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Sharon Li

Assistant Professor
Department of Computer Sciences
University of Wisconsin-Madison

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Publications and Preprints

You can also browse my Google Scholar profile. I publish under the name "Yixuan Li".

  • Kaiping Chen, Anqi Shao, Jirayu Burapacheep, Yixuan Li
    Conversational AI and Equity through Assessing GPT-3’s Communication with Diverse Social Groups on Contentious Topics
    Nature Scientific Reports, 2024
    [BibTeX] [PDF] [Press coverage]

    
    
  • Maxim Khanov*, Jirayu Burapacheep*, Yixuan Li
    ARGS: Alignment as Reward-Guided Search
    In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
    (* equal contributions)
    [BibTeX] [PDF] [Code]

    @inproceedings{khanov2024alignment,
      title={ARGS: Alignment as Reward-Guided Search},
      author={Khanov, Maxim and Burapacheep, Jirayu and Li, Yixuan},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2024}
    }
    
  • Haoyue Bai*, Yifei Ming*, Julian Katz-Samuels, Yixuan Li
    HYPO: Hyperspherical Out-of-Distribution Generalization
    In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
    (* equal contributions)
    [BibTeX] [PDF] [Code]

    @inproceedings{bai2024hypo,
      title={HYPO: Hyperspherical Out-of-Distribution Generalization},
      author={Bai, Haoyue and Ming, Yifei and Katz-Samuels, Julian and Li, Yixuan},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2024}
    }
    
  • Xuefeng Du*, Zhen Fang*, Ilias Diakonikolas, Yixuan Li
    How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
    In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
    (* equal contributions)
    [BibTeX] [PDF] [Code]

    @inproceedings{du2024sal,
      title={How Does Unlabeled Data Provably Help Out-of-Distribution Detection?},
      author={Du, Xuefeng and Fang, Zhen and  Diakonikolas, Ilias and Li, Yixuan},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2024}
    }
    
  • Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang
    ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
    In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
    [BibTeX] [PDF] [Code]

    @inproceedings{peng2024conjnorm,
      title={ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection},
      author={Peng, Bo and Luo, Yadan and Zhang, Yonggang and Li, Yixuan and Fang, Zhen},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2024}
    }
    
  • Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, and Junbo Zhao
    PiCO+: Contrastive Label Disambiguation for Partial Label Learning
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
    [BibTeX] [PDF]

      @inproceedings{wang2024picopami,
          title={PiCO+: Contrastive Label Disambiguation for Partial Label Learning}, 
          author={Wang, Haobo and Xiao, Ruixuan and Li, Yixuan and Feng, Lei and Niu, Gang and Chen, Gang and Zhao, Junbo},
          booktitle={IEEE Transactions on Pattern Analysis and Machine Intelligence},
          year={2024}
    }
    
  • Soumya Suvra Ghosal*, Yiyou Sun*, Yixuan Li
    How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection?
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
    (* equal contributions)
    [BibTeX] [PDF] [Code]

      @inproceedings{ghosal2024how,
          title={How to Overcome Curse-of-Dimensionality for OOD Detection?}, 
          author={Ghosal, Soumya Suvra and Sun, Yiyou and Li, Yixuan},
          booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2024}
    }
    
  • Xuefeng Du, Yiyou Sun, Xiaojin Zhu, Yixuan Li
    Dream the Impossible: Outlier Imagination with Diffusion Models
    Neural Information Processing Systems (NeurIPS), 2023
    [BibTeX] [PDF] [Code]

     @inproceedings{du2023dream,
          title={Dream the Impossible: Outlier Imagination with Diffusion Models}, 
          author={Xuefeng Du and Yiyou Sun and Xiaojin Zhu and Yixuan Li },
          booktitle={Advances in Neural Information Processing Systems},
          year = {2023}
    }
    
  • Qizhou Wang*, Zhen Fang*, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
    Learning to Augment Distributions for Out-of-Distribution Detection
    Neural Information Processing Systems (NeurIPS), 2023
    (* equal contributions)
    [BibTeX] [PDF]

     @inproceedings{wang2023learning,
          title={Learning to Augment Distributions for Out-of-Distribution Detection}, 
          author={Qizhou Wang and Zhen Fang and Yonggang Zhang and Feng Liu and Yixuan Li and Bo Han},
          booktitle={Advances in Neural Information Processing Systems},
          year = {2023}
    }
    
  • Yiyou Sun, Zhenmei Shi, Yixuan Li
    A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
    Neural Information Processing Systems (NeurIPS), 2023
    Spotlight
    [BibTeX] [PDF] [Code]

     @inproceedings{sun2023graph,
          title={A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning}, 
          author={Yiyou Sun and Zhenmei Shi and Yixuan Li},
          booktitle={Advances in Neural Information Processing Systems},
          year = {2023}
    }
    
