Robin Jia

Publications

The statistical advantage of automatic NLG metrics at the system level.
Johnny Tian-Zheng Wei and Robin Jia.
Association for Computational Linguistics (ACL), 2021.
(github)

Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?
Pedro Rodriguez, Joe Barrow, Alexander Hoyle, John P. Lalor, Robin Jia, and Jordan Boyd-Graber.
Association for Computational Linguistics (ACL), 2021.
(website)

Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA.
Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, and Srinivasan Iyer.
Findings of ACL, 2021.

Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality.
Mina Lee*, Chris Donahue*, Robin Jia, Alexander Iyabor, and Percy Liang.
North American Association for Computational Linguistics (NAACL), 2021.
(github) (codalab)

Dynabench: Rethinking Benchmarking in NLP
Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, and Adina Williams.
North American Association for Computational Linguistics (NAACL), 2021.
(website)

N-ary relation prediction over text spans.
Hoifung Poon, Cliff Wong, and Robin Jia.
US Patent, 2021.

On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks.
Stephen Mussmann*, Robin Jia*, and Percy Liang.
Findings of EMNLP, 2020.
(bib) (codalab) (github)

With Little Power Comes Great Responsibility.
Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, and Dan Jurafsky.
Empirical Methods in Natural Language Processing (EMNLP), 2020.
(bib) (github)

Building Robust Natural Language Processing Systems.
Robin Jia.
Ph.D. Dissertation, 2020.

Selective Question Answering under Domain Shift.
Amita Kamath, Robin Jia, and Percy Liang.
Association for Computational Linguistics (ACL), 2020.
(bib) (codalab)

Robust Encodings: A Framework for Combating Adversarial Typos.
Erik Jones, Robin Jia*, Aditi Raghunathan*, and Percy Liang.
Association for Computational Linguistics (ACL), 2020.
(bib) (codalab) (github)

Certified Robustness to Adversarial Word Substitutions.
Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang.
Empirical Methods in Natural Language Processing (EMNLP), 2019.
(bib) (codalab) (github)

Document-Level N-ary Relation Extraction with Multiscale Representation Learning.
Robin Jia, Cliff Wong, and Hoifung Poon.
North American Association for Computational Linguistics (NAACL), 2019.
(bib) (code and data)

Know What You Don’t Know: Unanswerable Questions for SQuAD.
Pranav Rajpurkar*, Robin Jia*, and Percy Liang.
Best Short Paper Award.
Association for Computational Linguistics (ACL), 2018.
(bib) (website) (codalab) (pptx slides) (pdf slides)

Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer.
Juncen Li, Robin Jia, He He, and Percy Liang.
North American Association for Computational Linguistics (NAACL), 2018.
(bib) (codalab) (pptx slides) (pdf slides)

Adversarial Examples for Evaluating Reading Comprehension Systems.
Robin Jia and Percy Liang.
Empirical Methods in Natural Language Processing (EMNLP), 2017.
Outstanding Paper Award.
(bib) (codalab) (pptx slides) (pdf slides)

Learning Concepts through Conversations in Spoken Dialogue Systems.
Robin Jia, Larry Heck, Dilek Hakkani-Tür, and Georgi Nikolov.
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2017.
(bib) (data)

Data Recombination for Neural Semantic Parsing.
Robin Jia and Percy Liang.
Association for Computational Linguistics (ACL), 2016.
(bib) (codalab) (pptx slides) (pdf slides)

“Reverse genomics” predicts function of human conserved noncoding elements.
Amir Marcovitz, Robin Jia, and Gill Bejerano.
Molecular Biology and Evolution, 2016.

Mx1 and Mx2 key antiviral proteins are surprisingly lost in toothed whales.
Benjamin A. Braun, Amir Marcovitz, J. Gray Camp, Robin Jia, and Gill Bejerano.
Proceedings of the National Academy of Sciences (PNAS), 2015.

* denotes equal contribution

Preprints

Question Answering Infused Pre-training of General-Purpose Contextualized Representations.
Robin Jia, Mike Lewis, and Luke Zettlemoyer.
arXiv, 2021.

Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking.
Zhiyi Ma*, Kawin Ethayarajh*, Tristan Thrush*, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, and Douwe Kiela.
arXiv, 2021.

Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation.
Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, and Douwe Kiela.
arXiv, 2021.

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little.
Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, and Douwe Kiela.
arXiv, 2021.

Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches
Nelson F. Liu, Tony Lee, Robin Jia, and Percy Liang.
arXiv, 2021.

To what extent do human explanations of model behavior align with actual model behavior?
Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, and Adina Williams.
arXiv, 2020.

