Kun Xiang

Shenzhen, China

Thanks for stopping by! 👋

I am currently a PhD student at the HCP-I2 Lab in Sun Yat-sen University advised by Prof. Xiaodan Liang. Previously, I obtained both my Bachelor’s and Master’s degree at SYSU under the supervision of Prof. Shancheng Jiang.

Currently, I am interested in building generalizable multimodal reasoning systems grounded in data-centric perspective. I am working to answer:

1) Inward: How can MLLMs enhance perception and reasoning for real-world comprehension?

2) Outward: How can MLLMs enable modeling and interaction for physical engagement?

Feel free to reach out at xiangk123@gmail.com to discuss potential collaboration.

news

Oct 6, 2025	🔥 We release a survey to aligning perception, reasoning, modeling and interaction capabilities on physical AI!
Sep 19, 2025	One paper accepted by NeurIPS 2025!
May 21, 2025	🔥 We release the paper of SeePhys. It is a full spectrum multimodal benchmark for evaluating physics reasoning across different knowledge levels!
May 21, 2025	🎉 SeePhys is officially open for challenges at the 2nd AI for Math Workshop at ICML 2025!
Mar 8, 2025	We announce AtomThink, a novel slow thinking framework for multimodal mathematical reasoning task!

selected publications

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI

Kun Xiang, Terry Jingchen Zhang, Yinya Huang, Jixi He, and 12 more authors

https://arxiv.org/abs/2510.04978, 2025

Bib HTML Code

@article{Xiang2025AligningPR,
  title = {Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI},
  author = {Xiang, Kun and Zhang, Terry Jingchen and Huang, Yinya and He, Jixi and Liu, Zirong and Tang, Yueling and Zhou, Ruizhe and Luo, Lijing and Wen, Youpeng and Chen, Xiuwei and Lin, Bingqian and Han, Jianhua and Xu, Hang and Li, Hanhui and Dong, Bin and Liang, Xiaodan},
  journal = {https://arxiv.org/abs/2510.04978},
  year = {2025},
}

SeePhys: Does Seeing Help Thinking? – Benchmarking Vision-Based Physics Reasoning

Kun Xiang, Heng Li, Terry Jingchen Zhang, Yinya Huang, and 10 more authors

arxiv.org/pdf/2505.19099v1, 2025

Bib HTML Code

@article{xiang2025seephys,
  title = {SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning},
  author = {Xiang, Kun and Li, Heng and Zhang, Terry Jingchen and Huang, Yinya and Liu, Zirong and Qu, Peixin and He, Jixi and Chen, Jiaqi and Yu-Jie, Yuan and Han, Jianhua and Xu, Hang and Li, Hanhui and Sachan, Mrinmaya and Liang, Xiaodan},
  journal = {arxiv.org/pdf/2505.19099v1},
  year = {2025},
  huggingface = {https://huggingface.co/datasets/SeePhys/SeePhys},
}

AtomThink: Multimodal Slow Thinking with Atomic Step Reasoning

Kun Xiang, Zhili Liu, Terry Jingchen Zhang, Yinya Huang, and 6 more authors

arXiv preprint arXiv:2411.11930, 2025

Bib HTML PDF Code

@article{xiang2025can,
  title = {AtomThink: Multimodal Slow Thinking with Atomic Step Reasoning},
  author = {Xiang, Kun and Liu, Zhili and Zhang, Terry Jingchen and Huang, Yinya and Nie, Yunshuang and Cai, Kaixin and Yin, Yiyang and Huang, Runhui and Li, Hanhui and and others},
  journal = {arXiv preprint arXiv:2411.11930},
  year = {2025},
}

Toward robust diagnosis: A contour attention preserving adversarial defense for covid-19 detection

Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu, and 3 more authors

In Proceedings of the AAAI Conference on Artificial Intelligence, 2023

Bib HTML Code

@inproceedings{xiang2023toward,
  title = {Toward robust diagnosis: A contour attention preserving adversarial defense for covid-19 detection},
  author = {Xiang, Kun and Zhang, Xing and She, Jinwen and Liu, Jinpeng and Wang, Haohan and Deng, Shiqi and Jiang, Shancheng},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {37},
  number = {3},
  pages = {2928--2937},
  year = {2023},
}

A novel weight pruning strategy for light weight neural networks with application to the diagnosis of skin disease

Kun Xiang, Linlin Peng, Haiqiong Yang, Mingxin Li, and 3 more authors

Applied Soft Computing, 2021

Bib PDF

@article{xiang2021novel,
  title = {A novel weight pruning strategy for light weight neural networks with application to the diagnosis of skin disease},
  author = {Xiang, Kun and Peng, Linlin and Yang, Haiqiong and Li, Mingxin and Cao, Zhongfa and Jiang, Shancheng and Qu, Gang},
  journal = {Applied Soft Computing},
  volume = {111},
  pages = {107707},
  year = {2021},
  publisher = {Elsevier},
}