Denoising Surface: Modeling and Predicting Inference Cost for Diffusion LLM Serving
As diffusion large language models (dLLMs) become more capable, they are moving from research settings to real-world \textit{serving}, where request management (such as scheduling and resource allocation) relies on accurate estimation of per-request inference cost. However, common cost proxies fall short for dLLMs: out...
Hao-Yu Zheng, Fang-Cheng Fu, Bin-Hang Yuan et al.
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