Jacob Eisenstein

Introduction to Natural Language Processing is now available from MIT press.

I work on computational linguistics and natural language processing. I have been focused on language variation and change: making NLP robust to it, and using computational techniques to measure and understand it. In July 2019, I joined Google AI as a research scientist. From 2012 to 2019, I was on the faculty at Georgia Tech, where I led the Computational Linguistics lab.

publications | twitter | biographical sketch | github

Research

A complete list of publications can be found on Google scholar, and on Semantic scholar. Here are some recent papers in my current areas of interest.

Trustworthy NLP

Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language. Eisenstein. NAACL 2022.
The MultiBERTS: BERT Reproductions for Robustness Analysis. Sellam, Yadlowsky, Tenney, ... Eisenstein, .... ICLR 2022.
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests. Veitch, D'Amour, Yadlowsky, and Eisenstein. NeurIPS 2021.
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. Feder, ..., Eisenstein, ... 2021 (working paper)
Learning to Recognize Dialect Features. Demszky, Sharma, Clark, Prabhakaran, and Eisenstein. NAACL 2021.
Underspecification Presents Challenges for Credibility in Modern Machine Learning. D'Amour, Heller, Moldovan, ..., Eisenstein, ..., Sculley. arXiv 2020.
Unsupervised domain adaptation of contextualized embeddings for sequence labeling. Han and Eisenstein. EMNLP 2019.

Measuring and modeling language change

Time-Aware Language Models as Temporal Knowledge Bases. Dhingra*, Cole*, Eisenschlos, Gillick, Eisenstein, and Cohen. TACL, 2021.
Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers. Soni, Klein, and Eisenstein. Journal of Cultural Analytics, 2021.
Follow the leader: Documents on the leading edge of semantic change get more citations. Soni, Lerman, and Eisenstein. JASIST 2020.
Measuring and modeling language change. Eisenstein. NAACL 2019 and IC2S2 tutorial.

Representation learning

Sparse, Dense, and Attentional Representations for Text Retrieval. Luan, Eisenstein, Toutanova, and Collins. TACL 2020.
The Referential Reader: A Recurrent Entity Network for Anaphora Resolution. Liu, Zettlemoyer, and Eisenstein. ACL 2019.
Predicting Semantic Relations using Global Graph Properties. Pinter and Eisenstein. EMNLP 2018.

Professional service

Senior area chair: EMNLP 2020, ACL 2019
Area chair: EMNLP 2021, ACL 2021, ACL 2020, NAACL 2018, EMNLP 2017, NAACL 2016, ACL 2014, EACL 2013
Tutorial co-chair: ACL 2018, NAACL 2012
Steering committee: 2021 EMNLP Workshop on Causal Inference & NLP.
Co-chair: 2016 EMNLP Workshop on NLP and Computational Social Science.
Co-chair: 2014 ACL Workshop on Language Technologies and Computational Social Science
Co-chair: 2013-2015 Atlanta Workshop on Computational Social Science
Coordinator/chair/czar of student research workshop, awards, and/or volunteers: NAACL 2016, ICML 2013, NAACL 2013
Program committees: ACL, CONLL, EMNLP, NAACL, ICML, NeurIPS, CSCW, various workshops. All these venues are open-access (OA).
Editorial boards: Action editor at TACL (OA), Linguistic Issues in Language Technology (OA), Language Variation series at Language Science Press (OA), Computational Linguistics (OA)
Journal Reviewing: Proceedings of the National Academy of Science (PNAS), Communications of the ACM, Computational Linguistics (OA), Journal of Machine Learning Research (OA), Journal of Artificial Intelligence Research (OA), Machine Learning Journal, Transactions of the Association of Computational Linguistics (OA), Journal of Sociolinguistics, Journal of the American Statistical Association, Language in Society, Glossa (OA), Proceedings of the National Academy of Science, Digital Scholarship in the Humanities, Nature Human Behavior ...
I prefer that my reviewing effort goes towards papers that everyone can read. So I usually will not review for venues that are non-OA, unless I submit papers there myself.

Georgia Tech

From 2012-2019 I was on the faculty at Georgia Tech, where I taught about Natural Language Processing and advised some great students.

Spring 2018: CS 4650/7650, Natural Language Processing
Fall 2017: CS 8803-CSS, Computational Social Science
Spring 2017: CS 4650/7650, Natural Language Processing
Spring 2016: CS4464/6465, Computational Journalism
Fall 2015: CS 4650/7650, Natural Language Processing
Spring 2015: CS 8803-CSS, Computational Social Science
Fall 2014: CS 4650/7650 Natural Language Processing
Spring 2014: CS 8803, Computational Social Science
Fall 2013: CS 4650/7650, Natural Language Processing
Spring 2013: CS 4650/7650, Natural Language Processing
Spring 2012: CS 4650/7650, Natural Language Processing

