Publications

2026

1. AISTATS

   The Rashomon Effect for Visualizing High-Dimensional Data

   Yiyang Sun , Haiyang Huang, Gaurav Rajesh Parikh , and 1 more author

   In Proceedings of the 29th International Conference on Artificial Intelligence and Statistics , 2026

   arXiv Bib HTML

   @inproceedings{sun2026rashomon,
     title = {The Rashomon Effect for Visualizing High-Dimensional Data},
     author = {Sun, Yiyang and Huang, Haiyang and Parikh, Gaurav Rajesh and Rudin, Cynthia},
     booktitle = {Proceedings of the 29th International Conference on Artificial Intelligence and Statistics},
     volume = {300},
     pages = {3160--3168},
     year = {2026},
   }

2025

1. Workshop

   It’s LIT! Reliability-Optimized LLMs with Inspectable Tools

   Ruixin Zhang , Jon Donnelly , Zhicheng Guo , and 4 more authors

   In NeurIPS Workshop on Multi-Turn Interactions in Large Language Models , 2025

   arXiv Bib

   @inproceedings{zhang2025lit,
     title = {It's LIT! Reliability-Optimized LLMs with Inspectable Tools},
     author = {Zhang, Ruixin and Donnelly, Jon and Guo, Zhicheng and Khalighinejad, Ghazal and Huang, Haiyang and Barnett, Alina Jade and Rudin, Cynthia},
     booktitle = {NeurIPS Workshop on Multi-Turn Interactions in Large Language Models},
     year = {2025},
   }

2. AAAI

   Dimension Reduction with Locally Adjusted Graphs

   Yingfan Wang , Yiyang Sun , Haiyang Huang, and 1 more author

   In Proceedings of the AAAI Conference on Artificial Intelligence , 2025

   arXiv Bib HTML

   @inproceedings{wang2025localmap,
     title = {Dimension Reduction with Locally Adjusted Graphs},
     author = {Wang, Yingfan and Sun, Yiyang and Huang, Haiyang and Rudin, Cynthia},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     volume = {39},
     number = {20},
     pages = {21357--21365},
     year = {2025},
     doi = {10.1609/aaai.v39i20.35436},
   }

2024

1. NeurIPS

   Toward Efficient Inference for Mixture of Experts

   Haiyang Huang, Newsha Ardalani , Anna Sun , and 5 more authors

   In Advances in Neural Information Processing Systems , 2024

   Bib HTML Code

   @inproceedings{huangtoward,
     title = {Toward Efficient Inference for Mixture of Experts},
     author = {Huang, Haiyang and Ardalani, Newsha and Sun, Anna and Ke, Liu and Bhosale, Shruti and Lee, Hsien-Hsin S and Wu, Carole-Jean and Lee, Benjamin},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2024},
   }

2. NeurIPS

   Navigating the Effect of Parametrization for Dimensionality Reduction

   Haiyang Huang, Yingfan Wang , and Cynthia Rudin

   In Advances in Neural Information Processing Systems , 2024

   arXiv Bib HTML Code

   @inproceedings{huangnavigating,
     title = {Navigating the Effect of Parametrization for Dimensionality Reduction},
     author = {Huang, Haiyang and Wang, Yingfan and Rudin, Cynthia},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2024},
   }

2023

1. Preprint

   Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

   Haiyang Huang, Newsha Ardalani , Anna Sun , and 6 more authors

   arXiv preprint arXiv:2303.06182, 2023

   arXiv Bib

   @article{huang2023towards,
     title = {Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference},
     author = {Huang, Haiyang and Ardalani, Newsha and Sun, Anna and Ke, Liu and Lee, Hsien-Hsin S and Sridhar, Anjali and Bhosale, Shruti and Wu, Carole-Jean and Lee, Benjamin},
     journal = {arXiv preprint arXiv:2303.06182},
     year = {2023},
   }

2022

1. Preprint

   SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation

   Haiyang Huang, Zhi Chen , and Cynthia Rudin

   arXiv preprint arXiv:2204.10926, 2022

   arXiv Bib

   @article{huang2022segdiscover,
     title = {SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation},
     author = {Huang, Haiyang and Chen, Zhi and Rudin, Cynthia},
     journal = {arXiv preprint arXiv:2204.10926},
     year = {2022},
   }

2. Comm. Bio.

   Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization

   Haiyang Huang, Yingfan Wang , Cynthia Rudin , and 1 more author

   Communications Biology, 2022

   Bib HTML

   @article{huang2022towards,
     title = {Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization},
     author = {Huang, Haiyang and Wang, Yingfan and Rudin, Cynthia and Browne, Edward P},
     journal = {Communications Biology},
     volume = {5},
     number = {1},
     pages = {719},
     year = {2022},
     publisher = {Nature Publishing Group UK London},
     doi = {10.1038/s42003-022-03628-x},
   }

3. Stat. Surv.

   Interpretable machine learning: Fundamental principles and 10 grand challenges

   Cynthia Rudin , Chaofan Chen , Zhi Chen , and 3 more authors

   Statistics Surveys, 2022

   arXiv Bib

   @article{rudin2022interpretable,
     title = {Interpretable machine learning: Fundamental principles and 10 grand challenges},
     author = {Rudin, Cynthia and Chen, Chaofan and Chen, Zhi and Huang, Haiyang and Semenova, Lesia and Zhong, Chudi},
     journal = {Statistics Surveys},
     volume = {16},
     pages = {1--85},
     year = {2022},
     publisher = {Institute of Mathematical Statistics},
   }

2021

1. JMLR

   Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization

   Yingfan Wang , Haiyang Huang, Cynthia Rudin , and 1 more author

   Journal of Machine Learning Research, 2021

   Bib HTML PDF Code

   @article{wang2021understanding,
     title = {Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization},
     author = {Wang, Yingfan and Huang, Haiyang and Rudin, Cynthia and Shaposhnik, Yaron},
     journal = {Journal of Machine Learning Research},
     volume = {22},
     pages = {1--73},
     year = {2021},
   }