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---
task_categories:
- image-text-to-text
- video-text-to-text
- object-detection
- image-segmentation
language:
- en
---
This repository contains the **evaluation data** presented in: [OneThinker: All-in-one Reasoning Model for Image and Video](https://arxiv.org/abs/2512.03043)
Code: https://github.com/tulerfeng/OneThinker
## About OneThinker
<div align="center">
<img src="https://github.com/tulerfeng/OneThinker/blob/main/assets/teaser.png?raw=true" alt="OneThinker Teaser" width="95%">
</div>
We introduce **OneThinker**, an all-in-one multimodal reasoning generalist that is **capable of thinking across a wide range of fundamental visual tasks within a single model**.
We construct the large-scale **OneThinker-600k** multi-task training corpus and build **OneThinker-SFT-340k** with high-quality CoT annotations for cold-start SFT. Moreover, we propose **EMA-GRPO**, a new RL method that **balances heterogeneous reward signals across diverse visual tasks**, via simply tracking task-wise moving averages of reward std.
OneThinker demonstrates **strong performance on 31 benchmarks across 10 fundamental vision tasks**, while showing cross-task knowledge transfer and promising zero-shot generalization toward a **unified multimodal reasoning generalist**.
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