J
Jacob Eisenstein
Researcher at Google
Publications - 201
Citations - 11502
Jacob Eisenstein is an academic researcher from Google. The author has contributed to research in topics: Gesture & Language model. The author has an hindex of 50, co-authored 196 publications receiving 9772 citations. Previous affiliations of Jacob Eisenstein include Georgia Institute of Technology & University of Illinois at Urbana–Champaign.
Papers
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Proceedings ArticleDOI
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments
Kevin Gimpel,Nathan Schneider,Brendan O'Connor,Dipanjan Das,Daniel Mills,Jacob Eisenstein,Michael Heilman,Dani Yogatama,Jeffrey Flanigan,Noah A. Smith +9 more
TL;DR: A tagset is developed, data is annotated, features are developed, and results nearing 90% accuracy are reported on the problem of part-of-speech tagging for English data from the popular micro-blogging service Twitter.
Proceedings Article
A Latent Variable Model for Geographic Lexical Variation
TL;DR: A multi-level generative model that reasons jointly about latent topics and geographical regions is presented, which recovers coherent topics and their regional variants, while identifying geographic areas of linguistic consistency.
Proceedings Article
What to do about bad language on the internet
TL;DR: A critical review of the NLP community's response to the landscape of bad language is offered, and a quantitative analysis of the lexical diversity of social media text, and its relationship to other corpora is presented.
Posted Content
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour,Katherine Heller,Dan Moldovan,Ben Adlam,Babak Alipanahi,Alex Beutel,Christina Chen,Jonathan Deaton,Jacob Eisenstein,Matthew D. Hoffman,Farhad Hormozdiari,Neil Houlsby,Shaobo Hou,Ghassen Jerfel,Alan Karthikesalingam,Mario Lucic,Yi-An Ma,Cory Y. McLean,Diana Mincu,Akinori Mitani,Andrea Montanari,Zachary Nado,Vivek T. Natarajan,Christopher Nielson,Thomas F. Osborne,Rajiv Raman,Kim Ramasamy,Rory Sayres,Jessica Schrouff,Martin G. Seneviratne,Shannon Sequeira,Harini Suresh,Victor Veitch,Max Vladymyrov,Xuezhi Wang,Kellie Webster,Steve Yadlowsky,Taedong Yun,Xiaohua Zhai,D. Sculley +39 more
TL;DR: This work shows the need to explicitly account for underspecification in modeling pipelines that are intended for real-world deployment in any domain, and shows that this problem appears in a wide variety of practical ML pipelines.
Proceedings Article
Sparse Additive Generative Models of Text
TL;DR: This approach has two key advantages: it can enforce sparsity to prevent overfitting, and it can combine generative facets through simple addition in log space, avoiding the need for latent switching variables.