Publications and Preprints

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

Process Reward Model with Q-Value Rankings
Wendi Li, Yixuan Li
Manuscript 2024.
[BibTeX] [PDF] [Code]
```
 
```
CodeLutra: Boosting LLM Code Generation via Preference-Guided Refinement
Leitian Tao, Xiang Chen, Tong Yu, Tung Mai, Ryan Rossi, Yixuan Li, Saayan Mitra
Manuscript 2024.
[BibTeX] [PDF]
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How Reliable Is Human Feedback For Aligning Large Language Models?
Min-Hsuan Yeh, Leitian Tao, Jeffrey Wang, Xuefeng Du, Yixuan Li
Manuscript 2024.
[BibTeX] [PDF]
```
 
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Your Weak LLM is Secretly a Strong Teacher for Alignment
Leitian Tao, Yixuan Li
Manuscript 2024.
[BibTeX] [PDF]
```
 
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On the Generalization of Preference Learning with DPO
Shawn Im, Yixuan Li
Manuscript 2024.
[BibTeX] [PDF]
```
 
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VLMGuard: Defending VLMs against Malicious Prompts via Unlabeled Data
Xuefeng Du, Reshmi Ghosh, Robert Sim, Ahmed Salem, Vitor Carvalho, Emily Lawton, Yixuan Li, Jack W. Stokes
Manuscript 2024.
[BibTeX] [PDF]
```
 
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Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models
Shuoyuan Wang, Yixuan Li, Hongxin Wei
Manuscript 2024.
[BibTeX] [PDF]
```
 
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Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Yueqian Lin, Qing Yu, Go Irie, Shafiq Joty, Yixuan Li, Hai Li, Ziwei Liu, Toshihiko Yamasaki, Kiyoharu Aizawa
Manuscript 2024.
[BibTeX] [PDF]

  @misc{miyai2024survey,
      title={Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey}, 
      author={Atsuyuki Miyai and Jingkang Yang and Jingyang Zhang and Yifei Ming and Yueqian Lin and Qing Yu and Go Irie and Shafiq Joty and Yixuan Li and Hai Li and Ziwei Liu and Toshihiko Yamasaki and Kiyoharu Aizawa},
      year={2024},
      eprint={2407.21794},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.21794}, 
}

Out-of-Distribution Learning with Human Feedback
Haoyue Bai, Xuefeng Du, Katie Rainey, Shibin Parameswaran, Yixuan Li
Manuscript 2024.
[BibTeX] [PDF]
```
 
```
Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha
Manuscript 2024.
[BibTeX] [PDF]
```
 
```
Exploring Transition States of Protein Conformational Changes via Out-of-Distribution Detection in the Hyperspherical Latent Space
Bojun Liu, Jordan G. Boysen, Ilona Christy Unarta, Xuefeng Du, Yixuan Li, Xuhui Huang
Nature Communications (to appear), 2024.
