DLLM-VSR applies diffusion LLMs to VSR via masked denoising, two-stage training, and length-guided candidate decoding to reach 19.5% WER on LRS3.
Diffusion llm with native variable generation lengths: Let [eos] lead the way.arXiv preprint arXiv:2510.24605, 2025
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iLLaDA is an 8B masked diffusion LM trained from scratch with bidirectional attention, reporting gains of 14-21 points on BBH, ARC, MATH and HumanEval over prior diffusion models while remaining competitive with Qwen2.5-7B.
VoidPadding decouples padding from termination in MDLMs via a new [VOID] token, delivering +17.84 average benchmark points and 55.7% fewer decoding steps on Dream-7B-Instruct.
citing papers explorer
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Diffusion Large Language Models for Visual Speech Recognition
DLLM-VSR applies diffusion LLMs to VSR via masked denoising, two-stage training, and length-guided candidate decoding to reach 19.5% WER on LRS3.
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Improved Large Language Diffusion Models
iLLaDA is an 8B masked diffusion LM trained from scratch with bidirectional attention, reporting gains of 14-21 points on BBH, ARC, MATH and HumanEval over prior diffusion models while remaining competitive with Qwen2.5-7B.
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VoidPadding: Let [VOID] Handle Padding in Masked Diffusion Language Models so that [EOS] Can Focus on Semantic Termination
VoidPadding decouples padding from termination in MDLMs via a new [VOID] token, delivering +17.84 average benchmark points and 55.7% fewer decoding steps on Dream-7B-Instruct.