no code implementations • EMNLP (WNUT) 2020 • Omid Kashefi, Rebecca Hwa
Data augmentation has been shown to be effective in providing more training data for machine learning and resulting in more robust classifiers.
1 code implementation • WNUT (ACL) 2021 • Omid Kashefi, Rebecca Hwa
Certain types of classification problems may be performed at multiple levels of granularity; for example, we might want to know the sentiment polarity of a document or a sentence, or a phrase.
no code implementations • 3 Jun 2022 • Omid Kashefi, Tazin Afrin, Meghan Dale, Christopher Olshefski, Amanda Godley, Diane Litman, Rebecca Hwa
The variety of revision unit scope and purpose granularity levels in ArgRewrite, along with the inclusion of new types of meta-data, can make it a useful resource for research and applications that involve revision analysis.
no code implementations • NAACL 2018 • Omid Kashefi, Andrew T. Lucas, Rebecca Hwa
Pleonasms are words that are redundant.
no code implementations • 10 Jan 2018 • Omid Kashefi
Part-of-Speech (POS) tagging is an old and fundamental task in natural language processing.
1 code implementation • 7 Jan 2018 • Omid Kashefi
One of the most major and essential tasks in natural language processing is machine translation that is now highly dependent upon multilingual parallel corpora.