Khái niệm cốt lõi
DivLog proposes an effective log parsing framework based on in-context learning (ICL) of large language models (LLMs) to generate log templates in a training-free manner, achieving state-of-the-art performance.
Thống kê
DivLog는 16개의 널리 사용되는 로그 데이터셋에서 Parsing Accuracy, Precision Template Accuracy, Recall Template Accuracy를 평균적으로 98.1%, 92.1%, 92.9% 달성
Trích dẫn
"DivLog achieves state-of-the-art performance in log parsing accuracy across various datasets."
"The proposed prompt format restricts the output to enhance the quality of generated log templates."