Datasets:
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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
```
@article{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},
journal={Transactions on Machine Learning Research},
year={2024},
volume={2024},
url={https://openreview.net/forum?id=skLtdUVaJa}
}
```
|