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cs.CL2026
SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding
Na Li, Chengda Wang, Mingju Gao +1
Diffusion large language models (DLLMs) enable non-autoregressive generation by iteratively denoising corrupted token sequences with bidirectional context. Despite their ability to…
cs.CL2026
SemBlock: Semantic Boundary Dynamic Blocks for Diffusion LLMs
Xinrui Song, Zhuoran Wang, Mingju Gao +1
Diffusion language models (DLMs) generate text through iterative denoising, and blockwise decoding improves their practicality by committing tokens in local blocks. However, existi…
cs.CL2025
CtrlDiff: Boosting Large Diffusion Language Models with Dynamic Block Prediction and Controllable Generation
Chihan Huang, Hao Tang
Although autoregressive models have dominated language modeling in recent years, there has been a growing interest in exploring alternative paradigms to the conventional next-token…