Fairness in machine learning has attracted increasing attention in recent years. The fairness
methods improving algorithmic fairness for in-distribution data may not perform well under …

Clinical trials are indispensable in developing new treatments, but they face obstacles in
patient recruitment and retention, hindering the enrollment of necessary participants. To …

The exponential growth in scholarly publications necessitates advanced tools for efficient
article retrieval, especially in interdisciplinary fields where diverse terminologies are used to …

Large Language Models (LLMs) have recently become proficient in addressing complex
tasks by utilizing their rich internal knowledge and reasoning ability. Consequently, this …

The issue of bias in Machine Learning (ML) models is a significant challenge for the
machine learning community. Real-world biases can be embedded in the data used to train …