The human ability to learn, generalize, and control complex manipulation tasks through multi-
modality feedback suggests a unique capability, which we refer to as dexterity intelligence …

In NLP research, unsupervised or semisupervised learning techniques are increasingly
getting more attention. These learning techniques are capable of learning from data that has …

Generating novel and useful concepts is essential during the early design stage to explore a
large variety of design opportunities, which usually requires advanced design thinking ability …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …

This review presents a comprehensive exploration of hybrid and ensemble deep learning
models within Natural Language Processing (NLP), shedding light on their transformative …

Objective Plain language in medicine has long been advocated as a way to improve patient
understanding and engagement. As the field of Natural Language Processing has …

Pseudo-code written in natural language can aid the comprehension of source code in
unfamiliar programming languages. However, the great majority of source code has no …

Humans use rich natural language to describe and communicate visual perceptions. In
order to provide natural language descriptions for visual content, this paper combines two …

Machine translation (MT) is an important task in natural language processing (NLP), as it
automates the translation process and reduces the reliance on human translators. With the …