Multi-Task Learning Improves Synthetic Speech Detection. - Yichuan Mo; Shilin Wang (ICASSP, 2022)

DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness. - Qibing Ren; Yiting Chen 003; Yichuan Mo; Qitian Wu; Junchi Yan (KDD, 2022)

Improving Generative Adversarial Networks via Adversarial Learning in Latent Space. - Yang Li 197; Yichuan Mo; Liangliang Shi; Junchi Yan (NeurIPS, 2022)

When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. - Yichuan Mo; Dongxian Wu; Yifei Wang 001; Yiwen Guo; Yisen Wang 001 (NeurIPS, 2022)

PID: Prompt-Independent Data Protection Against Latent Diffusion Models. - Ang Li; Yichuan Mo; Mingjie Li 007; Yisen Wang 001 (ICML, 2024)

TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors. - Yichuan Mo; Hui Huang; Mingjie Li 007; Ang Li; Yisen Wang 001 (ICML, 2024)

Fight Back Against Jailbreaking via Prompt Adversarial Tuning. - Yichuan Mo; Yuji Wang; Zeming Wei; Yisen Wang 001 (NeurIPS, 2024)

Studious Bob Fight Back Against Jailbreaking via Prompt Adversarial Tuning. - Yichuan Mo; Yuji Wang; Zeming Wei; Yisen Wang 001 (CoRR, 2024)

On the Adversarial Transferability of Generalized "Skip Connections". - Yisen Wang 001; Yichuan Mo; Dongxian Wu; Mingjie Li 007; Xingjun Ma; Zhouchen Lin (CoRR, 2024)

Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning. - Ang Li; Yichuan Mo; Mingjie Li 007; Yifei Wang 001; Yisen Wang 001 (CoRR, 2025)