Abstract Named Entity Recognition (NER) is an important component of Natural Language
Processing (NLP) and is a fundamental yet challenging task in text analysis. Recently, NER …

The Chinese radiology report summarization is a crucial component in smart healthcare that
employs language models to summarize key findings in radiology reports and communicate …

Large Language Models (LLMs), which bridge the gap between human language
understanding and complex problem-solving, achieve state-of-the-art performance on …

Recently, various parameter-efficient fine-tuning (PEFT) strategies for application to
language models have been proposed and successfully implemented. However, this raises …

The engineering geology report serves as a comprehensive portrayal of the geological
conditions and information within a surveyed region, making it highly valuable for extracting …

The detection of mental disorders through social media has received significant attention.
With the growing prevalence of Autism Spectrum Disorder (ASD) and the inherent difficulties …

Graph representation learning faces challenges in node classification tasks due to the
intricate interplay between node categories, topological structure, significant characteristics …

Data efficiency plays a pivotal role in medical image segmentation where data labeling is
expensive and time consuming. However, there are few effective methods to enhance data …

Automatic radiology report summarization has been an attractive research problem towards
computer-aided diagnosis to alleviate physicians' workload in recent years. However …

Multi-modal learning aims at simultaneously modelling data from several modalities such as
image, text and speech. The goal is to simultaneously learn representations and make them …