Xiaoxiao Saxon Li

selected publications [view all]

1. ICLR

   Gmvaluator: Similarity-based data valuation for generative models

   Jiaxi Yang, Wenglong Deng, Benlin Liu, Yangsibo Huang, James Zou, and Xiaoxiao Li

   International Conference on Learning Representations, 2025

   Bib PDF Code

   @article{yang2025gmvaluator,
     title = {Gmvaluator: Similarity-based data valuation for generative models},
     author = {Yang, Jiaxi and Deng, Wenglong and Liu, Benlin and Huang, Yangsibo and Zou, James and Li, Xiaoxiao},
     journal = {International Conference on Learning Representations},
     year = {2025},
   }

2. ICLR

   Can Textual Gradient Work in Federated Learning?

   Minghui Chen, Ruinan Jin, Wenlong Deng, Yuanyuan Chen, Zhi Huang, Han Yu, and Xiaoxiao Li

   International Conference on Learning Representations, 2025

   Bib PDF

   @article{chen2025can,
     title = {Can Textual Gradient Work in Federated Learning?},
     author = {Chen, Minghui and Jin, Ruinan and Deng, Wenlong and Chen, Yuanyuan and Huang, Zhi and Yu, Han and Li, Xiaoxiao},
     journal = {International Conference on Learning Representations},
     year = {2025},
   }

3. ICLR

   S4M: S4 for multivariate time series forecasting with Missing values

   Peng Jing, Meiqi Yang, Qiong Zhang, and Xiaoxiao Li

   International Conference on Learning Representations, 2025

   Bib PDF Code

   @article{peng2025s4,
     title = {S4M: S4 for multivariate time series forecasting with Missing values},
     author = {Jing, Peng and Yang, Meiqi and Zhang, Qiong and Li, Xiaoxiao},
     journal = {International Conference on Learning Representations},
     year = {2025},
   }

4. NeurIPS

   FairMedFM: fairness benchmarking for medical imaging foundation models

   Ruinan Jin, Zikang Xu, Yuan Zhong, Qiongsong Yao, Qi Dou, S Kevin Zhou, and Xiaoxiao Li

   Advances in Neural Information Processing Systems, 2024

   Bib PDF Code

   @article{jin2024fairmedfm,
     title = {FairMedFM: fairness benchmarking for medical imaging foundation models},
     author = {Jin, Ruinan and Xu, Zikang and Zhong, Yuan and Yao, Qiongsong and Dou, Qi and Zhou, S Kevin and Li, Xiaoxiao},
     journal = {Advances in Neural Information Processing Systems},
     year = {2024}
   }

5. CVPR

   Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning

   Wenlong Deng, Christos Thrampoulidis, and Xiaoxiao Li

   Conference on Computer Vision and Pattern Recognition, 2024

   Bib PDF Code

   @article{deng2024unlocking,
     title = {Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning},
     author = {Deng, Wenlong and Thrampoulidis, Christos and Li, Xiaoxiao},
     journal = {Conference on Computer Vision and Pattern Recognition},
     year = {2024},
   }

6. Nature Methods

   BUDDY: molecular formula discovery via bottom-up MS/MS interrogation

   Shipei Xing, Sam Shen, Banghua Xu, Xiaoxiao Li, and Tao Huan

   Nature Methods, 2023

   Bib HTML Code

   @article{xing2023buddy,
     title = {BUDDY: molecular formula discovery via bottom-up MS/MS interrogation},
     author = {Xing, Shipei and Shen, Sam and Xu, Banghua and Li, Xiaoxiao and Huan, Tao},
     journal = {Nature Methods},
     pages = {1--10},
     year = {2023},
     publisher = {Nature Publishing Group US New York},
   }

7. TMI

   GATE: graph CCA for temporal SElf-supervised learning for label-efficient fMRI analysis

   Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, and Xiaoxiao Li

   IEEE Transactions on Medical Imaging, 2022

   Bib HTML PDF Code

   @article{peng2022gate,
     title = {GATE: graph CCA for temporal SElf-supervised learning for label-efficient fMRI analysis},
     author = {Peng, Liang and Wang, Nan and Xu, Jie and Zhu, Xiaofeng and Li, Xiaoxiao},
     journal = {IEEE Transactions on Medical Imaging},
     volume = {42},
     number = {2},
     pages = {391--402},
     year = {2022},
     publisher = {IEEE},
   }

8. ICLR

   FedBN: Federated learning on non-iid features via local batch normalization

   Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, and Qi Dou

   International Conference on Learning Representations, 2021

   Bib HTML PDF Code

   @article{li2021fedbn,
     title = {FedBN: Federated learning on non-iid features via local batch normalization},
     author = {Li, Xiaoxiao and Jiang, Meirui and Zhang, Xiaofei and Kamp, Michael and Dou, Qi},
     year = {2021},
     journal = {International Conference on Learning Representations},
   }

9. ICML

   Fl-NTK: A neural tangent kernel-based framework for federated learning analysis

   Baihe Huang, Xiaoxiao Li, Zhao Song, and Xin Yang

   In International Conference on Machine Learning, 2021

   Bib PDF

   @inproceedings{huang2021fl,
     title = {Fl-NTK: A neural tangent kernel-based framework for federated learning analysis},
     author = {Huang, Baihe and Li, Xiaoxiao and Song, Zhao and Yang, Xin},
     booktitle = {International Conference on Machine Learning},
     pages = {4423--4434},
     year = {2021},
     organization = {PMLR},
   }

10. MedIA

    BrainGNN: Interpretable brain graph neural network for fmri analysis

    Xiaoxiao Li, Yuan Zhou, Nicha Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H Staib, Pamela Ventola, and James S Duncan

    Medical Image Analysis, 2021

    Bib HTML Code

    @article{li2021braingnn,
      title = {BrainGNN: Interpretable brain graph neural network for fmri analysis},
      author = {Li, Xiaoxiao and Zhou, Yuan and Dvornek, Nicha and Zhang, Muhan and Gao, Siyuan and Zhuang, Juntang and Scheinost, Dustin and Staib, Lawrence H and Ventola, Pamela and Duncan, James S},
      journal = {Medical Image Analysis},
      volume = {74},
      pages = {102233},
      year = {2021},
      publisher = {Elsevier},
    }