---
task_categories:
- image-text-to-text
- video-text-to-text
- audio-text-to-text
---

# ThinkOmni Evaluation Dataset

This repository contains the evaluation datasets for **ThinkOmni**, a training-free framework that lifts textual reasoning to omni-modal scenarios via guidance decoding.

ThinkOmni enhances omni-modal large language models (OLLMs) with the reasoning capabilities of large reasoning models (LRMs) at decoding time, adaptively balancing perception and reasoning signals.

- **Paper:** [ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding](https://huggingface.co/papers/2602.23306)
- **Repository:** [https://github.com/1ranGuan/thinkomni](https://github.com/1ranGuan/thinkomni)

### Dataset Contents

This collection includes the following evaluation sets used in the paper:
- **MMAU**
- **OmniBench**
- **Daily-Omni**

### Citation

If you find this work or these datasets useful, please cite:

```bibtex
@inproceedings{guan2026thinkomni,
  title={ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding},
  author={Guan, Yiran and Tu, Sifan and Liang, Dingkang and Zhu, Linghao and Ju, Jianzhong and Luo, Zhenbo and Luan, Jian and Liu, Yuliang and Bai, Xiang},
  booktitle={International Conference on Learning Representations (ICLR)},
  year={2026}
}
```