Abigail See
Research Scientist at Google DeepMind; first author of the pointer-generator summarization paper
- Research Scientist, Google DeepMind15
Abigail See is a Research Scientist at Google DeepMind, a role See's Stanford page lists since January 2022. See completed a PhD in computer science at Stanford in 2021, advised by Christopher Manning in the Natural Language Processing group, with research on neural text generation for open-ended tasks such as story generation and chitchat dialogue. See is first author of Get To The Point: Summarization with Pointer-Generator Networks and released its code under the Apache License 2.0. At Stanford, See was co-instructor and Head TA of CS224n, Natural Language Processing with Deep Learning, in 2018 and 2019, and led a redesign of its assignments.1234
Work
Pointer-generator networks for summarization (external site: github.com)Open-source code
First author, with Peter J. Liu and Christopher D. Manning, of the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Networks; the accompanying repository holds the code for the paper under the Apache License 2.0, with modifications copyrighted to See.234
Other documented roles
Roles the sources document but that are not confirmed as current.
- PhD student in the Stanford NLP Group (graduated 2021); CS224n co-instructor and Head TA (2018–2019), Stanford University1
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