[BibTeX] [PDF]
```
 
```

HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection
Xuefeng Du, Chaowei Xiao, Yixuan Li
Neural Information Processing Systems (NeurIPS), 2024
Spotlight
[BibTeX] [PDF] [Code]

  @inproceedings{du2024haloscope,
      title={ HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection}, 
      author={Xuefeng Du and Chaowei Xiao and Yixuan Li},
      booktitle={Advances in Neural Information Processing Systems},
      year = {2024}
}

Bridging OOD Detection and Generalization: A Graph-Theoretic View
Han Wang, Yixuan Li
Neural Information Processing Systems (NeurIPS), 2024
[BibTeX] [PDF] [Code]

  @inproceedings{wang2024bridging,
      title={ Bridging OOD Detection and Generalization: A Graph-Theoretic View}, 
      author={Han Wang and Yixuan Li},
      booktitle={Advances in Neural Information Processing Systems},
      year = {2024}
}

Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Junjie Hu, Yixuan Li, Patrick McDaniel, Muhao Chen, Bo Li, Chaowei Xiao
Neural Information Processing Systems (NeurIPS), 2024
[BibTeX] [PDF]

  @inproceedings{wang2024mitigating,
      title={ Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment}, 
      author={Jiongxiao Wang and Jiazhao Li and Yiquan Li and Xiangyu Qi and Junjie Hu and Yixuan Li and Patrick McDaniel and Muhao Chen and Bo Li and Chaowei Xiao},
      booktitle={Advances in Neural Information Processing Systems},
      year = {2024}
}

Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models
Jiayu Wang, Y. Ming, Zhenmei Shi, Vibhav Vineet, Xin Wang, Yixuan Li, Neel Joshi
Neural Information Processing Systems (NeurIPS), 2024
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
Changdae Oh, Yixuan Li, Kyungwoo Song, Sangdoo Yun, Dongyoon Han
Neural Information Processing Systems, Workshop on Adaptive Foundation Model (NeurIPS'W), 2024
[BibTeX] [PDF]
```
 
```
Safety-Aware Fine-Tuning of Large Language Models
Hyeong Kyu Choi, Xuefeng Du, Yixuan Li
Neural Information Processing Systems, Workshop on Safe Generative AI (NeurIPS'W), 2024
[BibTeX] [PDF]
```
 
```

PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Yixuan Li
In Proceedings of International Conference on Machine Learning (ICML), 2024
[BibTeX] [PDF] [Code]

  @inproceedings{choi2024beyond,
      title={PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning}, 
      author={Hyeong Kyu Choi and Yixuan Li},
      booktitle = {International Conference on Machine Learning},
      year = {2024}
}

Understanding the Learning Dynamics of Alignment with Human Feedback
Shawn Im, Yixuan Li
In Proceedings of International Conference on Machine Learning (ICML), 2024
[BibTeX] [PDF] [Code]

  @inproceedings{im2024understanding,
      title={Understanding the Learning Dynamics of Alignment with Human Feedback}, 
      author={Shawn Im and Yixuan Li},
      booktitle = {International Conference on Machine Learning},
      year = {2024}
}

Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
Yifei Ming, Yixuan Li
In Proceedings of International Conference on Machine Learning (ICML), 2024
[BibTeX] [PDF]

  @inproceedings{ming2024understanding,
      title={Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models}, 
      author={Yifei Ming and Yixuan Li},
      booktitle = {International Conference on Machine Learning},
      year = {2024}
}

When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun and Yixuan Li
In Proceedings of International Conference on Machine Learning (ICML), 2024
[BibTeX] [PDF] [Code]

  @inproceedings{du2024when,
      title={When and How Does In-Distribution Label Help Out-of-Distribution Detection?}, 
      author={Xuefeng Du and Yiyou Sun and Yixuan Li},
      booktitle = {International Conference on Machine Learning},
      year = {2024}
}

Adaptive Concept Bottleneck for Foundation Models
Jihye Choi, Jayaram Raghuram, Yixuan Li, Suman Banerjee, Somesh Jha
International Conference on Machine Learning, Workshop on Foundation Models in the Wild (ICML'W), 2024
[BibTeX]

On the Learnability of Out-of-distribution Detection
Zhen Fang, Yixuan Li, Feng Liu, Bo Han and Jie Lu
Journal of Machine Learning Research (JMLR), 2024
[BibTeX] [PDF]

@article{fang2024jmlr,
  title={On the Learnability of Out-of-distribution Detection}, 
      author={Zhen Fang and Yixuan Li and Feng Liu and Bo Han and Jie Lu},
  journal={Journal of Machine Learning Research},
  year={2024}
}

Your Classifier Can Be Secretly a Likelihood-Based OOD Detector
Jirayu Burapacheep, Yixuan Li
Transactions on Machine Learning Research (TMLR), 2024
[BibTeX] [PDF] [Code]
```
 
```

ARGS: Alignment as Reward-Guided Search
Maxim Khanov*, Jirayu Burapacheep*, Yixuan Li
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}
}

How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du*, Zhen Fang*, Ilias Diakonikolas, Yixuan Li
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}
}

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang
In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
[BibTeX] [PDF]

@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}
}

HYPO: Hyperspherical Out-of-Distribution Generalization
Haoyue Bai*, Yifei Ming*, Julian Katz-Samuels, Yixuan Li
In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024
(* equal contributions)
[BibTeX] [PDF] [Code]

@inproceedings{hypo,
  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}
}

Unsolvable Problem Detection for Vision Language Models
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, Kiyoharu Aizawa
International Conference on Learning Representations, Workshop on Reliable and Responsible Foundation Models (ICLR'W), 2024
[BibTeX] [PDF] [Code]

Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu
International Journal of Computer Vision (IJCV), 2024.
