collaborators

6 papers

cs.DB2026

Carnot: Interpretable, Interactive, and Optimized Execution of Deep Research Queries

Matthew Russo, Yash Agarwal, Tianyu Li +5

Enterprises increasingly seek to query data lakes using natural language via AI-driven tools like semantic operators or deep research agents. However, the latter operates as an opa…

cs.AI2026

PEEK: Context Map as an Orientation Cache for Long-Context LLM Agents

Zhuohan Gu, Qizheng Zhang, Omar Khattab +1

Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across invocations, existing approach…

cs.OS2026

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.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

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.MA2025

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…