Attention has arguably become one of the most important concepts in the deep learning
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …

Humans' ability to transfer knowledge through teaching is one of the essential aspects for
human intelligence. A human teacher can track the knowledge of students to customize the …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Few-Shot Learning refers to the problem of learning the underlying pattern in the data just
from a few training samples. Requiring a large number of data samples, many deep learning …

This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …

Boosting performance of the offline trained siamese trackers is getting harder nowadays
since the fixed information of the template cropped from the first frame has been almost …

Abstract Language model pre-training has been shown to capture a surprising amount of
world knowledge, crucial for NLP tasks such as question answering. However, this …

We address the problem of anomaly detection, that is, detecting anomalous events in a
video sequence. Anomaly detection methods based on convolutional neural networks …