  • Jingyang Zhang, Jingkang Yang, Pengyun Wang, Haoqi Wang, Yueqian Lin, Haoran Zhang, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Yixuan Li, Ziwei Liu, Yiran Chen, Hai Li
    OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
    Neural Information Processing Systems (NeurIPS), DistShift Workshop, 2023
    [BibTeX] [PDF] [Code] [Project Page]

    
    
  • Jiuxiang Gu*, Yifei Ming*, Yi Zhou, Jason Kuen, Vlad Morariu, Anqi Liu, Yixuan Li, Tong Sun and Ani Nenkova
    A Critical Analysis of Out-of-Distribution Detection for Document Understanding
    In Empirical Methods in Natural Language Processing (EMNLP-Findings), 2023
    (* equal contributions)
    [BibTeX] [PDF]

     @inproceedings{gu2023critical,
          title={A Critical Analysis of Out-of-Distribution Detection for Document Understanding}, 
          author={Jiuxiang Gu and Yifei Ming and Yi Zhou and Jason Kuen and Vlad Morariu and Anqi Liu and Yixuan Li and Tong Sun and Ani Nenkova},
          booktitle={EMNLP-Findings},
          year = {2023}
    }
    
  • Yiyou Sun, Zhenmei Shi, Yingyu Liang, Yixuan Li
    When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis
    In Proceedings of International Conference on Machine Learning (ICML), 2023
    [BibTeX] [PDF] [Code] [Video]

     @inproceedings{sun2023when,
          title={When and How Does Known Class Help Discover Unknown Ones? Provable Understandings Through Spectral Analysis}, 
          author={Yiyou Sun and Zhenmei Shi and Yingyu Liang and Yixuan Li },
          booktitle = {International Conference on Machine Learning},
          year = {2023}
    }
    
  • Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D Nowak, Yixuan Li
    Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
    In Proceedings of International Conference on Machine Learning (ICML), 2023
    [BibTeX] [PDF] [Code] [Video]

     @inproceedings{bai2023feed,
          title={Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection}, 
          author={Haoyue Bai and Gregory Canal and Xuefeng Du and Jeongyeol Kwon and Robert D Nowak and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2023}
    }
    
  • Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li
    Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
    In Proceedings of International Conference on Machine Learning (ICML), 2023
    [BibTeX] [PDF] [Code]

     @inproceedings{wei2023mitigating,
          title={When and How Does Known Class Help Discover Unknown Ones? Provable Understandings Through Spectral Analysis}, 
          author={Hongxin Wei and Huiping Zhuang and Renchunzi Xie and Lei Feng and Gang Niu and Bo An and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2023}
    }
    
  • Yifei Ming and Yixuan Li
    How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?
    In International Journal of Computer Vision (IJCV), 2023
    [BibTeX] [PDF]

    @article{ming2023finetune,
      title={How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?},
      author={Ming, Yifei and Li, Yixuan},
      journal={International Journal of Computer Vision},
      year={2023}
    }
    
  • Soumya Suvra Ghosal and Yixuan Li
    Are Vision Transformers Robust to Spurious Correlations?
    In International Journal of Computer Vision (IJCV), 2023
    [BibTeX] [PDF] [Code]

    @inproceedings{ghosal2023vision,
        title={Are Vision Transformers Robust to Spurious Correlations?},
        author={Soumya Suvra Ghosal and Yixuan Li},
      journal={International Journal of Computer Vision},
      year={2023}
    }
    
  • Rheeya Uppaal, Junjie Hu, Yixuan Li
    Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection
    In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023
    [BibTeX] [PDF] [Code] [Video]

     @inproceedings{uppaal2023fine,
          title={Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection}, 
          author={Rheeya Uppaal and Junjie Hu and Yixuan Li },
          booktitle = {Annual Meeting of the Association for Computational Linguistics},
          year = {2023}
    }
    
  • Yiyou Sun, Yaojie Liu, Xiaoming Liu, Yixuan Li, Wen-Sheng Chu
    Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    [BibTeX] [PDF] [Code]

      @inproceedings{sun2023rethinking,
          title={Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment}, 
          author={Sun, Yiyou and Liu, Yaojie and Liu, Xiaoming and Li, Yixuan and Chu, Wen-Sheng},
          booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
          year={2023}
    }
    
  • Yifei Ming, Yiyou Sun, Ousmane Dia, and Yixuan Li
    How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
    In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023
    [BibTeX] [PDF] [Code]

    @inproceedings{ming2023cider,
      title={How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?},
      author={Ming, Yifei and Sun, Yiyou and Dia, Ousmane and Li, Yixuan},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2023}
    }
    
