activity
20112025
most citedRCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models

87 citations · 101 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CE2025

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash +40

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Sc…

cs.LG2024★ 1 cited

KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs

Ruoqi Liu, Lingfei Wu, Ping Zhang

Treatment effect estimation (TEE) is the task of determining the impact of various treatments on patient outcomes. Current TEE methods fall short due to reliance on limited labeled…

cs.CL2024

FACE: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition

Xiaoqiang Wang, Lingfei Wu, Tengfei Ma +1

Large language models (LLMs) are primarily evaluated by overall performance on various text understanding and generation tasks. However, such a paradigm fails to comprehensively di…

cs.SE2023★ 87 cited

RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models

Zefan Wang, Zichuan Liu, Yingying Zhang +6

Large language model (LLM) applications in cloud root cause analysis (RCA) have been actively explored recently. However, current methods are still reliant on manual workflow setti…

cs.CY2021★ 1 cited

Low-skilled Occupations Face the Highest Upskilling Pressure

Di Tong, Lingfei Wu, James Allen Evans

Substantial scholarship has estimated the susceptibility of jobs to automation, but little has examined how job contents evolve in the information age as new technologies substitut…

cs.IR2011★ 12 cited

The Accelerating Growth of Online Tagging Systems

Lingfei Wu

Research on the growth of online tagging systems not only is interesting in its own right, but also yields insights for website management and semantic web analysis. Traditional mo…