Boosting Large Language Models with Continual Learning for Aspect-based Sentiment Analysis

arXiv:2405.05496v1 Announce Type: new
Abstract: Aspect-based sentiment analysis (ABSA) is an important subtask of sentiment analysis, which aims to extract the aspects and predict their sentiments. Most existing studies focus on improving the performance of the target domain by fine-tuning domain-specific models (trained on source domains) based on the target domain dataset. Few works propose continual learning tasks for ABSA, which aim to learn the target domain's ability while maintaining the history domains' abilities. In this paper, we propose a …

abstract analysis arxiv boosting continual cs.cl domain domains extract fine-tuning focus improving language language models large language large language models performance sentiment sentiment analysis studies type