New Trends in NLP Research

Natural language processing (NLP) is a field that uses text data and runs computations to gain insights and build predictive systems. Vast amounts of text data are available in written manuscripts and more so online on the web. These data sources have been used in the research community and industries to solve meaningful problems such as predicting the sentiment in a user comment, question answering, and fact-checking. Recent machine learning algorithms have enabled superhuman performance in a wide range of NLP tasks[1]. In this article, we summarize the recent machine learning research trends in NLP which have not only led to a plethora of breakthroughs but also resulted in a growing interest in this field of research. A big chunk of the breakthroughs can be attributed to the large language models that are built using neurons and trained using backpropagation.