  • Leitian Tao, Xuefeng Du, Xiaojin Zhu, and Yixuan Li
    Non-Parametric Outlier Synthesis
    In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023
    [BibTeX] [PDF] [Code]

    @inproceedings{tao2023nonparametric,
      title={Non-Parametric Outlier Synthesis},
      author={Tao, Leitian and Du, Xuefeng and Zhu, Xiaojin and Li, Yixuan},
      booktitle={Proceedings of the International Conference on Learning Representations},
      year={2023}
    }
    
  • Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang
    Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions
    Transactions on Machine Learning Research (TMLR), 2023
    [BibTeX] [PDF] [Code]

    @journal{sun2023opencon,
    title={Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions},
    author={Xuefeng Du and Tian Bian and Yu Rong and Bo Han and Tongliang Liu and Tingyang Xu and Wenbing Huang and Yixuan Li and Junzhou Huang},
    journal={Transactions on Machine Learning Research},
    year={2023}
    }
    
  • Yiyou Sun and Yixuan Li
    OpenCon: Open-world Contrastive Learning
    Transactions on Machine Learning Research (TMLR), 2023
    [BibTeX] [PDF] [Code]

    @journal{sun2023opencon,
    title={OpenCon: Open-world Contrastive Learning},
    author={Yiyou Sun and Yixuan Li},
    journal={Transactions on Machine Learning Research},
    year={2023}
    }
    
  • Hao Lang, Yinhe Zheng, Yixuan Li, Jian Sun, Fei Huang, Yongbin Li
    A Survey on Out-of-Distribution Detection in NLP
    Transactions on Machine Learning Research (TMLR), 2023
    [BibTeX] [PDF]

    @journal{lang2023survey,
      title={A Survey on Out-of-Distribution Detection in NLP}, 
      author={Hao Lang and Yinhe Zheng and Yixuan Li and Jian Sun and Fei Huang and Yongbin Li},
    journal={Transactions on Machine Learning Research},
    year={2023}
    }
    }
    
  • Soumya Suvra Ghosal and Yixuan Li
    Distributionally Robust Optimization with Probabilistic Group
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023
    Oral
    [BibTeX] [PDF] [Code]

      @inproceedings{ghosal2023pdgro,
          title={Distributionally Robust Optimization with Probabilistic Group}, 
          author={Ghosal, Soumya Suvra and Li, Yixuan},
          booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2023}
    }
    
  • Mu Cai and Yixuan Li
    Out-of-distribution Detection via Frequency-regularized Generative Models
    In Proceedings of IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.
    Spotlight
    [BibTeX] [PDF] [Code] [Video]

      @inproceedings{cai2023frequency,
          title={Out-of-distribution Detection via Frequency-regularized Generative Models}, 
          author={Cai, Mu and Li, Yixuan},
          booktitle={Proceedings of IEEE/CVF Winter Conference on Applications of Computer Vision},
          year={2023}
    }
    
  • Radhika Dua, Seongjun Yang, Yixuan Li, and Edward Choi
    Task Agnostic and Post-hoc Unseen Distribution Detection
    In Proceedings of IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.
    [BibTeX] [PDF] [Code]

      @inproceedings{dua2023task,
          title={Task Agnostic and Post-hoc Unseen Distribution Detection}, 
          author={Dua, Radhika and Yang, Seongjun and Li, Yixuan and Choi, Edward},
          booktitle={Proceedings of IEEE/CVF Winter Conference on Applications of Computer Vision},
          year={2023}
    }
    
  • Xuefeng Du, Gabriel Gozum, Yifei Ming, Yixuan Li
    SIREN: Shaping Representations for Detecting Out-of-Distribution Objects
    Neural Information Processing Systems (NeurIPS), 2022
    [BibTeX] [PDF] [Code]

    @inproceedings{du2022siren,
      title={SIREN: Shaping Representations for Detecting Out-of-Distribution Objects},
      author={Du, Xuefeng and Gozum, Gabriel and Ming, Yifei and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2022}
    }
    
  • Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li
    Delving into Out-of-Distribution Detection with Vision-Language Representations
    Neural Information Processing Systems (NeurIPS), 2022
    [BibTeX] [PDF] [Code]

    @inproceedings{ming2022delving,
      title={Delving into Out-of-Distribution Detection with Vision-Language Representations},
      author={Ming, Yifei and Cai, Ziyang and Gu, Jiuxiang and Sun, Yiyou and Li, Wei and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2022}
    }
    
  • Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, and Feng Liu
    Is Out-of-Distribution Detection Learnable?
    Neural Information Processing Systems (NeurIPS), 2022
    Outstanding Paper Award (top 13 in 10411 submissions)
    [BibTeX] [PDF]

