📝 Publications

🗡️🛡️ Jailbreak Attacks and Defenses

ACL 2025

Hierarchical Safety Realignment: Lightweight Restoration of Safety in Pruned Large Vision-Language Models \ Yue Li^*, Xin Yi^*, Dongsheng Shi, Gerard de Melo, Xiaoling Wang and Linlin Wang^†.

Arxiv | Project | ACL Anthology

• The current pruning methods will lead to a significant degradation of the model’s safety at a higher sparsity.
• The HSR (Hierarchical Safety Realignment) method we proposed can achieve safety realignment for the pruned model by restoring only a very small number of neurons. HSR is effective for both LLM and LVLM.

• ESWA 2026 Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks, Xin Yi, Yue Li, Dongsheng Shi, Linlin Wang^†, Xiaoling Wang and Liang He.

• Preprint Unified defense for large language models against jailbreak and fine-tuning attacks in education, Xin Yi, Yue Li, Dongsheng Shi, Linlin Wang^†, Xiaoling Wang and Liang He.

📄🔍 Model Watermarks and Fingerprints

• Preprint AGMark: Attention-Guided Dynamic Watermarking for Large Vision-Language Models, Yue Li^*, Xin Yi^*, Dongsheng Shi, Yongyi Cui, Gerard de Melo and Linlin Wang^†.

• Preprint From Construction to Injection: Edit-Based Fingerprints for Large Language Models, Yue Li^*, Xin Yi^*, Dongsheng Shi, Yongyi Cui, Gerard de Melo and Linlin Wang^†.

• KBS 2025 Unified Attacks to Large Language Model Watermarks: Spoofing and Scrubbing in Unauthorized Knowledge Distillation, Xin Yi, Yue Li, Shunfan Zheng, Linlin Wang^†, Xiaoling Wang and Liang He.

🗃️📊 Benchmarks

• ESWA 2026 Benchmarking Large Language Models for End-to-End Clinical Support in Traditional Chinese Medicine, Dongsheng Shi, Xin Yi, Yue Li, Linlin Wang^†.

👻💭 Model Hallucinations

• IJCNN 2026 Process Alignment: Verifiable Knowledge Distillation for Mitigating Hallucinations in Large Language Models, Weicong Ni, Yue Li, Dongsheng Shi, Linlin Wang^†.