most citedL4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2025

Trace Sampling 2.0: Code Knowledge Enhanced Span-level Sampling for Distributed Tracing

Yulun Wu, Guangba Yu, Zhihan Jiang +2

Distributed tracing is an essential diagnostic tool in microservice systems, but the sheer volume of traces places a significant burden on backend storage. A common approach to mit…

cs.SE2025

KPIRoot+: An Efficient Integrated Framework for Anomaly Detection and Root Cause Analysis in Large-Scale Cloud Systems

Wenwei Gu, Renyi Zhong, Guangba Yu +8

To ensure the reliability of cloud systems, their performance is monitored using KPIs (key performance indicators). When issues arise, root cause localization identifies KPIs respo…

cs.SE2025

COCA: Generative Root Cause Analysis for Distributed Systems with Code Knowledge

Yichen Li, Yulun Wu, Jinyang Liu +4

Runtime failures are commonplace in modern distributed systems. When such issues arise, users often turn to platforms such as Github or JIRA to report them and request assistance.…

cs.SE20251 cited

L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis

Zhihan Jiang, Junjie Huang, Zhuangbin Chen +6

As Large Language Models (LLMs) show their capabilities across various applications, training customized LLMs has become essential for modern enterprises. However, due to the compl…

cs.SE2024

FaaSRCA: Full Lifecycle Root Cause Analysis for Serverless Applications

Jin Huang, Pengfei Chen, Guangba Yu +3

Serverless becomes popular as a novel computing paradigms for cloud native services. However, the complexity and dynamic nature of serverless applications present significant chall…

cs.SE2024

Mint: Cost-Efficient Tracing with All Requests Collection via Commonality and Variability Analysis

Haiyu Huang, Cheng Chen, Kunyi Chen +6

Distributed traces contain valuable information but are often massive in volume, posing a core challenge in tracing framework design: balancing the tradeoff between preserving esse…