Adversarial Prompt Tuning for Vision-Language Models. - Jiaming Zhang 006; Xingjun Ma; Xin Wang 119; Lingyu Qiu; Jiaqi Wang 003; Yu-Gang Jiang 001; Jitao Sang (ECCV (45), 2024)

Multi-level Distributional Discrepancy Enhancement for Cross Domain Face Forgery Detection. - Lingyu Qiu; Ke Jiang; Sinan Liu; Xiaoyang Tan (PRCV (15), 2024)

LDCDroid: Learning data drift characteristics for handling the model aging problem in Android malware detection. - Zhen Liu 017; Ruoyu Wang 002; Bitao Peng; Lingyu Qiu; Qingqing Gan; Changji Wang; Wenbin Zhang 002 (Comput. Secur., 2025)

MF-CLIP: Leveraging CLIP as Surrogate Models for No-Box Adversarial Attacks. - Jiaming Zhang 006; Lingyu Qiu; Qi Yi; Yige Li; Jitao Sang; Changsheng Xu; Dit-Yan Yeung (IEEE Trans. Inf. Forensics Secur., 2025)

Towards One-shot Federated Learning: Advances, Challenges, and Future Directions. - Flora Amato; Lingyu Qiu; Mohammad Tanveer 001; Salvatore Cuomo; Fabio Giampaolo; Francesco Piccialli (CoRR, 2025)

RoGA: Towards Generalizable Deepfake Detection through Robust Gradient Alignment. - Lingyu Qiu; Ke Jiang; Xiaoyang Tan (CoRR, 2025)

Contrastive Desensitization Learning for Cross Domain Face Forgery Detection. - Lingyu Qiu; Ke Jiang; Xiaoyang Tan (CoRR, 2025)

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models. - Jiaming Zhang 006; Xin Wang 119; Xingjun Ma; Lingyu Qiu; Yu-Gang Jiang; Jitao Sang (CoRR, 2025)