6 citations · 8 across the 18 of their papers we have counts for
7 papers · 1 filter
MEPIC: Memory Efficient Position Independent Caching for LLM Serving
Qian Wang, Zahra Yousefijamarani, Morgan Lindsay Heisler +8
Modern LLM applications such as deep-research assistants, coding agents, and Retrieval-Augmented Generation (RAG) systems, repeatedly process long prompt histories containing share…
Scaling Graph Chain-of-Thought Reasoning: A Multi-Agent Framework with Efficient LLM Serving
Chengying Huan, Ziheng Meng, Yongchao Liu +11
Graph Chain-of-Thought (Graph-CoT) enables large language models (LLMs) to perform step-by-step reasoning over graph-structured knowledge, but existing pipelines suffer from low ac…
BOASF: A Unified Framework for Speeding up Automatic Machine Learning via Adaptive Successive Filtering
Guanghui Zhu, Xin Fang, Feng Cheng +4
Machine learning has been making great success in many application areas. However, for the non-expert practitioners, it is always very challenging to address a machine learning tas…
Chordless Structure: A Pathway to Simple and Expressive GNNs
Hongxu Pan, Shuxian Hu, Mo Zhou +5
Researchers have proposed various methods of incorporating more structured information into the design of Graph Neural Networks (GNNs) to enhance their expressiveness. However, the…
CoDec: Prefix-Shared Decoding Kernel for LLMs
Zhibin Wang, Rui Ning, Chao Fang +12
Prefix-sharing among multiple prompts presents opportunities to combine the operations of the shared prefix, while attention computation in the decode stage, which becomes a critic…
Revisiting Service Level Objectives and System Level Metrics in Large Language Model Serving
Zhibin Wang, Shipeng Li, Yuhang Zhou +7
User experience is a critical factor Large Language Model (LLM) serving systems must consider, where service level objectives (SLOs) considering the experience of individual reques…
Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization
Jingfan Chen, Guanghui Zhu, Chunfeng Yuan +1
Bayesian optimization is a broadly applied methodology to optimize the expensive black-box function. Despite its success, it still faces the challenge from the high-dimensional sea…