Toward Tag-free Aspect Based Sentiment Analysis: A Multiple Attention Network Approach. - Yao Qiang; Xin Li 081; Dongxiao Zhu (IJCNN, 2020)

Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification. - Yao Qiang; Supriya Tumkur Suresh Kumar; Marco Brocanelli; Dongxiao Zhu (CoRR, 2021)

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

Tiny RNN Model with Certified Robustness for Text Classification. - Yao Qiang; Supriya Tumkur Suresh Kumar; Marco Brocanelli; Dongxiao Zhu (IJCNN, 2022)

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

Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System. - Xin Li 081; Yao Qiang; Chengyin Li; Sijia Liu; Dongxiao Zhu (CoRR, 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)

FocalUNETR: A Focal Transformer for Boundary-Aware Prostate Segmentation Using CT Images. - Chengyin Li; Yao Qiang; Rafi Ibn Sultan; Hassan Bagher-Ebadian; Prashant Khanduri; Indrin J. Chetty; Dongxiao Zhu (MICCAI (3), 2023)

Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation. - Chengyin Li; Prashant Khanduri; Yao Qiang; Rafi Ibn Sultan; Indrin J. Chetty; Dongxiao Zhu (CoRR, 2023)

Interpretability-Aware Vision Transformer. - Yao Qiang; Chengyin Li; Prashant Khanduri; Dongxiao Zhu (CoRR, 2023)

Hijacking Large Language Models via Adversarial In-Context Learning. - Yao Qiang; Xiangyu Zhou; Dongxiao Zhu (CoRR, 2023)

FedDRO: Federated Compositional Optimization for Distributionally Robust Learning. - Prashant Khanduri; Chengyin Li; Rafi Ibn Sultan; Yao Qiang; Jörg Kliewer; Dongxiao Zhu (CoRR, 2023)

Prompt Perturbation Consistency Learning for Robust Language Models. - Yao Qiang; Subhrangshu Nandi; Ninareh Mehrabi; Greg Ver Steeg; Anoop Kumar; Anna Rumshisky; Aram Galstyan (EACL (Findings), 2024)

Fairness-Aware Vision Transformer via Debiased Self-Attention. - Yao Qiang; Chengyin Li; Prashant Khanduri; Dongxiao Zhu (ECCV (37), 2024)

Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge Graph. - Mona Zamiri; Yao Qiang; Fedor Nikolaev; Dongxiao Zhu; Alexander Kotov 001 (WWW, 2024)

Learning to Poison Large Language Models During Instruction Tuning. - Yao Qiang; Xiangyu Zhou; Saleh Zare Zade; Mohammad Amin Roshani; Douglas Zytko; Dongxiao Zhu (CoRR, 2024)

Generative LLM Powered Conversational AI Application for Personalized Risk Assessment: A Case Study in COVID-19. - Mohammad Amin Roshani; Xiangyu Zhou; Yao Qiang; Srinivasan Suresh 001; Steve Hicks; Usha Sethuraman; Dongxiao Zhu (CoRR, 2024)

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

Automatic Calibration for Membership Inference Attack on Large Language Models. - Saleh Zare Zade; Yao Qiang; Xiangyu Zhou; Hui Zhu 016; Mohammad Amin Roshani; Prashant Khanduri; Dongxiao Zhu (CoRR, 2025)

Not All Tokens Are Meant to Be Forgotten. - Xiangyu Zhou; Yao Qiang; Saleh Zare Zade; Douglas Zytko; Prashant Khanduri; Dongxiao Zhu (CoRR, 2025)