Information extraction suffers from its varying targets, heterogeneous structures, and
demand-specific schemas. In this paper, we propose a unified text-to-structure generation …

Sentiment analysis (SA) has been a long-standing research area in natural language
processing. It can offer rich insights into human sentiments and opinions and has thus seen …

Aspect-based sentiment analysis (ABSA) has received increasing attention recently. Most
existing work tackles ABSA in a discriminative manner, designing various task-specific …

The state-of-the-art methods in aspect-level sentiment classification have leveraged the
graph based models to incorporate the syntactic structure of a sentence. While being …

Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years,
which typically involves four fundamental sentiment elements, including the aspect category …

In this paper, we investigate the modeling power of contextualized embeddings from pre-
trained language models, eg BERT, on the E2E-ABSA task. Specifically, we build a series of …

ChatGPT has stimulated the research boom in the field of large language models. In this
paper, we assess the capabilities of ChatGPT from four perspectives including Performance …

Dependency trees have been intensively used with graph neural networks for aspect-based
sentiment classification. Though being effective, such methods rely on external dependency …

Aspect-oriented Fine-grained Opinion Extraction (AFOE) aims at extracting aspect terms and
opinion terms from review in the form of opinion pairs or additionally extracting sentiment …

It is popular that neural graph-based models are applied in existing aspect-based sentiment
analysis (ABSA) studies for utilizing word relations through dependency parses to facilitate …