University of Pennsylvania
University of Washington
Kristina ToutanovaResearch Scientist · Google DeepMindResearcher↗
Researcher
Kenton Lee
Google DeepMindResearch Scientist
Lee co-created BERT, helping language models understand words in context.[1] He developed neural systems that track when different names or pronouns refer to the same person or thing[2], and co-created REALM, which retrieves documents to help answer questions rather than relying only on memorized information.[3]
Career & education
Current roleGoogle DeepMind2023-presentResearch Scientist
Google DeepMind2023-presentPreviously
Google2017-2023Research Scientist
Google2017-2023Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations219,703As of Nov 1, '26
citations+4,281Since last snapshot, Oct 1, '26
Selected contributions
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT learns word meaning from the text on both sides.
References
- BERT: Pre-training of Deep Bidirectional Transformersarxiv.org
BERT: Pre-training of Deep Bidirectional Transformers supports the anchored contribution. Named-contribution check: personal publications and original BERT, coreference and REALM papers read. Preserves all three contributions, names REALM and explains BERT impact. Semantic parsing, entity linking and data augmentation also considered; omitted for focused bio. Personal publication list is historical; not used to infer a new current role. No supplied CV.
- End-to-end Neural Coreference Resolutionaclanthology.org
End-to-end Neural Coreference Resolution supports the anchored contribution. Named-contribution check: personal publications and original BERT, coreference and REALM papers read. Preserves all three contributions, names REALM and explains BERT impact. Semantic parsing, entity linking and data augmentation also considered; omitted for focused bio. Personal publication list is historical; not used to infer a new current role. No supplied CV.
- REALM: Retrieval-Augmented Language Model Pre-Trainingarxiv.org
REALM: Retrieval-Augmented Language Model Pre-Training supports the anchored contribution. Named-contribution check: personal publications and original BERT, coreference and REALM papers read. Preserves all three contributions, names REALM and explains BERT impact. Semantic parsing, entity linking and data augmentation also considered; omitted for focused bio. Personal publication list is historical; not used to infer a new current role. No supplied CV.
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Reviewed August 7, 2026 · Checked for accuracy and new information.
