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---
language:
- en
license: apache-2.0
size_categories:
- n<1K
task_categories:
- question-answering
pretty_name: Mantis-Eval
dataset_info:
- config_name: mantis_eval
  features:
  - name: id
    dtype: string
  - name: question_type
    dtype: string
  - name: question
    dtype: string
  - name: images
    sequence: image
  - name: options
    sequence: string
  - name: answer
    dtype: string
  - name: data_source
    dtype: string
  - name: category
    dtype: string
  splits:
  - name: test
    num_bytes: 479770102
    num_examples: 217
  download_size: 473031413
  dataset_size: 479770102
configs:
- config_name: mantis_eval
  data_files:
  - split: test
    path: mantis_eval/test-*
---

## Overview
This is a newly curated dataset to evaluate multimodal language models' capability to reason over multiple images. More details are shown in https://tiger-ai-lab.github.io/Mantis/. 

### Statistics
This evaluation dataset contains 217 human-annotated challenging multi-image reasoning problems.

### Leaderboard
We list the current results as follows:

| Models            | Size | Mantis-Eval |
|:------------------|:-----|:------------|
| LLaVA OneVision   | 72B  | 77.60       |
| LLaVA OneVision   | 7B   | 64.20       |
| GPT-4V            | -    | 62.67       |
| Mantis-SigLIP     | 8B   | 59.45       |
| Mantis-Idefics2   | 8B   | 57.14       |
| Mantis-CLIP       | 8B   | 55.76       |
| VILA              | 8B   | 51.15       |
| BLIP-2            | 13B  | 49.77       |
| Idefics2          | 8B   | 48.85       |
| InstructBLIP      | 13B  | 45.62       |
| LLaVA-V1.6        | 7B   | 45.62       |
| CogVLM            | 17B  | 45.16       |
| LLaVA OneVision   | 0.5B | 39.60       |
| Qwen-VL-Chat      | 7B   | 39.17       |
| Emu2-Chat         | 37B  | 37.79       |
| VideoLLaVA        | 7B   | 35.04       |
| Mantis-Flamingo   | 9B   | 32.72       |
| LLaVA-v1.5        | 7B   | 31.34       |
| Kosmos2           | 1.6B | 30.41       |
| Idefics1          | 9B   | 28.11       |
| Fuyu              | 8B   | 27.19       |
| OpenFlamingo      | 9B   | 12.44       |
| Otter-Image       | 9B   | 14.29       |

### Citation
If you are using this dataset, please cite our work with
```
@inproceedings{Jiang2024MANTISIM,
  title={MANTIS: Interleaved Multi-Image Instruction Tuning},
  author={Dongfu Jiang and Xuan He and Huaye Zeng and Cong Wei and Max W.F. Ku and Qian Liu and Wenhu Chen},
  publisher={arXiv2405.01483}
  year={2024},
}
```