Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness. - Xinli Yue; Ningping Mou; Qian Wang 002; Lingchen Zhao (NeurIPS, 2023)

Revisiting Adversarial Training Under Long-Tailed Distributions. - Xinli Yue; Ningping Mou; Qian Wang 002; Lingchen Zhao (CVPR, 2024)

Revisiting Video Quality Assessment from the Perspective of Generalization. - Xinli Yue; Jianhui Sun; Liangchao Yao; Fan Xia; Yuetang Deng; Tianyi Wang; Lei Li; Fengyun Rao; Jing Lv; Qian Wang 002; Lingchen Zhao (CoRR, 2024)

Advancing Video Quality Assessment for AIGC. - Xinli Yue; Jianhui Sun; Han Kong; Liangchao Yao; Tianyi Wang; Lei Li; Fengyun Rao; Jing Lv; Fan Xia; Yuetang Deng; Qian Wang 002; Lingchen Zhao (CoRR, 2024)

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment. - Shuhao Han; Haotian Fan; Fangyuan Kong; Wenjie Liao; Chunle Guo; Chongyi Li; Radu Timofte; Liang Li; Tao Li; Junhui Cui; Yunqiu Wang; Yang Tai; et al. (CVPR Workshops, 2025)

Instruction-augmented Multimodal Alignment for Image-Text and Element Matching. - Xinli Yue; Jianhui Sun; Junda Lu; Liangchao Yao; Fan Xia; Tianyi Wang; Fengyun Rao; Jing Lyu; Yuetang Deng (CVPR Workshops, 2025)

Fairness is essential for robustness: fair adversarial training by identifying and augmenting hard examples. - Ningping Mou; Xinli Yue; Lingchen Zhao; Qian Wang 002 (Frontiers Comput. Sci., 2025)

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment. - Shuhao Han; Haotian Fan; Fangyuan Kong; Wenjie Liao; Chunle Guo; Chongyi Li; Radu Timofte; Liang Li; Tao Li; Junhui Cui; Yunqiu Wang; Yang Tai; et al. (CoRR, 2025)