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News/Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models
arxiv
PublishedJune 11, 2026 at 4:00 AM
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Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models

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arXiv:2606.12273v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer an efficient alternative to autoregressive models through parallel decoding, yet existing post-training methods largely rely on random masking strategies that overlook intrinsic token dependencies. In this

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