Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Artificial Intelligence (AI) algorithms are increasingly providing decision making and
operational support across multiple domains. AI includes a wide (and growing) library of …

Existing calibration algorithms address the problem of covariate shift via unsupervised
domain adaptation. However, these methods suffer from the following limitations: 1) they …

The rapid growth of uncharacterized enzymes and their functional diversity urge accurate
and trustworthy computational functional annotation tools. However, current state-of-the-art …

With the rapid development of deep learning, training Big Models (BMs) for multiple
downstream tasks becomes a popular paradigm. Researchers have achieved various …

This commentary draws critical attention to the ongoing commodification of trust in policy
and scholarly discourses of artificial intelligence (AI) and society. Based on an assessment …

Large Language Models (LLMs) have demonstrated remarkable capabilities in performing
complex cognitive tasks. However, their complexity and lack of transparency have raised …

Engendering trust in technically acceptable and psychologically embraceable systems
requires domain-specific research to capture unique characteristics of the field of …

Making responsible lending decisions involves many factors. There is a growing amount of
research on machine learning applied to credit risk evaluation. This promises to enhance …

Synthetic electronic health records (EHR) can facilitate effective use of clinical data in
software development, medical education, and medical research without the concerns of …