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Planner-Guided Recursive Exploration for Diffusion Language Model Decoding
Masked diffusion language models (DLMs) enable parallel text generation by iteratively refining masked tokens, offering a promising alternative to autoregressive decoding. Recent search-based decoding methods improve the accuracy--efficiency trade-off by exploring multiple candidate decoding traject
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