README.md

---
license: cc-by-2.0
dataset_info:
  features:
  - name: sample_id
    dtype: int32
  - name: task_instruction
    dtype: string
  - name: task_instance
    struct:
    - name: context
      dtype: string
    - name: images_path
      sequence: string
    - name: choice_list
      sequence: string
    - name: combined_1_images
      sequence: string
  - name: response
    dtype: string
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    num_examples: 200
  - name: ActionLocalization_adv
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    num_examples: 200
  - name: ActionPrediction_test
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  - name: ActionPrediction_adv
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    num_examples: 200
  - name: ActionSequence_test
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  - name: ActionSequence_adv
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  - name: ALFRED_test
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  - name: ALFRED_adv
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    num_examples: 200
  - name: CharacterOrder_test
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  - name: CharacterOrder_adv
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    num_examples: 200
  - name: CLEVR_Change_test
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    num_examples: 200
  - name: CLEVR_Change_adv
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  - name: CounterfactualInference_test
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  - name: CounterfactualInference_adv
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    num_examples: 200
  - name: DocVQA_test
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  - name: DocVQA_adv
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    num_examples: 200
  - name: EgocentricNavigation_test
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  - name: EgocentricNavigation_adv
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    num_examples: 200
  - name: GPR1200_test
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    num_examples: 600
  - name: IEdit_test
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    num_examples: 200
  - name: IEdit_adv
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    num_examples: 200
  - name: ImageNeedleInAHaystack_test
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    num_examples: 320
  - name: MMCoQA_test
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    num_examples: 200
  - name: MMCoQA_adv
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    num_examples: 200
  - name: MovingAttribute_test
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    num_examples: 200
  - name: MovingAttribute_adv
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    num_examples: 200
  - name: MovingDirection_test
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    num_examples: 200
  - name: MovingDirection_adv
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    num_examples: 200
  - name: MultiModalQA_test
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  - name: MultiModalQA_adv
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  - name: nuscenes_test
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    num_examples: 200
  - name: nuscenes_adv
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    num_examples: 200
  - name: ObjectExistence_test
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    num_examples: 200
  - name: ObjectExistence_adv
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    num_examples: 200
  - name: ObjectInteraction_test
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    num_examples: 200
  - name: ObjectInteraction_adv
    num_bytes: 264032
    num_examples: 200
  - name: ObjectShuffle_test
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    num_examples: 200
  - name: ObjectShuffle_adv
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    num_examples: 200
  - name: OCR_VQA_test
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    num_examples: 200
  - name: OCR_VQA_adv
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    num_examples: 200
  - name: SceneTransition_test
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    num_examples: 200
  - name: SceneTransition_adv
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    num_examples: 200
  - name: SlideVQA_test
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    num_examples: 200
  - name: SlideVQA_adv
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    num_examples: 200
  - name: Spot_the_Diff_test
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    num_examples: 200
  - name: Spot_the_Diff_adv
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    num_examples: 200
  - name: StateChange_test
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    num_examples: 200
  - name: StateChange_adv
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    num_examples: 200
  - name: TextNeedleInAHaystack_test
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    num_examples: 320
  - name: TQA_test
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    num_examples: 200
  - name: TQA_adv
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    num_examples: 200
  - name: WebQA_test
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  - name: WebQA_adv
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    num_examples: 200
  - name: WikiVQA_test
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    num_examples: 200
  - name: WikiVQA_adv
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    num_examples: 200
  download_size: 12035444
  dataset_size: 26288285
configs:
- config_name: default
  data_files:
  - split: ActionLocalization_test
    path: preview/ActionLocalization_test-*
  - split: ActionLocalization_adv
    path: preview/ActionLocalization_adv-*
  - split: ActionPrediction_test
    path: preview/ActionPrediction_test-*
  - split: ActionPrediction_adv
    path: preview/ActionPrediction_adv-*
  - split: ActionSequence_test
    path: preview/ActionSequence_test-*
  - split: ActionSequence_adv
    path: preview/ActionSequence_adv-*
  - split: ALFRED_test
    path: preview/ALFRED_test-*
  - split: ALFRED_adv
    path: preview/ALFRED_adv-*
  - split: CharacterOrder_test
    path: preview/CharacterOrder_test-*
  - split: CharacterOrder_adv
    path: preview/CharacterOrder_adv-*
  - split: CLEVR_Change_test
    path: preview/CLEVR_Change_test-*
  - split: CLEVR_Change_adv
    path: preview/CLEVR_Change_adv-*
  - split: CounterfactualInference_test
    path: preview/CounterfactualInference_test-*
  - split: CounterfactualInference_adv
    path: preview/CounterfactualInference_adv-*
  - split: DocVQA_test
    path: preview/DocVQA_test-*
  - split: DocVQA_adv
    path: preview/DocVQA_adv-*
  - split: EgocentricNavigation_test
    path: preview/EgocentricNavigation_test-*
  - split: EgocentricNavigation_adv
    path: preview/EgocentricNavigation_adv-*
  - split: GPR1200_test
    path: preview/GPR1200_test-*
  - split: IEdit_test
    path: preview/IEdit_test-*
  - split: IEdit_adv
    path: preview/IEdit_adv-*
  - split: ImageNeedleInAHaystack_test
    path: preview/ImageNeedleInAHaystack_test-*
  - split: MMCoQA_test
    path: preview/MMCoQA_test-*
  - split: MMCoQA_adv
    path: preview/MMCoQA_adv-*
  - split: MovingAttribute_test
    path: preview/MovingAttribute_test-*
  - split: MovingAttribute_adv
    path: preview/MovingAttribute_adv-*
  - split: MovingDirection_test
    path: preview/MovingDirection_test-*
  - split: MovingDirection_adv
    path: preview/MovingDirection_adv-*
  - split: MultiModalQA_test
    path: preview/MultiModalQA_test-*
  - split: MultiModalQA_adv
    path: preview/MultiModalQA_adv-*
  - split: nuscenes_test
    path: preview/nuscenes_test-*
  - split: nuscenes_adv
    path: preview/nuscenes_adv-*
  - split: ObjectExistence_test
    path: preview/ObjectExistence_test-*
  - split: ObjectExistence_adv
    path: preview/ObjectExistence_adv-*
  - split: ObjectInteraction_test
    path: preview/ObjectInteraction_test-*
  - split: ObjectInteraction_adv
    path: preview/ObjectInteraction_adv-*
  - split: ObjectShuffle_test
    path: preview/ObjectShuffle_test-*
  - split: ObjectShuffle_adv
    path: preview/ObjectShuffle_adv-*
  - split: OCR_VQA_test
    path: preview/OCR_VQA_test-*
  - split: OCR_VQA_adv
    path: preview/OCR_VQA_adv-*
  - split: SceneTransition_test
    path: preview/SceneTransition_test-*
  - split: SceneTransition_adv
    path: preview/SceneTransition_adv-*
  - split: SlideVQA_test
    path: preview/SlideVQA_test-*
  - split: SlideVQA_adv
    path: preview/SlideVQA_adv-*
  - split: Spot_the_Diff_test
    path: preview/Spot_the_Diff_test-*
  - split: Spot_the_Diff_adv
    path: preview/Spot_the_Diff_adv-*
  - split: StateChange_test
    path: preview/StateChange_test-*
  - split: StateChange_adv
    path: preview/StateChange_adv-*
  - split: TextNeedleInAHaystack_test
    path: preview/TextNeedleInAHaystack_test-*
  - split: TQA_test
    path: preview/TQA_test-*
  - split: TQA_adv
    path: preview/TQA_adv-*
  - split: WebQA_test
    path: preview/WebQA_test-*
  - split: WebQA_adv
    path: preview/WebQA_adv-*
  - split: WikiVQA_test
    path: preview/WikiVQA_test-*
  - split: WikiVQA_adv
    path: preview/WikiVQA_adv-*
task_categories:
- visual-question-answering
- question-answering
- text-generation
- image-to-text
- video-classification
language:
- en
tags:
- Long-context
- MLLM
- VLM
- LLM
- Benchmark
pretty_name: MileBench
size_categories:
- 1K<n<10K
---


