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.
During denois- ing, positions whose confidence exceeds 0.9 are committed; if no position exceeds the threshold, the most confident position is committed
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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.