NLP/ML
ATTN: How Grammarly’s NLP/ML Team Figured Out Where Readers Focus in an Email
ATTN: How Grammarly’s NLP/ML Team Figured Out Where Readers Focus in an EmailThis article was co-written by Machine Learning Engineer Karun Singh and Product Manager Dru Knox. How do you know if the main...September 9, 2021
When Less Is More: Text Simplification by Tagging
When Less Is More: Text Simplification by TaggingThis article was co-written by Grammarly Applied Research Scientists Kostiantyn Omelianchuk, Vipul Raheja, and Oleksandr...June 29, 2021
Announcing UA-GEC: A Grammatical Error Correction Dataset for the Ukrainian Language
Announcing UA-GEC: A Grammatical Error Correction Dataset for the Ukrainian LanguageThe natural language processing (NLP) research community has traditionally focused on the English language, but in just the past...April 5, 2021
How Grammarly’s NLP Team Is Building the Future of Communication
How Grammarly’s NLP Team Is Building the Future of CommunicationThis article was co-written by Yury Markovsky, Engineering Manager; Timo Mertens, Head of ML and NLP Products; and Chad Mills,...February 25, 2021
Adversarial Grammatical Error Correction
Adversarial Grammatical Error CorrectionIn developing the world’s leading writing assistant, Grammarly helps people communicate wherever they write—whether in an...January 26, 2021
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