Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

As voice user interfaces (VUIs) rapidly transform the landscape of human–computer
interaction, their potential to revolutionize user engagement is becoming increasingly …

Abstract Knowledge graphs are sizeable graph-structured knowledge with both abstract and
concrete concepts in the form of entities and relations. Recently, convolutional neural …

Recent progress in using machine learning models for reasoning tasks has been driven by
novel model architectures, large-scale pre-training protocols, and dedicated reasoning …

Most medical dialogue systems assume that patients have clear goals (medicine querying,
surgical operation querying, etc.) before medical consultation. However, in many real …

With the popularity of ChatGPT, there has been increasing attention towards dialogue
systems. Researchers are dedicated to designing a knowledgeable model that can engage …

Automating radiology report generation can significantly alleviate radiologists' workloads.
Previous research has primarily focused on realizing highly concise observations while …

Link prediction in open knowledge graphs (OpenKGs) is crucial for applications like
question answering and recommendation systems. Existing OpenKG models leverage the …

Knowledge-enhanced text generation aims to enhance the quality of generated text by
utilizing internal or external knowledge sources. While language models have demonstrated …

Inductive link prediction over knowledge graphs (KGs) aims to perform inference over a new
graph with unseen entities. In contrast to transductive link prediction, which learns a fixed set …