Where to Start Alignment? Diffusion Large Language Model May Demand a Distinct Position

Understand

Diffusion Large Language Models (dLLMs) have recently emerged as a competitive non-autoregressive paradigm due to their unique training and inference approach.

• However, there is currently a lack of safety study on this novel architecture.
• In this paper, we present the first analysis of dLLMs' safety performance and propose a novel safety alignment method tailored to their unique generation characteristics.
• Specifically, we identify a critical asymmetry between the defender and attacker in terms of security.