Recent developments in deep learning, coupled with an increasing number of sequenced
proteins, have led to a breakthrough in life science applications, in particular in protein …

Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

This paper presents a novel framework, artificial intelligence-enabled intelligent assistant
(AIIA), for personalized and adaptive learning in higher education. The AIIA system …

Evolution is a blind fitting process by which organisms become adapted to their
environment. Does the brain use similar brute-force fitting processes to learn how to …

With the recent advances in deep learning, different approaches to improving pre-trained
language models (PLMs) have been proposed. PLMs have advanced state-of-the-art …

The recent improvements of language models have drawn much attention to potential cases
of use and abuse of automatically generated text. Great effort is put into the development of …

In the clinical and healthcare domains, medical images play a critical role. A mature medical
visual question answering system (VQA) can improve diagnosis by answering clinical …

Transfer learning has proven to be crucial in advancing the state of speech and natural
language processing research in recent years. In speech, a model pre-trained by self …

Antimicrobial resistance has become a critical global health problem due to the abuse of
conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides …

Advanced protein structure prediction requires evolutionary information from multiple
sequence alignments (MSAs) from evolutionary couplings that are not always available …