[BibTeX] [PDF] [Code]

@article{yang2024generalized,
  title={Generalized Out-of-Distribution Detection: A Survey},
  author={Yang, Jingkang and Zhou, Kaiyang and Li, Yixuan and Liu, Ziwei},
  journal={International Journal of Computer Vision},
  year={2024}
}

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

PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning
Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, and Junbo Zhao
IEEE Transactions on Pattern Analysis and Machine Inteligence (TPAMI), 2024
[BibTeX] [PDF]

@ARTICLE{wang2024contrastive,
  author={Wang, Haobo and Xiao, Ruixuan and Li, Yixuan and Feng, Lei and Niu, Gang and Chen, Gang and Zhao, Junbo},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning}, 
  year={2024},
  volume={46},
  number={5},
  pages={3183-3198},
  doi={10.1109/TPAMI.2023.3342650}}

Targeted Representation Alignment for Open-World Semi-Supervised Learning
Ruixuan Xiao, Lei Feng, Kai Tang, Junbo Zhao, Yixuan Li, Gang Chen, Haobo Wang
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
[BibTeX] [PDF]

  @inproceedings{xiao2024targeted,
      title={Targeted Representation Alignment for Open-World Semi-Supervised Learning}, 
      author={Ruixuan Xiao and Lei Feng and Kai Tang and Junbo Zhao and Yixuan Li and Gang Chen and Haobo Wang},
      booktitle={In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
      year={2024}
}

How Useful is Continued Pre-Training for Generative Unsupervised Domain Adaptation?
Rheeya Uppaal, Yixuan Li and Junjie Hu
Annual Meeting of the Association for Computational Linguistics (ACL), RepL4NLP Workshop, 2024.
[BibTeX] [PDF]

How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection?
Soumya Suvra Ghosal*, Yiyou Sun*, Yixuan Li
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}
}

Uncertainty Quantification via Localized Gradients for Deep Learning-based Medical Image Assessments
Brayden Schott, Dmitry Pinchuk, Victor Santoro-Fernandes, Žan Klaneček, Luciano Rivetti, Alison Deatsch, Scott Perlman, Yixuan Li, Robert Jeraj
Journal of Physics in Medicine and Biology , 2024
[BibTeX] [PDF]

@article{Schott_2024,
doi = {10.1088/1361-6560/ad611d},
url = {https://dx.doi.org/10.1088/1361-6560/ad611d},
year = {2024},
month = {jul},
publisher = {IOP Publishing},
volume = {69},
number = {15},
pages = {155015},
author = {Brayden Schott and Dmitry Pinchuk and Victor Santoro-Fernandes and Žan Klaneček and Luciano Rivetti and Alison Deatsch and Scott Perlman and Yixuan Li and Robert Jeraj},
title = {Uncertainty quantification via localized gradients for deep learning-based medical image assessments},
journal = {Physics in Medicine & Biology},
}

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
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
Journal of Data-centric Machine Learning Research (DMLR), 2024
Neural Information Processing Systems (NeurIPS), DistShift Workshop, 2023
[BibTeX] [PDF] [Code] [Project Page]

Dream the Impossible: Outlier Imagination with Diffusion Models
Xuefeng Du, Yiyou Sun, Xiaojin Zhu, Yixuan Li
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}
}

Learning to Augment Distributions for Out-of-Distribution Detection
Qizhou Wang*, Zhen Fang*, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
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}
}

A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
Yiyou Sun, Zhenmei Shi, Yixuan Li
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}
}

A Critical Analysis of Out-of-Distribution Detection for Document Understanding
Jiuxiang Gu*, Yifei Ming*, Yi Zhou, Jason Kuen, Vlad Morariu, Anqi Liu, Yixuan Li, Tong Sun and Ani Nenkova
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}
}

When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis
Yiyou Sun, Zhenmei Shi, Yingyu Liang, Yixuan Li
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}
}

Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D Nowak, Yixuan Li
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}
}

Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li
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}
}

How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?
