Mintong Kang

About Me

I am Mintong Kang, a second-year Ph.D. student at UIUC CS advised by Prof. Bo Li. My research interest lies in trustworthy machine learning including robustness, fairness, and uncertainty quantification. Recently, I am interested in the trustworthiness properties of large language models and diffusion models. I am working on exploring the vulnerabilities of them and develop more robust and reliable applications with them in practice.

Before that, I got the bachelor of engineering degree from the CS department of Zhejiang University. I work with Prof. Xi Li at DCD Lab @ Zhejiang University. I also luckily work with Prof. Alan L. Yuille at CCVL Lab @ Johns Hopkins University.

News

• [May. 2024] Two papers accepted to ICML 2024.
• [Jan. 2024] One paper accepted to ICLR 2024.
• [Dec. 2023] One paper selected as Outstanding Paper Award in NeurIPS 2023.
• [Nov. 2023] Received NeurIPS 2023 Scholar Award.
• [Sep. 2023] Two papers accepted to NeurIPS 2023.
• [Jun. 2023] Organized KLR workshop at ICML 2023.
• [Nov. 2022] One paper accepted to SaTML 2023.
• [Oct. 2022] Received NeurIPS 2022 Scholar Award.
• [Sep. 2022] Two papers accepted to NeurIPS 2022.

Research Papers

• C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models
  Mintong Kang, Nezihe Merve Gürel, Ning Yu, Dawn Song, Bo Li
  [ICML 2024] (Forty-first International Conference on Machine Learning)
  [PDF] [Code]

• Certifiably Byzantine-Robust Federated Conformal Prediction
  Mintong Kang, Zhen Lin, Jimeng Sun, Cao Xiao, Bo Li
  [ICML 2024] (Forty-first International Conference on Machine Learning)
  [PDF] [Code]

• COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction Via Probablistic Circuits
  Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li
  [ICLR 2024] (Twelfth International Conference on Learning Representations)
  [PDF] [Code]

• DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
  Boxin Wang*, Weixin Chen*, Hengzhi Pei*, Chulin Xie*, Mintong Kang*, Chenhui Zhang*, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
  [NeurIPS 2023] (Outstanding Paper Award, Oral) (Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track)
  [PDF] [Code]

• DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification
  Mintong Kang, Dawn Song, Bo Li
  [NeurIPS 2023] (Thirty-seventh Conference on Neural Information Processing Systems)
  [PDF] [Code]

• Certifying Some Distributional Fairness with Subpopulation Decomposition
  Mintong Kang*, Linyi Li*, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
  [NeurIPS 2022] (Spotlight) (Thirty-sixth Conference on Neural Information Processing Systems)
  [PDF] [Code]

• Fairness in Federated Learning via Core-Stability
  Bhaskar Ray Chaudhury, Linyi Li, Mintong Kang, Bo Li, Ruta Mehta
  [NeurIPS 2022] (Spotlight) (Thirty-sixth Conference on Neural Information Processing Systems)
  [PDF] [Code]

• Label-Assemble: Leveraging Multiple Datasets with Partial Labels
  Mintong Kang, Yongyi Lu, Alan L. Yuille, Zongwei Zhou
  [IBSI 2023] (IEEE International Symposium on Biomedical Imaging 2023)
  [PDF] [Code] [Slide]

• FaShapley: Fast and Approximated Shapley Based Model Pruning Towards Certifiably Robust DNNs
  Mintong Kang, Linyi Li, Bo Li
  [SaTML 2023] (IEEE Conference on Secure and Trustworthy Machine Learning 2023)
  [PDF] [Code]

• MgSvF: Multi-Grained Slow vs. Fast Framework for Few-Shot Class-Incremental Learning
  Hanbin Zhao, Yongjian Fu, Mintong Kang, Qi Tian, Fei Wu, Xi Li
  [TPAMI 2021] (IEEE Transactions on Pattern Analysis and Machine Intelligence 2021)
  [PDF] [Code]

Services

• Conference Reviewers: ICML 2022-2023; NeurIPS 2022-2023; ICLR 2024; CVPR 2023-2024; KDD 2023.
• Workshop organizer: KLR@ICML 2023.

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