Machine Learning Meets Natural Language Processing -- The story so far
It provides a historical overview for researchers and practitioners in NLP, but is incremental as it summarizes existing work without new results.
This paper reviews the evolution of Natural Language Processing over the last decade, highlighting key milestones and contributions of models like Transformers and BERT, while identifying remaining unsolved issues.
Natural Language Processing (NLP) has evolved significantly over the last decade. This paper highlights the most important milestones of this period while trying to pinpoint the contribution of each individual model and algorithm to the overall progress. Furthermore, it focuses on issues still remaining to be solved, emphasizing the groundbreaking proposals of Transformers, BERT, and all the similar attention-based models.