# MileBench

## Introduction

We introduce MileBench, a pioneering benchmark designed to test the **M**ult**I**modal **L**ong-cont**E**xt capabilities of MLLMs. 
This benchmark comprises not only multimodal long contexts, but also multiple tasks requiring both comprehension and generation. 
We establish two distinct evaluation sets, diagnostic and realistic, to systematically assess MLLMs’ long-context adaptation capacity and their ability to completetasks in long-context scenarios

 <img src="./images/MileBench.png" width="600" alt="MileBench" align="center" />

To construct our evaluation sets, we gather 6,440 multimodal long-context samples from 21 pre-existing or self-constructed datasets, 
with an average of 15.2 images and 422.3 words each, as depicted in the figure, and we categorize them into their respective subsets.
<center class="half">
  <img src="./images/stat2.png" width="300" alt="stat2"/><img src="./images/stat1.png" width="300" alt="stat1"/>
</center>

## How to use?

Please download MileBench.tar.gz and refer to [Code for MileBench](https://github.com/MileBench/MileBench?tab=readme-ov-file#-dataset-preparation).

## Links

- **Homepage:** [MileBench Homepage](https://milebench.github.io/)
- **Repository:** [MileBench GitHub](https://github.com/MileBench/MileBench)
- **Paper:** [Arxiv](https://arxiv.org/abs/2404.18532)
- **Point of Contact:** [Dingjie Song](mailto:bbsngg@outlook.com)

## Citation

If you find this project useful in your research, please consider cite:
```BibTeX
@misc{song2024milebench,
  title={MileBench: Benchmarking MLLMs in Long Context},
  author={Dingjie Song and Shunian Chen and Guiming Hardy Chen and Fei Yu and Xiang Wan and Benyou Wang},
  year={2024},
  eprint={2404.18532},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

@article{song2024milebench,
  title={MileBench: Benchmarking MLLMs in Long Context},
  author={Song, Dingjie and Chen, Shunian and Chen, Guiming Hardy and Yu, Fei and Wan, Xiang and Wang, Benyou},
  journal={arXiv preprint arXiv:2404.18532},
  year={2024}
}
```