collaborators

5 papers

cs.OS2025

EVICPRESS: Joint KV-Cache Compression and Eviction for Efficient LLM Serving

Shaoting Feng, Yuhan Liu, Hanchen Li +11

Reusing KV cache is essential for high efficiency of Large Language Model (LLM) inference systems. With more LLM users, the KV cache footprint can easily exceed GPU memory capacity…

cs.LG2025

LMCache: An Efficient KV Cache Layer for Enterprise-Scale LLM Inference

Yuhan Liu, Yihua Cheng, Jiayi Yao +8

KV cache has traditionally been stored in GPU memory to accelerate the decoding phase of large language model (LLM) inference. However, it is increasingly necessary to move KV cach…

cs.OS2025

AdaptCache: KV Cache Native Storage Hierarchy for Low-Delay and High-Quality Language Model Serving

Shaoting Feng, Hanchen Li, Kuntai Du +8

Large language model (LLM) applications often reuse previously processed context, such as chat history and documents, which introduces significant redundant computation. Existing L…

cs.LG2024

METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation

Siddhant Ray, Rui Pan, Zhuohan Gu +5

RAG (Retrieval Augmented Generation) allows LLMs (large language models) to generate better responses with external knowledge, but using more external knowledge often improves gene…

cs.MA2024

DroidSpeak: KV Cache Sharing for Cross-LLM Communication and Multi-LLM Serving

Yuhan Liu, Yuyang Huang, Jiayi Yao +9

Compound AI systems, such as agentic systems, are an emerging trend in large-scale enterprise settings, with multiple LLMs specialized for different users, tasks, and/or roles work…