2026
Membership Inference Attacks Against Fine-tuned Diffusion Language Models
ICLR 2026poster
Diffusion Language Models (DLMs) represent a promising alternative to autoregressive language models, using bidirectional masked token prediction. Yet their susceptibility to privacy leakage via Membership Inference Attacks (MIA) remains critically underexplored. This paper presents the first system…