Abstract In Text Classification, modern neural networks have achieved great performance,
but simultaneously, it is sensitive to adversarial examples. Existing studies usually use …

Machine learning algorithms have had a profound impact on the field of computer science
over the past few decades. The performance of these algorithms heavily depends on the …

Sleep staging is helpful in assessing sleep quality and diagnosing sleep disorders.
However, how to adequately capture the temporal and spatial relations of the brain during …

Sleep staging is essential for sleep assessment and plays an important role in disease
diagnosis, which refers to the classification of sleep epochs into different sleep stages …

Deep neural networks (DNNs) are increasingly deployed as integral parts of software
systems. However, due to the complex interconnections among hidden layers and massive …

This paper reports on a study of cross-lingual information retrieval (CLIR) using the mT5-
XXL reranker on the NeuCLIR track of TREC 2022. Perhaps the biggest contribution of this …

The transformer-based models have become the de-facto standard for natural language
processing (NLP) tasks. However, most of these models are only designed to capture the …

Referring image segmentation has sprung up benefiting from the outstanding performance
of deep neural networks. However, most existing methods explore either local details or the …

Recent work has demonstrated that pretrained transformers are overconfident in text
classification tasks, which can be calibrated by the famous post-hoc calibration method …

Machine Learning algorithms have had a profound impact on the field of computer science
over the past few decades. These algorithms performance is greatly influenced by the …