Creating learning models that can exhibit sophisticated reasoning abilities is one of the
greatest challenges in deep learning research, and mathematics is rapidly becoming one of …

Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient
services such as counseling and suggestive care. They are not used for patient diagnostic …

AI systems have seen significant adoption in various domains. At the same time, further
adoption in some domains is hindered by the inability to fully trust an AI system that it will not …

Large language models (LLMs) have shown increasing in-context learning capabilities
through scaling up model and data size. Despite this progress, LLMs are still unable to solve …

Visual understanding involves detecting objects in a scene and investigating rich semantic
relationships between the objects, which is required for downstream visual reasoning tasks …

Neural-symbolic computing (NeSy), which pursues the integration of the symbolic and
statistical paradigms of cognition, has been an active research area of Artificial Intelligence …

Pre-trained language models (PLMs) demonstrate excellent abilities to understand texts in
the generic domain while struggling in a specific domain. Although continued pre-training on …

Deep learning has revolutionized the artificial intelligence (AI) landscape by enhancing
machine capabilities to understand data-dependant relationships. On the other hand …

We solve object localisation in partial scenes, a new problem of estimating the unknown
position of an object (eg where is the bag?) given a partial 3D scan of a scene. The …

As agile manufacturing expands and workforce mobility increases, the importance of
efficient knowledge transfer among factory workers grows. Cognitive Assistants (CAs) with …