CAiRE Webinar - Moving Away from One-Size-Fits-All Natural Language Processing
The typical approach in natural language processing is to use one-size-fits-all representations, obtained from training one model on very large text collections. While this approach is effective for those people whose language style is well represented in the data, it fails to account for variations between people, and thus may lead to worse performance for those in the minority. In this talk, Prof. Rada Mihalcea will challenge the one-size-fits-all assumption, and show that (1) they can identify words that are used in significantly different ways by speakers from different cultures; and (2) they can effectively use information about the people behind the words to build better natural language processing models.
Prof. Rada Mihalcea is the Janice M. Jenkins Collegiate Professor of Computer Science and Engineering at the University of Michigan and the Director of the Michigan Artificial Intelligence Lab. Her research interests are in computational linguistics, with a focus on lexical semantics, multilingual natural language processing, and computational social sciences. She currently serves as the President of the Association for Computational Linguistics. She is the recipient of a Presidential Early Career Award for Scientists and Engineers awarded by President Obama (2009), an ACM Fellow (2019) and a AAAI Fellow (2021). In 2013, she was made an honorary citizen of her hometown of Cluj-Napoca, Romania.