In addressing the imbalanced issue of data within the realm of Natural Language
Processing, text data augmentation methods have emerged as pivotal solutions. This data …

Large language models (LLMs) have demonstrated remarkable advancements, primarily
due to their capabilities in modeling the hidden relationships within text sequences. This …

Emerging topics in biomedical research are continuously expanding, providing a wealth of
information about genes and their function. This rapid proliferation of knowledge presents …

Multimodal recommendation systems (MMRS) have received considerable attention from
the research community due to their ability to jointly utilize information from user behavior …

An increasing demand for model explainability has accompanied the widespread adoption
of transformers in various fields of applications. In this paper, we conduct a survey of the …

Zero-Shot Hashing (ZSH) has aroused significant attention due to its efficiency and
generalizability in multi-modal retrieval scenarios, which aims to encode semantic …

Prosthetic joint infection (PJI) is a prevalent and severe complication characterized by high
diagnostic challenges. Currently, a unified diagnostic standard incorporating both computed …

Automatic disease diagnosis from symptoms has attracted much attention in medical
practices. It can assist doctors and medical practitioners in narrowing down disease …

This paper proposes an innovative method that exploits a complex deep learning network
architecture, called Hierarchical Deep Neural Network (HDNN), specifically developed for …

Prosthetic Joint Infection (PJI) is a prevalent and severe complication characterized by high
diagnostic challenges. Currently, a unified diagnostic standard incorporating both computed …