Recently, the performance of Pre-trained Language Models (PLMs) has been significantly
improved by injecting knowledge facts to enhance their abilities of language understanding. …

Medical text mining aims to learn models to extract useful information from medical sources.
A major challenge is obtaining large-scale labeled data in the medical domain for model …

Knowledge-Enhanced Pre-trained Language Models (KEPLMs) improve the language
understanding abilities of deep language models by leveraging the rich semantic knowledge …

Variational autoencoders (VAEs) have been widely applied in recommendations. One reason
is that their amortized inferences are beneficial for overcoming the data sparsity. However, …

Conditional Variational AutoEncoder (CVAE) is promising for modeling one-to-many
relationships in dialogue generation, as it can naturally generate many responses from a given …

Energy consumption optimization is crucial for improving the quality of application services
in the industrial Internet of Things (IIoT) environment. Traditional optimization methods often …

Ammonia-fueled solid oxide fuel cells (SOFCs) have attracted the focus of researchers due
to no carbon emissions in utilization. Understanding the reaction mechanism is vital for the …

Generating explanations for recommendation systems is essential for improving its transparency
since informative explanations such as generated reviews can help users comprehend …

High-emitting vehicles cause disproportionate air pollutants, thus making the identification
and control of high-emitters a critical issue to reduce air pollution. On-road emission remote …

SmartNICs have become an indispensable communication fabric and computing substrate
in today’s data centers and enterprise clusters, providing in-network computing capabilities …