Teaching

• In the Summer of 2019, I was the head instructor for CS221, Stanford’s introductory artificial intelligence class, which had over 100 enrolled students.
• In the Winter of 2018, I was a TA for CS124, Stanford’s undergraduate natural language processing class, taught by Dan Jurafsky.
• In the Autumn of 2015, I was the head TA for CS221, Stanford’s introductory artificial intelligence class, taught by Percy Liang. I led a team of 18 TAs for a class with 550 enrolled students.
• I was a section leader for Stanford’s CS106A (Introduction to Programming) class in the Winter of 2012. I led weekly 50-minute sections, assisted students, graded assignments, and helped maintain some of our internal grading scirpts.
• In 2011 and 2012, I was a Math 50’s Series Tutor, as part of the Stanford University Math Organization (SUMO) tutoring program. I also ran the tutoring program during the 2011-2012 school year.

Professional Service

• Co-organizer of the Third Workshop on Machine Reading and Question Answering (MRQA) to be held at EMNLP 2021.
• Co-organizer of the Second Workshop on Machine Reading and Question Answering (MRQA) at EMNLP 2019.
• Co-organizer of the First Workshop on Machine Reading and Question Answering (MRQA) at ACL 2018.
• Area chair for NAACL (2021), ACL (2021), EMNLP (2021), and AKBC (2021).
• Reviewer for ACL (2018, 2019, 2020), EMNLP (2018, 2019, 2020), NAACL (2019), ACL Rolling Review (2021), AACL (2020), ICML (2019), CoNLL (2018), AKBC (2019), Repl4NLP Workshop (2021), RobustML Workshop (2021), EMNLP DeepLo Workshop (2019), and NAACL GenDeep Workshop (2018). Outstanding Reviewer for EMNLP 2020.

Other Work

Industry Internships

• In 2018, I was an intern with Hoifung Poon at Microsoft Research Redmond, working on biomedical machine reading for precision medicine.
• In 2016, I worked with Larry Heck, Georgi Nikolov, and Dilek Hakkani-Tür on the Deep Dialogue team at Google Research, exploring how to build task-based dialogue systems that can learn from personalized user feedback.
• In 2014, I worked on the Crisis Response Team within the Social Impact arm of Google, where I built infrasturcutre to automatically launch informational pages about hurricanes and tropical storms for people in affected areas.
• In 2012, I worked on the YouTube Ads team on a machine learning project to understand user behavior on the YouTube search page.

Undergraduate Research

• Forward Genomics for Conserved Noncoding Elements with Gray Camp, Amir Marcovitz, and Gill Bejerano.
  Starting in October of 2012, I worked on computational genomics research with Professor Gill Bejerano. I developed a computational pipeline to predict function of conserved noncoding elements by using their evolutionary histories to match them with known traits. I completed my undergraduate honors thesis with Professor Bejerano as my advisor. (poster)

• Automated Gating of Flow Cytometry Data with Robert Bruggner, Rachel Finck, Noah Zimmerman, and David Dill.
  Starting in June of 2011, I worked with Professor David Dill’s group on automated clustering (“gating”) of high-dimensional flow cytometry data. Our work was presented at the Flowcap-II summit. (presentation, poster)

Music

I have had the great pleasure of studying piano performance with Angela Wright and Laura Dahl. At various points, I have also studied solo piano with George Barth, duo piano with Kumaran Arul, and chamber music with Stephen Harrison.

Here are some of my recordings:

Piano duo concert, June 2017

Lisa Wang and I gave a piano duo concert on June 4, 2017.

• Mozart: Sonata for Two Pianos in D Major, K. 448 (video)
• Shostakovich: Concertino for Two Pianos in A Minor, Op. 94 (video)
• Schubert: Allegro in A minor “Lebensstürme,” D.947 (video)
• Brahms: Variations on a Theme by Haydn,* Op. 56a (video)

* Probably not actually by Haydn

Piano Quintet Recital, May 2016

Ricky Wedeen, Brad Girardeau, Lee Fan, Andrew Guo, and I gave a concert on May 18, 2016, at which we performed the Schumann Piano Quintet, Op. 44 (mp3).

Senior Recital, April 2014

I gave my undergraduate senior recital on April 12, 2014. Here are the live audio recordings.

• Mozart: Sonata in B-Flat, K 281 (m4a for Mov. 1, Mov. 2, Mov. 3)
• Chopin: Ballade No. 1 in G Minor (m4a)
• Debussy: L’Isle Joyeuse (m4a)
• Liszt: Sonata in B Minor (m4a)

Other

• Stanford Math Tournament. As an undergraduate at Stanford, I helped organize the Stanford Math Tournament, a high school math tournament created and run by Stanford students.