6 papers
HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models
Weilin Jin, Mingyu Wang, Wenbo Li +5
Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucinations, where model outputs…
LogPTR: Variable-Aware Log Parsing with Pointer Network
Yifan Wu, Bingxu Chai, Siyu Yu +4
Due to the sheer size of software logs, developers rely on automated log analysis. Log parsing, which parses semi-structured logs into a structured format, is a prerequisite of aut…
DeLog: An Efficient Log Compression Framework with Pattern Signature Synthesis
Siyu Yu, Yifan Wu, Junjielong Xu +8
Parser-based log compression, which separates static templates from dynamic variables, is a promising approach to exploit the unique structure of log data. However, its performance…
A Survey of AIOps in the Era of Large Language Models
Lingzhe Zhang, Tong Jia, Mengxi Jia +7
As large language models (LLMs) grow increasingly sophisticated and pervasive, their application to various Artificial Intelligence for IT Operations (AIOps) tasks has garnered sig…
An Empirical Study on Commit Message Generation using LLMs via In-Context Learning
Yifan Wu, Yunpeng Wang, Ying Li +5
Commit messages concisely describe code changes in natural language and are important for software maintenance. Several approaches have been proposed to automatically generate comm…
Log Parsing using LLMs with Self-Generated In-Context Learning and Self-Correction
Yifan Wu, Siyu Yu, Ying Li
Log parsing transforms log messages into structured formats, serving as a crucial step for log analysis. Despite a variety of log parsers that have been proposed, their performance…