Zhu, Dongxiao

16 publications

ICLR 2026 Attention Smoothing Is All You Need for Unlearning Saleh Zare Zade, Xiangyu Zhou, Sijia Liu, Dongxiao Zhu

MIDL 2026 FluenceFormer: Transformer-Driven Multi-Beam Fluence mAP Regression for Radiotherapy Planning Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim, Kundan Thind, Dongxiao Zhu

WACV 2025 AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation Chengyin Li, Rafi Ibn Sultan, Prashant Khanduri, Yao Qiang, Chetty Indrin, Dongxiao Zhu

WACV 2025 MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Chengyin Li, Hui Zhu, Rafi Ibn Sultan, Hassan Bagher Ebadian, Prashant Khanduri, Chetty Indrin, Kundan Thind, Dongxiao Zhu

ECCV 2024 Fairness-Aware Vision Transformer via Debiased Self-Attention Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu

AAAI 2024 MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Minhui Xue, Dongxiao Zhu, Kim-Kwang Raymond Choo

AAAI 2023 Learning Compact Features via In-Training Representation Alignment Xin Li, Xiangrui Li, Deng Pan, Yao Qiang, Dongxiao Zhu

IJCAI 2023 Negative Flux Aggregation to Estimate Feature Attributions Xin Li, Deng Pan, Chengyin Li, Yao Qiang, Dongxiao Zhu

ICMLW 2023 Proximal Compositional Optimization for Distributionally Robust Learning Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan, Yao Qiang, Joerg Kliewer, Dongxiao Zhu

NeurIPS 2022 AttCAT: Explaining Transformers via Attentive Class Activation Tokens Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, Dongxiao Zhu

IJCAI 2022 Counterfactual Interpolation Augmentation (CIA): A Unified Approach to Enhance Fairness and Explainability of DNN Yao Qiang, Chengyin Li, Marco Brocanelli, Dongxiao Zhu

ECML-PKDD 2022 Coupling User Preference with External Rewards to Enable Driver-Centered and Resource-Aware EV Charging Recommendation Chengyin Li, Zheng Dong, Nathan Fisher, Dongxiao Zhu

IJCAI 2021 Explaining Deep Neural Network Models with Adversarial Gradient Integration Deng Pan, Xin Li, Dongxiao Zhu

AAAI 2021 Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints Xin Li, Xiangrui Li, Deng Pan, Dongxiao Zhu

IJCAI 2020 Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu

AAAI 2020 On the Learning Property of Logistic and SoftMax Losses for Deep Neural Networks Xiangrui Li, Xin Li, Deng Pan, Dongxiao Zhu