DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models B Wang*, W Chen*, H Pei*, C Xie*, M Kang*, C Zhang*, C Xu, Z Xiong, ... NeurIPS 2023, 2023 | 185 | 2023 |
Mgsvf: Multi-grained slow vs. fast framework for few-shot class-incremental learning H Zhao, Y Fu, M Kang, Q Tian, F Wu, X Li TPAMI 2021, 2021 | 73* | 2021 |
Fairness in federated learning via core-stability B Ray Chaudhury, L Li, M Kang, B Li, R Mehta NeurIPS 2022, 2022 | 21 | 2022 |
Certifying Some Distributional Fairness with Subpopulation Decomposition M Kang*, L Li*, M Weber, Y Liu, C Zhang, B Li NeurIPS 2022, 2022 | 13 | 2022 |
Label-assemble: Leveraging multiple datasets with partial labels M Kang, B Li, Z Zhu, Y Lu, EK Fishman, A Yuille, Z Zhou ISBI 2023, 2023 | 9* | 2023 |
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models M Kang, NM Gürel, N Yu, D Song, B Li ICML 2024, 2024 | 4* | 2024 |
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification M Kang, D Song, B Li NeurIPS 2023, 2023 | 4 | 2023 |
FaShapley: Fast and Approximated Shapley Based Model Pruning Towards Certifiably Robust DNNs M Kang, L Li, B Li SaTML 2023, 2023 | 2 | 2023 |
Certifiably Byzantine-Robust Federated Conformal Prediction M Kang, Z Lin, J Sun, C Xiao, B Li ICML 2024, 2024 | | 2024 |
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits M Kang, NM Gürel, L Li, B Li ICLR 2024, 2023 | | 2023 |