/10pyscene_clip.json
```

## Citations

If publishing work using this dataset, please be sure to cite the following works:

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

```
@misc{kriz2025multivent20massivemultilingual,
      title={MultiVENT 2.0: A Massive Multilingual Benchmark for Event-Centric Video Retrieval}, 
      author={Reno Kriz and Kate Sanders and David Etter and Kenton Murray and Cameron Carpenter and Kelly Van Ochten and Hannah Recknor and Jimena Guallar-Blasco and Alexander Martin and Ronald Colaianni and Nolan King and Eugene Yang and Benjamin Van Durme},
      year={2025},
      eprint={2410.11619},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2410.11619}, 
}
```

```
@misc{sanders2023multiventmultilingualvideosevents,
      title={MultiVENT: Multilingual Videos of Events with Aligned Natural Text}, 
      author={Kate Sanders and David Etter and Reno Kriz and Benjamin Van Durme},
      year={2023},
      eprint={2307.03153},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2307.03153}, 
}
```

## Dataset Card Contact

Please feel free to reach out to the MAGMaR Workshop organizers for any questions/comments: magmar@lists.jh.edu.