The Natural Language Decathlon (decaNLP) is a new benchmark for studying general NLP models that can perform a variety of complex, natural language tasks.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
This is a list of 100 important natural language processing (NLP) papers that serious students and researchers working in the field should probably know about and read.
In natural language understanding, there is a hierarchy of lenses through which we can extract meaning - from words to sentences to paragraphs to documents. At the document level, one of the most useful ways to understand text is by analyzing its topics.
I made an introductory talk on word embeddings in the past and this write-up is an extended version of the part about philosophical ideas behind word vectors.
S. Bordia, and S. Bowman. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, page 7--15. Minneapolis, Minnesota, Association for Computational Linguistics, (June 2019)
S. Blodgett, S. Barocas, H. Daumé III, and H. Wallach. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, page 5454--5476. Online, Association for Computational Linguistics, (July 2020)