    @inproceedings{fang2022learnable,
      title={Is Out-of-Distribution Detection Learnable?},
      author={Fang, Zhen and Li, Yixuan and Lu, Jie and Dong, Jiahua and Han, Bo and Liu, Feng},
      booktitle={Advances in Neural Information Processing Systems},
      year={2022}
    }
    
  • Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao
    SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning
    Neural Information Processing Systems (NeurIPS), 2022
    [BibTeX] [PDF] [Code]

    @inproceedings{wang2022solar,
      title={SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning},
      author={Wang, Haobo and Xia, Mingxuan and Li, Yixuan and Mao, Yuren and Feng, Lei and Chen, Gang and Zhao, Junbo},
      booktitle={Advances in Neural Information Processing Systems},
      year={2022}
    }
    
  • Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, Ziwei Liu
    OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
    Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2022
    [BibTeX] [PDF] [Code]

    
    
  • Yiyou Sun and Yixuan Li
    DICE: Leveraging Sparsification for Out-of-Distribution Detection
    In Proceedings of European Conference on Computer Vision (ECCV), 2022.
    [BibTeX] [PDF] [Code] [Video]

      @inproceedings{sun2022dice,
          title={DICE: Leveraging Sparsification for Out-of-Distribution Detection}, 
          author={Sun, Yiyou and Li, Yixuan},
          booktitle={Proceedings of European Conference on Computer Vision},
          year={2022}
    }
    
  • Yifei Ming*, Ying Fan*, and Yixuan Li
    POEM: Out-of-Distribution Detection with Posterior Sampling
    In Proceedings of International Conference on Machine Learning (ICML), 2022
    Long talk (2%) (* indicates equal contributions)
    [BibTeX] [PDF] [code]

     @inproceedings{ming2022posterior,
          title={POEM: Out-of-Distribution Detection with Posterior Sampling}, 
          author={Yifei Ming and Ying Fan and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2022}
    }
    
  • Yiyou Sun, Yifei Ming, Xiaojin Zhu, and Yixuan Li
    Out-of-Distribution Detection with Deep Nearest Neighbors
    In Proceedings of International Conference on Machine Learning (ICML), 2022
    [BibTeX] [PDF] [Code]

     @inproceedings{sun2022knn,
          title={Out-of-Distribution Detection with Deep Nearest Neighbors}, 
          author={Yiyou Sun and Yifei Ming and Xiaojin Zhu and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2022}
    }
    
  • Julian Katz-Samuels*, Julia Nakhleh*, Robert Nowak, and Yixuan Li
    Training OOD Detectors in their Natural Habitats
    In Proceedings of International Conference on Machine Learning (ICML), 2022
    (* indicates equal contributions)
    [BibTeX] [PDF] [Code]

     @inproceedings{katzsamuels2022training,
          title={Training OOD Detectors in their Natural Habitats}, 
          author={Julian Katz-Samuels and Julia Nakhleh and Robert Nowak and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2022}
    }
    
  • Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, and Yixuan Li
    Mitigating Neural Network Overconfidence with Logit Normalization
    In Proceedings of International Conference on Machine Learning (ICML), 2022
    [BibTeX] [PDF] [Code] [Video]

     @inproceedings{wei2022mitigating,
          title={Mitigating Neural Network Overconfidence with Logit Normalization}, 
          author={Hongxin Wei and Renchunzi Xie and Hao Cheng and Lei Feng and Bo An and Yixuan Li},
          booktitle = {International Conference on Machine Learning},
          year = {2022}
    }
    
  • Soumya Suvra Ghosal, Yifei Ming, and Yixuan Li
    Are Vision Transformers Robust to Spurious Correlations?
    International Conference on Machine Learning (ICML'W), SCIS Workshop, 2022.
    [BibTeX] [PDF] [Code]

    @inproceedings{ghosal2022vision,
        title={Are Vision Transformers Robust to Spurious Correlations?},
        author={Soumya Suvra Ghosal and Yifei Ming and Yixuan Li},
        booktitle={ICML Workshop on Spurious Correlations, Invariance and Stability (SCIS)}
        year={2022},
    }
    
  • Xuefeng Du, Xin Wang, Gabriel Gozum, and Yixuan Li
    Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
    Oral Presentation
    [BibTeX] [PDF] [Code]

      @inproceedings{du2022unknown,
          title={Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild}, 
          author={Du, Xuefeng and Wang, Xin and Gozum, Gabriel and Li, Yixuan},
          booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
          year={2022}
    }
    
  • Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li
    VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
    In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022
    [BibTeX] [PDF] [Code] [Video on ICLR]

