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Ying-Hui Li

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#artificial intelligence Preprint Sep 2026

Decoupling Readiness from Release for Tail-Aware Scheduling of Agentic LLM Workflows

This work presents a tail-risk-aware turn release scheduling method that jointly decides which ready turn to release next and how much released but unfinished work to maintain, and reduces the P95 of workflow flow time under contention, achieving up to a \(3.50\times\) speedup.

Bo-Chao Feng, Jian-Jiang Li, Haojie Wang et al. · 0 citations
#small language model Preprint Sep 2026

Epoch: Compiling Diffusion Blocks for Sparse MoE Serving

A serving system that treats the diffusion block as a compilation unit that improves end-to-end execution time by up to 2.7 times over the strongest surviving baseline under the same 8-GPU placement and remains feasible at the largest batch sizes where multiple baselines run out of memory, while preserving task quality...

Jia-Nian Zhu, Hang Wu, Ying-Hui Li et al. · 0 citations
Book Open access Jul 2026

Taming Dynamic Diffusion LLM Inference through Virtual Static Execution

Prism abstracts the highly dynamic diffusion workload into a predictable, static execution flow transparent to the compiler, and achieves this via three techniques: spatial regularization, temporal stabilization, and specialized kernels that selectively bypass padding data.

Jianian Zhu, Hang Wu, Yinghui Li et al. · 0 citations

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