The field of Natural Language Processing (NLP) has undergone a significant transformation
with the introduction of Transformers. From the first introduction of this technology in 2017 …

The images acquired by a single visible light sensor are very susceptible to light conditions,
weather changes, and other factors, while the images acquired by a single infrared light …

Pre-trained language models such as BERT have proven to be highly effective for natural
language processing (NLP) tasks. However, the high demand for computing resources in …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Humans gather information through conversations involving a series of interconnected
questions and answers. For machines to assist in information gathering, it is therefore …

Conversational search is an emerging topic in the information retrieval community. One of
the major challenges to multi-turn conversational search is to model the conversation history …

Question answering (QA) systems provide a way of querying the information available in
various formats including, but not limited to, unstructured and structured data in natural …

We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and
natural language processing based on Apache MXNet (incubating). These toolkits provide …

Conversational search is one of the ultimate goals of information retrieval. Recent research
approaches conversational search by simplified settings of response ranking and …

In a conversational question answering scenario, a questioner seeks to extract information
about a topic through a series of interdependent questions and answers. As the …