      @inproceedings{du2022vos,
          title={VOS: Learning What You Don’t Know by Virtual Outlier Synthesis}, 
          author={Du, Xuefeng and Wang, Zhaoning and Cai, Mu and Li, Yixuan},
          booktitle={Proceedings of the International Conference on Learning Representations},
          year={2022}
    }
    
  • Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, and Junbo Zhao
    PiCO: Contrastive Label Disambiguation for Partial Label Learning
    In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022
    Outstanding Paper Award Honorable Mention (top 10 in 3391 submissions)
    [BibTeX] [PDF] [Code] [Video]

      @inproceedings{wang2022contrastive,
          title={PiCO: Contrastive Label Disambiguation for Partial Label Learning}, 
          author={Wang, Haobo and Xiao, Ruixuan and Li, Yixuan and Feng, Lei and Niu, Gang and Chen, Gang and Zhao, Junbo},
          booktitle={Proceedings of the International Conference on Learning Representations},
          year={2022}
    }
    
  • Peyman Morteza and Yixuan Li
    Provable Guarantees for Understanding Out-of-distribution Detection
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022
    Oral presentation
    [BibTeX] [PDF] [Code]

      @inproceedings{morteza2022provable,
          title={Provable Guarantees for Understanding Out-of-distribution Detection}, 
          author={Morteza, Peyman and Li, Yixuan},
          booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2022}
    }
    
  • Yifei Ming, Hang Yin and Yixuan Li
    On the Impact of Spurious Correlation for Out-of-distribution Detection
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022
    Oral presentation
    [BibTeX] [PDF] [Code]

      @inproceedings{ming2022spurious,
          title={On the Impact of Spurious Correlation for Out-of-distribution Detection}, 
          author={Ming, Yifei and Yin, Hang and Li, Yixuan},
          booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2022}
    }
    
  • Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, Mohammad Sabokrou
    A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
    Transactions on Machine Learning Research (TMLR), 2022
    [BibTeX] [PDF]

    @journal{salehi2021unified,
    title={A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges},
    author={Mohammadreza Salehi and Hossein Mirzaei and Dan Hendrycks and Yixuan Li and Mohammad Hossein Rohban and Mohammad Sabokrou},
    journal={Transactions on Machine Learning Research},
    year={2022}
    }
    
  • Yiyou Sun, Chuan Guo and Yixuan Li
    ReAct: Out-of-distribution Detection With Rectified Activations
    Neural Information Processing Systems (NeurIPS), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{sun2021react,
      title={ReAct: Out-of-distribution Detection With Rectified Activations},
      author={Sun, Yiyou and Guo, Chuan and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2021}
    }
    
  • Haoran Wang*, Weitang Liu, Alex Bocchieri and Yixuan Li*
    Can multi-label classification networks know what they don’t know?
    Neural Information Processing Systems (NeurIPS), 2021
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

    @inproceedings{wang2021canmulti,
          title={Can multi-label classification networks know what they don't know?},
          author={Wang, Haoran and Liu, Weitang and Bocchieri, Alex and Li, Yixuan},
          booktitle={Advances in Neural Information Processing Systems},
          year={2021}
     }
    
  • Rui Huang, Andrew Geng and Yixuan Li
    On the Importance of Gradients for Detecting Distributional Shifts in the Wild
    Neural Information Processing Systems (NeurIPS), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2021importance,
      title={On the Importance of Gradients for Detecting Distributional Shifts in the Wild},
      author={Huang, Rui and Geng, Andrew and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2021}
    }
    
  • Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu
    Generalized Out-of-Distribution Detection: A Survey
    Preprints, 2021
    [BibTeX] [PDF] [Code]

    @article{yang2021generalized,
      title={Generalized Out-of-Distribution Detection: A Survey},
      author={Yang, Jingkang and Zhou, Kaiyang and Li, Yixuan and Liu, Ziwei},
      journal={arXiv preprint arXiv:2110.11334},
      year={2021}
    }
    
  • Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng, Yixuan Li and Gao Huang
    Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
    In Proceedings of International Conference on Computer Vision (ICCV), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{cai2021frequency,
    title={Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving},
    author={Cai, Mu and Zhang, Hong and Huang, Huijuan and Geng, Qichuan and Li, Yixuan and Huang, Gao},
    booktitle={In Proceedings of International Conference on Computer Vision (ICCV)},
    year={2021}
    }
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
    In Proceedings of European Conference on Machine Learning (ECML-PKDD), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{chen2021robustifying,
    title={ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining},
    author={Chen, Jiefeng and Li, Yixuan and Wu, Xi and Liang, Yingyu and Jha, Somesh},
    booktitle={In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},
    year={2021}
    }
    
  • Rui Huang and Yixuan Li
    MOS: Scaling Out-of-distribution Detection to Large Semantic Space
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    Oral Presentation, Top 4%
    [BibTeX] [PDF] [Code] [Video]

