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cs.CL2026
Less Uniform Discrete Diffusion is More Powerful and Scalable
Kaibo Wang, Ding Ding, Fangyu Ding +5
Although uniform diffusion language models (UDLMs) represent a promising diffusion paradigm, scaling them remains challenging. We identify the core obstacle as an over-uniform trai…
cs.CL2026
Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes
Fangyu Ding, Ding Ding, Sijin Chen +8
While Masked Diffusion Language Models (MDLMs) relying on token masking and unmasking have shown promise in language modeling, their computational efficiency and generation flexibi…