SelfCAD: Protecting Your Efficient Reasoning Capabilities via Self-Cautious Insertion
Taiye Chen, Mingjie Li, Yichuan Mo, Shuo Feng, and Yisen Wang. (2026). "SelfCAD: Protecting Your Efficient Reasoning Capabilities via Self-Cautious Insertion."
CV
Education
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
- M.S. in Jekyll, GitHub University, 2014
- B.S. in GitHub, GitHub University, 2012
Work experience
- Spring 2024: Academic Pages Collaborator
- GitHub University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
- Fall 2015: Research Assistant
- GitHub University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
- Summer 2015: Research Assistant
- GitHub University
- Duties included: Tagging issues
- Supervisor: Professor Git
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
TrustLDM: Benchmarking Trustworthiness in Language Diffusion Model
Yichuan Mo, Yukun Jiang, Yanbo Shi, Mingjie Li, Michael Backes, Yang Zhang, and Yisen Wang. (2026). "TrustLDM: Benchmarking Trustworthiness in Language Diffusion Model." ICLR 2026 Trustworthy Workshop.
Decoding Large Language Diffusion Models with Foreseeing Movement
Yichuan Mo, Quan Chen, Mingjie Li, Zeming Wei, and Yisen Wang. (2026). "Decoding Large Language Diffusion Models with Foreseeing Movement." ICLR 2026 DeLTa Workshop.
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
Zeming Wei, Yifei Wang, Li Ang, Yichuan Mo, and Yisen Wang. (2026). "Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations." TPAMI 2026.
On the Adversarial Transferability of Generalized “Skip Connections”
Yisen Wang, Yichuan Mo, Dongxian Wu, Mingjie Li, Xingjun Ma, and Zhouchen Lin. (2026). "On the Adversarial Transferability of Generalized "Skip Connections"." TPAMI 2026.
Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training
Yisen Wang, Yichuan Mo, Hongjun Wang, Junyi Li, and Zhouchen Lin. (2025). "Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training." arXiv preprint arXiv:2510.13361.
Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning
Ang Li, Yichuan Mo, Mingjie Li, Yifei Wang, and Yisen Wang. (2025). "Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning." arXiv preprint arXiv:2502.09673.
Fight Back Against Jailbreaking via Prompt Adversarial Tuning
Yichuan Mo, Yuji Wang, Zeming Wei, and Yisen Wang. (2024). "Fight Back Against Jailbreaking via Prompt Adversarial Tuning." NeurIPS 2024.
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
Yichuan Mo, Hui Huang, Mingjie Li, Ang Li, and Yisen Wang. (2024). "TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors." ICML 2024.
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li, and Yisen Wang. (2024). "PID: Prompt-Independent Data Protection Against Latent Diffusion Models." ICML 2024.
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, and Yisen Wang. (2022). "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture." NeurIPS 2022.
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space
Yang Li, Yichuan Mo, Liangliang Shi, Junchi Yan, Xiaolu Zhang, and Jun Zhou. (2022). "Improving Generative Adversarial Networks via Adversarial Learning in Latent Space." NeurIPS 2022.
DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness
Qibing Ren, Yiting Chen, Yichuan Mo, Qitian Wu, and Junchi Yan. (2022). "DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness." SIGKDD 2022.
Multi-Task Learning Improves Synthetic Speech Detection
Yichuan Mo, and Shilin Wang. (2022). "Multi-Task Learning Improves Synthetic Speech Detection." ICASSP 2022.
Talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA, USA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley, CA, USA
Talk 1 on Relevant Topic in Your Field
Talk at UC San Francisco, Department of Testing, San Francisco, CA, USA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams