Conceitos essenciais
Large language models (LLMs) can be effectively utilized for log parsing with the introduction of LILAC, a practical framework that leverages in-context learning and adaptive parsing cache to enhance accuracy and efficiency.
Estatísticas
The recent emergence of powerful large language models (LLMs) demonstrates their vast pre-trained knowledge related to code and logging.
Extensive evaluation on public large-scale datasets shows that LILAC outperforms state-of-the-art methods by 69.5% in template accuracy.