3 papers
cs.LG2026
Invisible Safety Threat: Malicious Finetuning for LLM via Steganography
Guangnian Wan, Xinyin Ma, Gongfan Fang +1
Understanding and addressing potential safety alignment risks in large language models (LLMs) is critical for ensuring their safe and trustworthy deployment. In this paper, we high…
cs.CR2026
Self-Purification Mitigates Backdoors in Multimodal Diffusion Language Models
Guangnian Wan, Qi Li, Gongfan Fang +2
Multimodal Diffusion Language Models (MDLMs) have recently emerged as a competitive alternative to their autoregressive counterparts. Yet their vulnerability to backdoor attacks re…
cs.AI2025
CoT-Valve: Length-Compressible Chain-of-Thought Tuning
Xinyin Ma, Guangnian Wan, Runpeng Yu +2
Chain-of-Thought significantly enhances a model's reasoning capability, but it also comes with a considerable increase in inference costs due to long chains. With the observation t…