Conventional machine learning studies generally assume close-environment scenarios
where important factors of the learning process hold invariant. With the great success of …

Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of machine
learning systems. For instance, in autonomous driving, we would like the driving system to …

Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

Research in the field of Intrusion Detection is focused on developing an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …

Abstract Emotion Recognition in Conversations (ERC) can capture the speakers' emotional
changes in multiple rounds of conversation, so it has a wide range of applications. In recent …

Abstract Most applications of Artificial Intelligence (AI) are designed for a confined and
specific task. However, there are many scenarios that call for a more general AI, capable of …

Implementing effective control mechanisms to ensure the proper functioning and security of
deployed NLP models, from translation to chatbots, is essential. A key ingredient to ensure …

The microservices architecture (MSA) is a form of distributed systems architecture that has
been widely adopted in large-scale software systems in recent years. As with other …

The generalization capability of machine learning systems degenerates notably when the
test distribution drifts from the training distribution. Recently, Domain Generalization (DG) …

Africa's agriculture has over time, improved and expanded in scale and efficiency, yet its
productivity is far from its optimum, and the majority of the continent is still food insecure. To …