    @inproceedings{huang2021mos,
      title={MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space},
      author={Huang, Rui and Li, Yixuan},
      booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
      year={2021}
    }
    
  • Ziqian Lin*, Sreya Dutta Roy* and Yixuan Li
    MOOD: Multi-level Out-of-distribution Detection
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

      @inproceedings{lin2021mood,
      author    = {Lin, Ziqian  and Roy, Sreya Dutta  and Li, Yixuan},
      title     = {MOOD: Multi-level Out-of-distribution Detection},
      booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
      year      = {2021}
    }
    
  • Yiyou Sun*, Bastin Joseph*, Alison Deatsch, Robert Jeraj and Yixuan Li
    LOOD: Localization-based Uncertainty Estimation for Medical Imaging
    International Conference on Machine Learning (ICML), DFUQ Workshop, 2021.
    Spotlight paper
    [BibTeX]

    
    
  • Karan Goel*, Albert Gu*, Yixuan Li and Christopher Ré
    Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
    In Proceedings of the 9th International Conference on Learning Representations (ICLR), 2021
    * indicates equal contribution
    [BibTeX] [PDF] [Blog] [Video] [Code]

    @inproceedings{goel2020model,
    title={Model Patching: Closing the Subgroup Performance Gap with Data Augmentation},
    author={Goel, Karan and Gu, Albert and Li, Yixuan and Ré, Christopher},
    booktitle={Proceedings of the International Conference on Learning Representations (ICLR)},
    year={2021}
    }
    
  • Weitang Liu, Xiaoyun Wang, John Owens and Yixuan Li
    Energy-based Out-of-distribution Detection
    Neural Information Processing Systems (NeurIPS), 2020
    [BibTeX] [PDF] [Code]

    @inproceedings{liu2020energy,
    title={Energy-based Out-of-distribution Detection},
    author={Liu, Weitang and Wang, Xiaoyun and Owens, John and Li, Yixuan},
    booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
    year={2020}
    }
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    Informative Outlier Matters: Robustifying Out-of-distribution Detection Using Outlier Mining
    ICML workshop on Uncertainty and Robustness in Deep Learning (ICML UDL), 2020
    [BibTeX] [PDF]

    
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    Robust Out-of-distribution Detection for Neural Networks
    AAAI Workshop on Adversarial Machine Learning and Beyond, 2022
    [BibTeX] [PDF]

    @article{chen2020robust,
    title={Robust Out-of-distribution Detection in Neural Networks},
    author={Chen, Jiefeng and Li, Yixuan and Wu, Xi and Liang, Yingyu and Jha, Somesh},
    journal={arXiv},
    pages={arXiv--2003},
    year={2020}
    }
    
  • Trenton Chang, Dan Fu, Yixuan Li, and Christopher Ré
    Beyond the Pixels: Exploring the Effect of Video File Corruptions on Model Robustness
    ECCV Workshop, 2020
    [PDF] [Slides] [Video]

  • Yina Tang*, Fedor Borisyuk*, Siddarth Malreddy*, Yixuan Li*, Yiqun Liu* and Sergey Kirshner*
    MSURU: Large Scale E-commerce Image Classification With Weakly Supervised Search Data
    In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2019
    * indicates equal contribution
    [BibTeX] [PDF]

    @inproceedings{tang2019msuru,
      title={MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data},
      author={Tang, Yina and Borisyuk, Fedor and Malreddy, Siddarth and Li, Yixuan and Liu, Yiqun and Kirshner, Sergey},
      booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
      pages={2518--2526},
      year={2019}
    }
    
  • Abhinmanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li and Dhruv Mahajan
    Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{dubey2019defense,
    title={Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search},
    author={Dubey, Abhimanyu and van der Maaten, Laurens and Yalniz, Zeki and Li, Yixuan and Mahajan, Dhruv},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year={2019}
    }
    
  • Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten
    Exploring the Limits of Weakly Supervised Pretraining
    In Proceedings of European Conference on Computer Vision (ECCV), 2018.
    [BibTeX] [PDF] [Blog Post]

    @inproceedings{mahajan2018exploring,
      title={Exploring the limits of weakly supervised pretraining},
      author={Mahajan, Dhruv and Girshick, Ross and Ramanathan, Vignesh and He, Kaiming and Paluri, Manohar and Li, Yixuan and Bharambe, Ashwin and Van Der Maaten, Laurens},
      booktitle={Proceedings of the European conference on computer vision (ECCV)},
      pages={181--196},
      year={2018}
    }
    
  • Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant,
    Understanding the Loss Surface of Neural Networks for Binary Classification
    In Proceedings of International Conference on Machine Learning (ICML), 2018.
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{liang2018understanding,
      author = {Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant},
      title = {Understanding the Loss Surface of Neural Networks for Binary Classification},
      booktitle = {International Conference on Machine Learning (ICML)},
      year = {2018}
    }
    
  • Shiyu Liang, Ruoyu Sun, Yixuan Li, and R. Srikant
    Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification
    International Conference on Learning Representation (ICLR Workshop), 2018
    [BibTeX] [PDF]

      @article{liang2018understanding,
        title={Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification},
        author={Liang, Shiyu and Sun, Ruoyu and Li, Yixuan and Srikant, R},
        year={2018}
      }
    
  • Shiyu Liang, Yixuan Li, and R. Srikant
    Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
    In Proceedings of the 6th International Conference on Learning Representations (ICLR), 2018.
    [BibTeX] [PDF]

    @inproceedings{liang2017enhancing,
      title={Enhancing the reliability of out-of-distribution image detection in neural networks},
      author={Liang, Shiyu and Li, Yixuan and Srikant, R},
      booktitle={International Conference on Learning Representations (ICLR)},
      year={2018}
    }
    
  • Gao Huang*, Yixuan Li*, Geoff Pleiss, Zhuang Liu, John Hopcroft, and Kilian Weinberger
    Snapshot Ensembles: Train 1, Get M for Free
    In Proceedings of the 5th International Conference on Learning Representations (ICLR), 2017.
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2017snapshot,
      title={Snapshot ensembles: Train 1, get M for free},
      author={Huang, Gao and Li, Yixuan and Pleiss, Geoff and Liu, Zhuang and Hopcroft, John E and Weinberger, Kilian Q},
      booktitle={International Conference on Learning Representations (ICLR)},
      year={2017}
    }
    
  • Xun Huang, Yixuan Li,Omid Poursaeed, John Hopcroft, and Serge Belongie
    Stacked Adversarial Generative Networks
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2017stacked,
      title={Stacked Generative Adversarial Networks.},
      author={Huang, Xun and Li, Yixuan and Poursaeed, Omid and Hopcroft, John E and Belongie, Serge J},
      booktitle={CVPR},
      volume={2},
      pages={3},
      year={2017}
    }
    
  • Yixuan Li, Pingmei Xu, Dmitry Lagun, and Vidhya Navalpakkam
    Towards Measuring and Inferring User Interest From Gaze
    In Proceedings of the 26th international conference on World Wide Web (WWW), 2017
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{li2017towards,
      title={Towards measuring and inferring user interest from gaze},
      author={Li, Yixuan and Xu, Pingmei and Lagun, Dmitry and Navalpakkam, Vidhya},
      booktitle={Proceedings of the 26th International Conference on World Wide Web Companion},
      pages={525--533},
      year={2017},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Yixuan Li, Kun He, Kyle Kloster, David Bindel, and John Hopcroft
    Local spectral clustering for overlapping community detection
    In ACM Transactions on Knowledge Discovery from Data (TKDD), 2017.
    [BibTeX] [PDF] [Code]

    @article{li2018local,
      title = {Local spectral clustering for overlapping community detection},
      author = {Li, Yixuan and He, Kun and Kloster, Kyle and Bindel, David and Hopcroft, John},
      journal = {ACM Transactions on Knowledge Discovery from Data (TKDD)},
      volume = {12},
      number = {2},
      pages = {17},
      year = {2018},
      publisher = {ACM}
    }
    
  • Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft, and Hod Lipson
    Convergent Learning: Do different neural networks learn the same representations?
    In Proceedings of the 4th International Conference on Learning Representation (ICLR), 2016
    Oral Presentation
    [BibTeX] [PDF] [Code]

    @inproceedings{li2015convergent,
      title={Convergent learning: Do different neural networks learn the same representations?},
      author={Li, Yixuan and Yosinski, Jason and Clune, Jeff and Lipson, Hod and Hopcroft, John E},
      booktitle = {International Conference on Learning Representations (ICLR)},
      year={2016}
    }
    
  • Yixuan Li, Oscar Martinez, Xing Chen, Yi Li, and John Hopcroft
    In a World that Counts: Clustering and Detecting Fake Social Engagement at Scale
    In Proceedings of the 25th international conference on World Wide Web (WWW), 2016
    Oral Presentation
    [BibTeX] [PDF] [Press]

