We cannot overemphasize the essence of contextual information in most natural language
processing (NLP) applications. The extraction of context yields significant improvements in …

Recently, the emergence of pre-trained models (PTMs) has brought natural language
processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs …

As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …

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 …

Thanks to the breakthrough of large-scale pre-trained language model (PLM) technology,
prompt-based classification tasks, eg, sentiment analysis and emotion detection, have …

Language models pretrained on text from a wide variety of sources form the foundation of
today's NLP. In light of the success of these broad-coverage models, we investigate whether …

Aspect-based sentiment analysis aims to determine the sentiment polarity towards a specific
aspect in online reviews. Most recent efforts adopt attention-based neural network models to …

Abstract In early 2023, the Artificial Intelligence (AI) industry experienced a significant
advancement with the emergence of OpenAI's ChatGPT, a research product that …

Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Product reviews contain a large number of implicit aspects and implicit opinions. However,
most of the existing studies in aspect-based sentiment analysis ignored this problem. In this …