Yifei Ming and Yixuan Li
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}
}

Are Vision Transformers Robust to Spurious Correlations?
Soumya Suvra Ghosal and Yixuan Li
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}
}

Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection
Rheeya Uppaal, Junjie Hu, Yixuan Li
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}
}

Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment
Yiyou Sun, Yaojie Liu, Xiaoming Liu, Yixuan Li, Wen-Sheng Chu
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}
}

How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
Yifei Ming, Yiyou Sun, Ousmane Dia, and Yixuan Li
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}
}

Non-Parametric Outlier Synthesis
Leitian Tao, Xuefeng Du, Xiaojin Zhu, and Yixuan Li
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}
}

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions
Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang
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}
}

OpenCon: Open-world Contrastive Learning
Yiyou Sun and Yixuan Li
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}
}

A Survey on Out-of-Distribution Detection in NLP
Hao Lang, Yinhe Zheng, Yixuan Li, Jian Sun, Fei Huang, Yongbin Li
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}
}
}

Distributionally Robust Optimization with Probabilistic Group
Soumya Suvra Ghosal and Yixuan Li
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}
}

Out-of-distribution Detection via Frequency-regularized Generative Models
Mu Cai and Yixuan Li
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}
}

Task Agnostic and Post-hoc Unseen Distribution Detection
Radhika Dua, Seongjun Yang, Yixuan Li, and Edward Choi
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}
}

SIREN: Shaping Representations for Detecting Out-of-Distribution Objects
Xuefeng Du, Gabriel Gozum, Yifei Ming, Yixuan Li
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}
}

Delving into Out-of-Distribution Detection with Vision-Language Representations
Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li
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}
}

Is Out-of-Distribution Detection Learnable?
Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, and Feng Liu
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}
}

SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning
Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao
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}
}

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
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
Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2022
[BibTeX] [PDF] [Code]

DICE: Leveraging Sparsification for Out-of-Distribution Detection
Yiyou Sun and Yixuan Li
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}
}

POEM: Out-of-Distribution Detection with Posterior Sampling
Yifei Ming*, Ying Fan*, and Yixuan Li
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}
}

Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu, and Yixuan Li
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}
}

Training OOD Detectors in their Natural Habitats
Julian Katz-Samuels*, Julia Nakhleh*, Robert Nowak, and Yixuan Li
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}
}

Mitigating Neural Network Overconfidence with Logit Normalization
Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, and Yixuan Li
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}
}

Are Vision Transformers Robust to Spurious Correlations?
Soumya Suvra Ghosal, Yifei Ming, and Yixuan Li
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},
}

Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild
Xuefeng Du, Xin Wang, Gabriel Gozum, and Yixuan Li
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}
}

VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li
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}
}

PiCO: Contrastive Label Disambiguation for Partial Label Learning
Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, and Junbo Zhao
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}
}

Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza and Yixuan Li
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}
}

On the Impact of Spurious Correlation for Out-of-distribution Detection
Yifei Ming, Hang Yin and Yixuan Li
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}
}

A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, Mohammad Sabokrou
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}
}

ReAct: Out-of-distribution Detection With Rectified Activations
Yiyou Sun, Chuan Guo and Yixuan Li
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}
}

Can multi-label classification networks know what they don’t know?
