3 papers
cs.LG2026
Mosaic: Unlocking Long-Context Inference for Diffusion LLMs via Global Memory Planning and Dynamic Peak Taming
Liang Zheng, Bowen Shi, Yitao Hu +5
Diffusion-based large language models (dLLMs) have emerged as a promising paradigm, utilizing simultaneous denoising to enable global planning and iterative refinement. While these…
cs.LG2025
RAGPulse: An Open-Source RAG Workload Trace to Optimize RAG Serving Systems
Zhengchao Wang, Yitao Hu, Jianing Ye +4
Retrieval-Augmented Generation (RAG) is a critical paradigm for building reliable, knowledge-intensive Large Language Model (LLM) applications. However, the multi-stage pipeline (r…
cs.DC2024
Harpagon: Minimizing DNN Serving Cost via Efficient Dispatching, Scheduling and Splitting
Zhixin Zhao, Yitao Hu, Ziqi Gong +5
Advances in deep neural networks (DNNs) have significantly contributed to the development of real-time video processing applications. Efficient scheduling of DNN workloads in cloud…