On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks. - Xiangrui Li; Xin Li 081; Deng Pan 001; Dongxiao Zhu (AAAI, 2020)

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability. - Deng Pan 001; Xiangrui Li; Xin Li 081; Dongxiao Zhu (IJCAI, 2020)

Improve SGD Training via Aligning Mini-batches. - Xiangrui Li; Deng Pan 001; Xin Li 081; Dongxiao Zhu (CoRR, 2020)

Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints. - Xin Li 081; Xiangrui Li; Deng Pan 001; Dongxiao Zhu (AAAI, 2021)

Explaining Deep Neural Network Models with Adversarial Gradient Integration. - Deng Pan 001; Xin Li 081; Dongxiao Zhu (IJCAI, 2021)

Defending Against Adversarial Attacks On Medical Imaging Ai System, Classification Or Detection? - Xin Li 081; Deng Pan 001; Dongxiao Zhu (ISBI, 2021)

AttCAT: Explaining Transformers via Attentive Class Activation Tokens. - Yao Qiang; Deng Pan 001; Chengyin Li; Xin Li 081; Rhongho Jang; Dongxiao Zhu (NeurIPS, 2022)

Learning Compact Features via In-Training Representation Alignment. - Xin Li 081; Xiangrui Li; Deng Pan 001; Yao Qiang; Dongxiao Zhu (AAAI, 2023)

Negative Flux Aggregation to Estimate Feature Attributions. - Xin Li 081; Deng Pan 001; Chengyin Li; Yao Qiang; Dongxiao Zhu (IJCAI, 2023)