What Are Major NLP Achievements & Papers From 2019?

In 2018 we saw a number of landmark research breakthroughs in the field of natural language processing (NLP). The introduction of transfer learning and pretrained language models in NLP pushed forward the limits of language understanding and generation. These also dominated NLP progress this year. Teams from top research institutions and tech companies explored ways to make state-of-the-art language models even more sophisticated. Many improvements were driven by massive boosts in computing capacities, but many research groups also discovered ingenious ways to lighten models while maintaining high performance. In this article, we summarize 11 research papers covering key language models presented during the year as well as recent research breakthroughs in machine translation, sentiment analysis, dialogue systems, and abstractive summarization.