Thyme
Collection
Think Beyond Images
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5 items
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Updated
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2
[📊 Thyme SFT Model] [📊 Thyme RL Model] [📝 SFT Data] [📝 RL Data]
2025.08.15
🌟 We are excited to introduce Thyme: Think Beyond Images. Thyme transcends traditional ``thinking with images'' paradigms by autonomously generating and executing diverse image processing and computational operations through executable code, significantly enhancing performance on high-resolution perception and complex reasoning tasks. Leveraging a novel two-stage training strategy that combines supervised fine-tuning with reinforcement learning and empowered by the innovative GRPO-ATS algorithm, Thyme achieves a sophisticated balance between reasoning exploration and code execution precision.We have provided the usage instructions, training code, and evaluation code in the GitHub repo.
If you find Thyme useful in your research or applications, please cite our paper:
@misc{zhang2025thymethinkimages,
title={Thyme: Think Beyond Images},
author={Yi-Fan Zhang and Xingyu Lu and Shukang Yin and Chaoyou Fu and Wei Chen and Xiao Hu and Bin Wen and Kaiyu Jiang and Changyi Liu and Tianke Zhang and Haonan Fan and Kaibing Chen and Jiankang Chen and Haojie Ding and Kaiyu Tang and Zhang Zhang and Liang Wang and Fan Yang and Tingting Gao and Guorui Zhou},
year={2025},
eprint={2508.11630},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2508.11630},
}
Base model
Qwen/Qwen2.5-VL-7B-Instruct