| Attcat: Explaining transformers via attentive class activation tokens Y Qiang, D Pan, C Li, X Li, R Jang, D Zhu Advances in neural information processing systems 35, 5052-5064, 2022 | 25 | 2022 |
| Toward tag-free aspect based sentiment analysis: A multiple attention network approach Y Qiang, X Li, D Zhu 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 17 | 2020 |
| Counterfactual Interpolation Augmentation (CIA): A Unified Approach to Enhance Fairness and Explainability of DNN. Y Qiang, C Li, M Brocanelli, D Zhu IJCAI, 732-739, 2022 | 14 | 2022 |
| Auto-prompting sam for mobile friendly 3d medical image segmentation C Li, P Khanduri, Y Qiang, RI Sultan, I Chetty, D Zhu arXiv preprint arXiv:2308.14936, 2023 | 12 | 2023 |
| Hijacking large language models via adversarial in-context learning Y Qiang, X Zhou, D Zhu arXiv preprint arXiv:2311.09948, 2023 | 9 | 2023 |
| Tiny rnn model with certified robustness for text classification Y Qiang, STS Kumar, M Brocanelli, D Zhu 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 9 | 2022 |
| Fairness-aware vision transformer via debiased self-attention Y Qiang, C Li, P Khanduri, D Zhu arXiv preprint arXiv:2301.13803, 2023 | 5 | 2023 |
| Interpretability-aware vision transformer Y Qiang, C Li, P Khanduri, D Zhu arXiv preprint arXiv:2309.08035, 2023 | 4 | 2023 |
| FocalUNETR: A Focal Transformer for Boundary-aware Prostate Segmentation using CT Images Chengyin Li, Yao Qiang, Rafi Lbn Sultan, Hassan Bagher-Ebadian, Prashant ... MICCAI(2023) International Conference on Medical Image Computing and …, 2023 | 4* | 2023 |
| Negative flux aggregation to estimate feature attributions X Li, D Pan, C Li, Y Qiang, D Zhu arXiv preprint arXiv:2301.06989, 2023 | 4 | 2023 |
| Learning compact features via in-training representation alignment X Li, X Li, D Pan, Y Qiang, D Zhu arXiv preprint arXiv:2211.13332, 2022 | 4 | 2022 |
| Saliency guided adversarial training for learning generalizable features with applications to medical imaging classification system X Li, Y Qiang, C Li, S Liu, D Zhu arXiv preprint arXiv:2209.04326, 2022 | 2 | 2022 |
| Prompt perturbation consistency learning for robust language models Y Qiang, S Nandi, N Mehrabi, GV Steeg, A Kumar, A Rumshisky, ... arXiv preprint arXiv:2402.15833, 2024 | | 2024 |
| Learning to Poison Large Language Models During Instruction Tuning Y Qiang, X Zhou, SZ Zade, MA Roshani, D Zytko, D Zhu arXiv preprint arXiv:2402.13459, 2024 | | 2024 |
| FedDRO: Federated Compositional Optimization for Distributionally Robust Learning P Khanduri, C Li, RI Sultan, Y Qiang, J Kliewer, D Zhu arXiv preprint arXiv:2311.12652, 2023 | | 2023 |
| Proximal Compositional Optimization for Distributionally Robust Learning P Khanduri, C Li, RI Sultan, Y Qiang, J Kliewer, D Zhu The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023 | | 2023 |
| Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification Y Qiang, STS Kumar, M Brocanelli, D Zhu arXiv preprint arXiv:2101.05624, 2021 | | 2021 |
| On the Implementation and Evaluation of Loss Functions for Robust Multiple Anatomy Segmentation on CT Images C Li, R Ibn Sultan, H Bagher-Ebadian, Y Qiang, K Thind, D Zhu, I Chetty Hassan and Qiang, Yao and Thind, Kundan and Zhu, Dongxiao and Chetty, Indrin …, 0 | | |
Dongxiao ZhuProfessor of Computer Science, Wayne State UniversityVahvistettu sähköpostiosoite verkkotunnuksessa wayne.edu
