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cs.CL2025
DND: Boosting Large Language Models with Dynamic Nested Depth
Tieyuan Chen, Xiaodong Chen, Haoxing Chen +3
We introduce Dynamic Nested Depth (DND), a novel method that improves performance for off-the-shelf LLMs by selecting critical tokens to reprocess in a nested depth manner. Specifi…
cs.CL2025
CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit
Kangyu Wang, Zhiyun Jiang, Haibo Feng +5
Diffusion large language models (dLLMs) generate text through iterative denoising. In commonly adopted parallel decoding schemes, each step confirms only high-confidence positions…