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20222026
most citedEfficient Serving of LLM Applications with Probabilistic Demand Modeling

1 citations · 3 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.CR2025

ThinkTrap: Denial-of-Service Attacks against Black-box LLM Services via Infinite Thinking

Yunzhe Li, Jianan Wang, Hongzi Zhu +3

Large Language Models (LLMs) have become foundational components in a wide range of applications, including natural language understanding and generation, embodied intelligence, an…

cs.CV2025

BlinkBud: Detecting Hazards from Behind via Sampled Monocular 3D Detection on a Single Earbud

Yunzhe Li, Jiajun Yan, Yuzhou Wei +7

Failing to be aware of speeding vehicles approaching from behind poses a huge threat to the road safety of pedestrians and cyclists. In this paper, we propose BlinkBud, which utili…

cs.DC2025

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving

Huanqi Hu, Bowen Xiao, Shixuan Sun +8

Quantization is a critical technique for accelerating LLM inference by reducing memory footprint and improving computational efficiency. Among various schemes, 4-bit weight and 8-b…

cs.DC2025★ 1 cited

Efficient Serving of LLM Applications with Probabilistic Demand Modeling

Yifei Liu, Zuo Gan, Zhenghao Gan +8

Applications based on Large Language Models (LLMs) contains a series of tasks to address real-world problems with boosted capability, which have dynamic demand volumes on diverse b…

cs.DC2025

Efficient Unified Caching for Accelerating Heterogeneous AI Workloads

Tianze Wang, Yifei Liu, Chen Chen +8

Modern AI clusters, which host diverse workloads like data pre-processing, training and inference, often store the large-volume data in cloud storage and employ caching frameworks…

cs.DC2025

eLLM: Elastic Memory Management Framework for Efficient LLM Serving

Jiale Xu, Rui Zhang, Yi Xiong +11

Large Language Models are increasingly being deployed in datacenters. Serving these models requires careful memory management, as their memory usage includes static weights, dynami…

cs.DB2025

Revisiting the Design of In-Memory Dynamic Graph Storage

Jixian Su, Chiyu Hao, Shixuan Sun +7

The effectiveness of in-memory dynamic graph storage (DGS) for supporting concurrent graph read and write queries is crucial for real-time graph analytics and updates. Various meth…