Hugging Face Trending Papers June 10, 2026

Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models

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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 work, we present an empirical analysis of attention in dLLMs and show that tokens attending more strongly to unmasked context exhibit greater generation stability and play a critical role in reasoning.

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DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention

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