Yao Li

25 papers A* 6Journal 16Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Defense Against Syntactic Textual Backdoor Attacks With Token Substitution.
IEEE Trans. Inf. Forensics Secur.
Xianwen He, Xinglin Li, Yao Li, Minhao Cheng
2024 — conf
AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation.
ECCV (79)
Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu
2024 J jnl
Adversarial Examples Detection With Bayesian Neural Network.
IEEE Trans. Emerg. Top. Comput. Intell.
Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee
2024 A* conf
DALD: Improving Logits-based Detector without Logits from Black-box LLMs.
NeurIPS
Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu
2024 J jnl
Defense Against Syntactic Textual Backdoor Attacks with Token Substitution.
CoRR
Xinglin Li, Xianwen He, Yao Li, Minhao Cheng
2024 J jnl
Improving Logits-based Detector without Logits from Black-box LLMs.
CoRR
Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu
2024 J jnl
Trusted Aggregation (TAG): Backdoor Defense in Federated Learning.
Trans. Mach. Learn. Res.
Joseph Lavond, Minhao Cheng, Yao Li
2024 J jnl
Uncovering Distortion Differences: A Study of Adversarial Attacks and Machine Discriminability.
IEEE Access
Xiawei Wang, Yao Li, Cho-Jui Hsieh, Thomas C. M. Lee
2023 A* conf
Accelerating Dataset Distillation via Model Augmentation.
CVPR
Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu
2023 J jnl
DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation.
CoRR
Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu
2023 A* conf
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model.
CVPR
Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu
2022 A* conf
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation.
EMNLP
Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang
2022 J jnl
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation.
CoRR
Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang
2022 J jnl
Accelerating Dataset Distillation via Model Augmentation.
CoRR
Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu
2022 J jnl
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model.
CoRR
Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu
2021 J jnl
A Review of Adversarial Attack and Defense for Classification Methods.
CoRR
Yao Li, Minhao Cheng, Cho-Jui Hsieh, Thomas C. M. Lee
2021 J jnl
Detecting Adversarial Examples with Bayesian Neural Network.
CoRR
Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee
2021 A* conf
Towards Robustness of Deep Neural Networks via Regularization.
ICCV
Yao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh
2020 J jnl
Uncertainty Quantification for High-Dimensional Sparse Nonparametric Additive Models.
Technometrics
Qi Gao, Randy C. S. Lai, Thomas C. M. Lee, Yao Li
2019 — conf
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network.
ICLR (Poster)
Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2018 J jnl
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network.
CoRR
Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2018 A* conf
Learning from Group Comparisons: Exploiting Higher Order Interactions.
NeurIPS
Yao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh
2018 J jnl
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding.
CoRR
Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas C. M. Lee, Erik Kruus
2017 J jnl
Positive-Unlabeled Demand-Aware Recommendation.
CoRR
Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li
2017 — conf
Scalable Demand-Aware Recommendation.
NIPS
Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li