Haoran Wang*, Weitang Liu, Alex Bocchieri and Yixuan Li*
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}
 }

On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang, Andrew Geng and Yixuan Li
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}
}

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng, Yixuan Li and Gao Huang
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}
}

ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
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}
}

MOS: Scaling Out-of-distribution Detection to Large Semantic Space
Rui Huang and Yixuan Li
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}
}

MOOD: Multi-level Out-of-distribution Detection
Ziqian Lin*, Sreya Dutta Roy* and Yixuan Li
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}
}

LOOD: Localization-based Uncertainty Estimation for Medical Imaging
Yiyou Sun*, Bastin Joseph*, Alison Deatsch, Robert Jeraj and Yixuan Li
International Conference on Machine Learning (ICML), DFUQ Workshop, 2021.
Spotlight paper
[BibTeX]

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel*, Albert Gu*, Yixuan Li and Christopher Ré
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}
}

Energy-based Out-of-distribution Detection
Weitang Liu, Xiaoyun Wang, John Owens and Yixuan Li
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}
}

Informative Outlier Matters: Robustifying Out-of-distribution Detection Using Outlier Mining
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
ICML workshop on Uncertainty and Robustness in Deep Learning (ICML UDL), 2020
[BibTeX] [PDF]
Beyond the Pixels: Exploring the Effect of Video File Corruptions on Model Robustness
Trenton Chang, Dan Fu, Yixuan Li, and Christopher Ré
ECCV Workshop, 2020
[PDF] [Slides] [Video]

MSURU: Large Scale E-commerce Image Classification With Weakly Supervised Search Data
Yina Tang*, Fedor Borisyuk*, Siddarth Malreddy*, Yixuan Li*, Yiqun Liu* and Sergey Kirshner*
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}
}

Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
Abhinmanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li and Dhruv Mahajan
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}
}

Exploring the Limits of Weakly Supervised Pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten
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}
}

Understanding the Loss Surface of Neural Networks for Binary Classification
Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant,
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}
}

Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification
Shiyu Liang, Ruoyu Sun, Yixuan Li, and R. Srikant
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}
  }

Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang, Yixuan Li, and R. Srikant
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}
}

Snapshot Ensembles: Train 1, Get M for Free
Gao Huang*, Yixuan Li*, Geoff Pleiss, Zhuang Liu, John Hopcroft, and Kilian Weinberger
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}
}

Stacked Adversarial Generative Networks
Xun Huang, Yixuan Li,Omid Poursaeed, John Hopcroft, and Serge Belongie
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}
}

Towards Measuring and Inferring User Interest From Gaze
Yixuan Li, Pingmei Xu, Dmitry Lagun, and Vidhya Navalpakkam
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}
}

Local spectral clustering for overlapping community detection
Yixuan Li, Kun He, Kyle Kloster, David Bindel, and John Hopcroft
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}
}

Convergent Learning: Do different neural networks learn the same representations?
Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft, and Hod Lipson
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}
}

In a World that Counts: Clustering and Detecting Fake Social Engagement at Scale
Yixuan Li, Oscar Martinez, Xing Chen, Yi Li, and John Hopcroft
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}
}

The Lifecycle and Cascade of Social Messaging Groups
Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang and John Hopcroft
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}
}

Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions
Kyle Kloster and Yixuan Li
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}
}

Deep Manifold Traversal: Changing Labels with Convolutional Features
Jacob Gardner, Paul Upchurch, Matt Kusner, Yixuan Li, Kilian Weinberger, Kavita Bala, and John Hopcroft
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}
}

Convergent Learning: Do different neural networks learn the same representations?
Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft, and Hod Lipson
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}
  }

Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach
Yixuan Li, Kun He, David Bindel, and John Hopcroft
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}
}

Detecting Overlapping Communities from Local Spectral Subspaces
Kun He, Yiwei Sun, David Bindel, John Hopcroft, and Yixuan Li
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}
}

On Multicast Capacity and Delay in Cognitive Radio Mobile Ad-hoc Networks
Jinbei Zhang, Yixuan Li, Zhuotao Liu, Fan Wu, Feng Yang, and Xinbing Wang
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}
}

Multicast Capacity With Max-Min Fairness for Heterogeneous Networks
Yixuan Li, Qiuyu Peng, Xinbing Wang
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}
}

Sharon Li

Publications and Preprints