PhD advisees

		Jacob Eisenstein Introduction to Natural Language Processing is now available from MIT press. I work on computational linguistics and natural language processing. I have been focused on language variation and change: making NLP robust to it, and using computational techniques to measure and understand it. In July 2019, I joined Google AI as a research scientist. From 2012 to 2019, I was on the faculty at Georgia Tech, where I led the Computational Linguistics lab. publications \| twitter \| biographical sketch \| github
Research A complete list of publications can be found on Google scholar, and on Semantic scholar. Here are some recent papers in my current areas of interest. Trustworthy NLP Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language. Eisenstein. NAACL 2022. The MultiBERTS: BERT Reproductions for Robustness Analysis. Sellam, Yadlowsky, Tenney, ... Eisenstein, .... ICLR 2022. Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests. Veitch, D'Amour, Yadlowsky, and Eisenstein. NeurIPS 2021. Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. Feder, ..., Eisenstein, ... 2021 (working paper) Learning to Recognize Dialect Features. Demszky, Sharma, Clark, Prabhakaran, and Eisenstein. NAACL 2021. Underspecification Presents Challenges for Credibility in Modern Machine Learning. D'Amour, Heller, Moldovan, ..., Eisenstein, ..., Sculley. arXiv 2020. Unsupervised domain adaptation of contextualized embeddings for sequence labeling. Han and Eisenstein. EMNLP 2019. Measuring and modeling language change Time-Aware Language Models as Temporal Knowledge Bases. Dhingra, Cole, Eisenschlos, Gillick, Eisenstein, and Cohen. TACL, 2021. Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers. Soni, Klein, and Eisenstein. Journal of Cultural Analytics, 2021. Follow the leader: Documents on the leading edge of semantic change get more citations. Soni, Lerman, and Eisenstein. JASIST 2020. Measuring and modeling language change. Eisenstein. NAACL 2019 and IC2S2 tutorial. Representation learning Sparse, Dense, and Attentional Representations for Text Retrieval. Luan, Eisenstein, Toutanova, and Collins. TACL 2020. The Referential Reader: A Recurrent Entity Network for Anaphora Resolution. Liu, Zettlemoyer, and Eisenstein. ACL 2019. Predicting Semantic Relations using Global Graph Properties. Pinter and Eisenstein. EMNLP 2018. Professional service Senior area chair: EMNLP 2020, ACL 2019 Area chair: EMNLP 2021, ACL 2021, ACL 2020, NAACL 2018, EMNLP 2017, NAACL 2016, ACL 2014, EACL 2013 Tutorial co-chair: ACL 2018, NAACL 2012 Steering committee: 2021 EMNLP Workshop on Causal Inference & NLP. Co-chair: 2016 EMNLP Workshop on NLP and Computational Social Science. Co-chair: 2014 ACL Workshop on Language Technologies and Computational Social Science Co-chair: 2013-2015 Atlanta Workshop on Computational Social Science Coordinator/chair/czar of student research workshop, awards, and/or volunteers: NAACL 2016, ICML 2013, NAACL 2013 Program committees: ACL, CONLL, EMNLP, NAACL, ICML, NeurIPS, CSCW, various workshops. All these venues are open-access (OA). Editorial boards: Action editor at TACL (OA), Linguistic Issues in Language Technology (OA), Language Variation series at Language Science Press (OA), Computational Linguistics (OA) Journal Reviewing: Proceedings of the National Academy of Science (PNAS), Communications of the ACM, Computational Linguistics (OA), Journal of Machine Learning Research (OA), Journal of Artificial Intelligence Research (OA), Machine Learning Journal, Transactions of the Association of Computational Linguistics (OA), Journal of Sociolinguistics, Journal of the American Statistical Association, Language in Society, Glossa (OA), Proceedings of the National Academy of Science, Digital Scholarship in the Humanities, Nature Human Behavior ... I prefer that my reviewing effort goes towards papers that everyone can read. So I usually will not review for venues that are non-OA, unless I submit papers there myself. Georgia Tech From 2012-2019 I was on the faculty at Georgia Tech, where I taught about Natural Language Processing and advised some great students. Spring 2018: CS 4650/7650, Natural Language Processing Fall 2017: CS 8803-CSS, Computational Social Science Spring 2017: CS 4650/7650, Natural Language Processing Spring 2016: CS4464/6465, Computational Journalism Fall 2015: CS 4650/7650, Natural Language Processing Spring 2015: CS 8803-CSS, Computational Social Science Fall 2014: CS 4650/7650 Natural Language Processing Spring 2014: CS 8803, Computational Social Science Fall 2013: CS 4650/7650, Natural Language Processing Spring 2013: CS 4650/7650, Natural Language Processing Spring 2012: CS 4650/7650, Natural Language Processing PhD advisees Sandeep Soni (Postdoc at UC Berkeley), Yuval Pinter (Ben-Gurion University) Ian Stewart (Postdoc at Michigan), Umashanthi Pavalanathan (Twitter), Yi Yang (Asapp), Yangfeng Ji (University of Virginia)