Abstract Aspect-Based Sentiment Analysis (ABSA) is a fine-grained task in sentiment
analysis, aiming to identify sentiment expressed towards specific aspects of an entity. This …

Dimensional aspect-based sentiment analysis (dimABSA) aims to recognize aspect-level
quadruples from reviews, offering a fine-grained sentiment description for user opinions. A …

Recently, Large Language Models (LLMs) have garnered increasing attention in the field of
natural language processing, revolutionizing numerous downstream tasks with powerful …

Aspect-based sentiment analysis (ABSA) assesses sentiments towards specific aspects
within texts, resulting in detailed sentiment tuples. Previous ABSA models often use static …

Aspect-based sentiment analysis (ABSA) has recently received considerable attention within
the Natural Language Processing (NLP) community, especially for complex tasks like triplet …

We present LADy ᖡ, a Python-based benchmark toolkit to facilitate extracting aspects of
products or services in reviews toward which customers target their opinions and …

Abstract Aspect Sentiment Quad Prediction (ASQP) enhances the scope of aspect-based
sentiment analysis by introducing the necessity to predict both explicit and implicit aspect …

In this work we investigate the capability of Graph Attention Network for extracting aspect
and opinion terms. Aspect and opinion term extraction is posed as a token-level …

Generative models have shown excellent results in aspect-based sentiment analysis tasks
by predicting quadruples by setting specific template formats. The existing research predicts …

The dimensional approach can represent more fine-grained emotional information than
discrete affective states. In this paper, a pretrained language model (PLM) with a joint …