Datasets:
metadata
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
- Repository: 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:
@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}
}