Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …

Pre-trained Language Models (PLMs) which are trained on large text corpus via self-
supervised learning method, have yielded promising performance on various tasks in …

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

Recently, ChatGPT has drawn great attention from both the research community and the
public. We are particularly interested in whether it can serve as a universal sentiment …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

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 …

GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on, have gained
considerable attention due to their exceptional natural language processing capabilities …

Universally modeling all typical information extraction tasks (UIE) with one generative
language model (GLM) has revealed great potential by the latest study, where various IE …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Business failure prediction or survival analysis can assist corporate organizations in better
understanding their performance and improving decision making. Based on aspect-based …