    @inproceedings{li2016world,
      title={In a world that counts: Clustering and detecting fake social engagement at scale},
      author={Li, Yixuan and Martinez, Oscar and Chen, Xing and Li, Yi and Hopcroft, John E},
      booktitle={Proceedings of the 25th International Conference on World Wide Web},
      pages={111--120},
      year={2016},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang and John Hopcroft
    The Lifecycle and Cascade of Social Messaging Groups
    In Proceedings of the 25th international conference on World Wide Web (WWW), 2016
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{qiu2016lifecycle,
    title={The lifecycle and cascade of wechat social messaging groups},
    author={Qiu, Jiezhong and Li, Yixuan and Tang, Jie and Lu, Zheng and Ye, Hao and Chen, Bo and Yang, Qiang and Hopcroft, John E},
    booktitle={Proceedings of the 25th International Conference on World Wide Web},
    pages={311--320},
    year={2016},
    organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Kyle Kloster and Yixuan Li
    Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions
    Preprint on arXiv., 2016
    [BibTeX] [PDF]

    @article{kloster2016scalable,
      title={Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions},
      author={Kloster, Kyle and Li, Yixuan},
      journal={arXiv preprint arXiv:1611.05152},
      year={2016}
    }
    
  • Jacob Gardner, Paul Upchurch, Matt Kusner, Yixuan Li, Kilian Weinberger, Kavita Bala, and John Hopcroft
    Deep Manifold Traversal: Changing Labels with Convolutional Features
    arXiv cs.LG/1511.06421, 2015
    [BibTeX] [PDF]

    @article{gardner2015deep,
      title={Deep manifold traversal: Changing labels with convolutional features},
      author={Gardner, Jacob R and Upchurch, Paul and Kusner, Matt J and Li, Yixuan and Weinberger, Kilian Q and Bala, Kavita and Hopcroft, John E},
      journal={arXiv preprint arXiv:1511.06421},
      year={2015}
    }
    
  • Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft, and Hod Lipson
    Convergent Learning: Do different neural networks learn the same representations?
    NIPS Workshop on Feature Extraction: Modern Questions and Challenges (NIPS Workshop), 2015.
    Oral presentation
    [BibTeX] [PDF]

      @inproceedings{li2015convergent_b,
        title={Convergent learning: Do different neural networks learn the same representations?},
        author={Li, Yixuan and Yosinski, Jason and Clune, Jeff and Lipson, Hod and Hopcroft, John E},
        booktitle={FE@ NIPS},
        pages={196--212},
        year={2015}
      }
    
  • Yixuan Li, Kun He, David Bindel, and John Hopcroft
    Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach
    In Proceedings of the 24th International Conference on World Wide Web (WWW), 2015
    Oral presentation
    [BibTeX] [PDF] [Code]

    @inproceedings{li2015uncovering,
      title={Uncovering the small community structure in large networks: A local spectral approach},
      author={Li, Yixuan and He, Kun and Bindel, David and Hopcroft, John E},
      booktitle={Proceedings of the 24th international conference on world wide web},
      pages={658--668},
      year={2015},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Kun He, Yiwei Sun, David Bindel, John Hopcroft, and Yixuan Li
    Detecting Overlapping Communities from Local Spectral Subspaces
    In Proceedings of the International Conference on Data Mining (ICDM), 2015
    [BibTeX] [PDF]

    @inproceedings{he2015detecting,
      title={Detecting overlapping communities from local spectral subspaces},
      author={He, Kun and Sun, Yiwei and Bindel, David and Hopcroft, John and Li, Yixuan},
      booktitle={Data Mining (ICDM), 2015 IEEE International Conference on},
      pages={769--774},
      year={2015},
      organization={IEEE}
    }
    
  • Jinbei Zhang, Yixuan Li, Zhuotao Liu, Fan Wu, Feng Yang, and Xinbing Wang
    On Multicast Capacity and Delay in Cognitive Radio Mobile Ad-hoc Networks
    IEEE Transactions on Wireless Communications (TWC), 2015.
    [BibTeX] [PDF]

    @article{zhang2015multicast,
    title={On multicast capacity and delay in cognitive radio mobile ad hoc networks},
    author={Zhang, Jinbei and Li, Yixuan and Liu, Zhuotao and Wu, Fan and Yang, Feng and Wang, Xinbing},
    journal={IEEE Transactions on Wireless Communications},
    volume={14},
    number={10},
    pages={5274--5286},
    year={2015},
    publisher={IEEE}
    }
    
  • Yixuan Li, Qiuyu Peng, Xinbing Wang
    Multicast Capacity With Max-Min Fairness for Heterogeneous Networks
    In IEEE/ACM Transactions on Networking (TON), 2014
    [BibTeX] [PDF]

    @article{li2014multicast,
    title={Multicast capacity with max-min fairness for heterogeneous networks},
    author={Li, Yixuan and Peng, Qiuyu and Wang, Xinbing},
    journal={IEEE/ACM Transactions on Networking (TON)},
    volume={22},
    number={2},
    pages={622--635},
    year={2014},
    publisher={IEEE Press}
    }