240 citations · 248 across the 8 of their papers we have counts for
9 papers
Cleaning Logs for Downstream Tasks (Registered Report)
Zahra G. Yazdi, Van-Hoang Le, Nyyti Saarimäki +3
Background: Software systems generate logs during execution to record critical events and runtime information for troubleshooting and monitoring. However, in practice, logs often c…
Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining
Van-Hoang Le, Duc-Vu Nguyen, Kiet Van Nguyen +1
Large Language Models (LLMs) face significant challenges in specialized domains like law, where precision and domain-specific knowledge are critical. This paper presents a streamli…
Stronger, Cheaper and Demonstration-Free Log Parsing with LLMs
Yi Xiao, Van-Hoang Le, Hongyu Zhang
Log parsing, the process of converting raw log messages into structured formats, is an important initial step for automated analysis of logs of large-scale software systems. Tradit…
OptLLM: Optimal Assignment of Queries to Large Language Models
Yueyue Liu, Hongyu Zhang, Yuantian Miao +2
Large Language Models (LLMs) have garnered considerable attention owing to their remarkable capabilities, leading to an increasing number of companies offering LLMs as services. Di…
LogShrink: Effective Log Compression by Leveraging Commonality and Variability of Log Data
Xiaoyun Li, Hongyu Zhang, Van-Hoang Le +1
Log data is a crucial resource for recording system events and states during system execution. However, as systems grow in scale, log data generation has become increasingly explos…
Log Parsing: How Far Can ChatGPT Go?
Van-Hoang Le, Hongyu Zhang
Software logs play an essential role in ensuring the reliability and maintainability of large-scale software systems, as they are often the sole source of runtime information. Log…
Log Parsing with Prompt-based Few-shot Learning
Van-Hoang Le, Hongyu Zhang
Logs generated by large-scale software systems provide crucial information for engineers to understand the system status and diagnose problems of the systems. Log parsing, which co…
Log-based Anomaly Detection with Deep Learning: How Far Are We?
Van-Hoang Le, Hongyu Zhang
Software-intensive systems produce logs for troubleshooting purposes. Recently, many deep learning models have been proposed to automatically detect system anomalies based on log d…
Log-based Anomaly Detection Without Log Parsing
Van-Hoang Le, Hongyu Zhang
Software systems often record important runtime information in system logs for troubleshooting purposes. There have been many studies that use log data to construct machine learnin…