The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

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

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

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 …

Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

The whole sentence representation reasoning process simultaneously comprises a
sentence representation module and a semantic reasoning module. This paper combines …

In the natural language processing literature, neural networks are becoming increasingly
deeper and complex. The recent poster child of this trend is the deep language …

Text similarity measurement is the basis of natural language processing tasks, which play an
important role in information retrieval, automatic question answering, machine translation …

Ranking models lie at the heart of research on information retrieval (IR). During the past
decades, different techniques have been proposed for constructing ranking models, from …

In recent years, deep neural networks have led to exciting breakthroughs in speech
recognition, computer vision, and natural language processing (NLP) tasks. However, there …