Jack Hessel's Academic Page
Jack Hessel
Postdoctoral Young Investigator @ AI2
contact: jackh@allenai.org
CV (as of 10/2020).
I am on github, twitter, google scholar, and semantic scholar. I work on natural language processing, machine learning, social interactions, and computer vision. As of October 2020, I am a postdoctoral Young Investigator with Yejin Choi at AI2. Previously, I earned a PhD in Computer Science at Cornell University, where I was advised by Lillian Lee.
If you're looking for me, I look something like this (facial hair subject to change):
Publications (in reverse chronological order)
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Does my multimodal model learn cross-modal interactions? It’s harder to tell than you might think!
Jack Hessel and Lillian Lee
EMNLP 2020
code, talk
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Beyond Instructional Videos: Probing for More Diverse Visual-Textual Grounding on YouTube
Jack Hessel, Zhenhai Zhu, Bo Pang, and Radu Soricut
EMNLP 2020
data, talk
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Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents
Gregory Yauney, Jack Hessel, and David Mimno
EMNLP 2020
code
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Learning from Multimodal Web Data
PhD Thesis
Cornell University 2020
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Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents
Jack Hessel, Lillian Lee, and David Mimno
EMNLP 2019
code/data, poster,
project page
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A Case Study on Combining ASR and Visual Features for Generating Instructional Video Captions
Jack Hessel, Bo Pang, Zhenhai Zhu, and Radu Soricut
CoNLL 2019
talk slides
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Something's Brewing! Early Prediction of Controversy-causing Posts from Discussion Features
Jack Hessel and Lillian Lee
NAACL 2019
data
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Quantifying the Visual Concreteness of Words and Topics in Multimodal Datasets
Jack Hessel, David Mimno, and Lillian Lee
NAACL 2018
code/data
- Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity
Jack Hessel, Lillian Lee, David Mimno
WWW 2017
code/data,
slides,
replication
- Aligning Images and Text in a Digital Library
Jack Hessel and David Mimno
Computer Vision in Digital Humanities Workshop at DH 2017 (extended abstract)
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Science, AskScience and BadScience: On the Coexistience of Highly Related Communities
Jack Hessel, Chenhao Tan, and Lillian Lee
ICWSM 2016
data,
slides,
replication
- What do Vegans do in their Spare Time? Latent Interest Detection in Multi-Community Networks
Jack Hessel, Alexandra Schofield, Lillian Lee, David Mimno
Workshop on Networks in the Social and Information Sciences at NeurIPS 2015
project page
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Image Representations and New Domains in Neural Image Captioning
Jack Hessel, Nicolas Savva, and Kimberly J. Wilber
Workshop on Vision and Language at EMNLP 2015
slides
- Using Reproductive Altruism to Evolve Multicellularity in Digital Organisms
Jack Hessel and Sherri Goings
ECAL 2013
Industry Experience
Things I've Taught
- I was a visiting faculty member at Carleton College in Spring, 2019; I taught two classes: Natural Language Processing and Discrete Math.
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INFO/CS 4300 Language and Information, Cornell University, SP 2016
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CS4786 Machine Learning for Data Science, Cornell University, SP 2015 for which I received an outstanding TA award!
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CS4620 Introduction to Computer Graphics, Cornell University, FA 2014
- Introduction to Computer Science/Graph Theory, Carleton College, FA 2011
Invited Talks
Service/Guest Lectures/Other Activites
- Program Committees: ACL 2016, 2017, 2018*, 2019, 2020*; NAACL 2018, 2019*; EMNLP 2017, 2018*, 2019*; EACL 2017; AAAI 2017; ICWSM 2018; CoNLL 2019*; ICML 2020*. For the starred conferences, I was acknowledged as a top reviewer!
- Workshop Program Committees: Black in AI @ NeurIPS 2017, 2018, 2019; Student Research Workshop @ NAACL 2018 ; Workshop on Noisy User-generated Text (W-NUT) @ EMNLP 2018, 2019.
- Two guest lectures (and one "magic" trick) for Spring 2016/2017 CS4300 about my favorite machine learning algorithm: the truncated SVD!
- Spoke at Carleton College's Networks Reading Group where I discussed the role of altruism on Kickstarter.
- Spring Cornell CS4740 Guest Lecture on Topic Models with Xanda Schofield
- Helped with Cornell's annual Expand Your Horizons conference, where some friends and I taught a class on programming (2015, 2016)
Other Projects
- I wrote a TreeLSTM in tensorflow 2; this is a neural network whose topology changes based on each input example.
- I wrote a factorization machine layer in pytorch; for speed reasons, the forward and backward passes are written in cython.
- I implemented Monroe et al.'s "Fightin' Words" algorithm for robustly comparing word frequencies in two corpora. This implementation has been used in several publications, e.g., this and this
- As part of an NSF REU,
I contributed to the implementation of a really (really) fast SVM solver in Kilian Weinberger's lab at Washington University, St. Louis. [now at Cornell!] see Parallel Support Vector Machines in Practice by Tyree, S., Gardner, J. R., Weinberger, K. Q., Agrawal, K., & Tran, J. (2014).
- "A Comparative Analysis of Popular Phylogenetic Reconstruction Algorithms." Undergraduate thesis project/best paper award at MICS 2014: joint work with Evan Albright, Nao Hiranuma, Cody Wang, and Sherri Goings.
More
I grew up in beautiful Portola Valley, California. I earned a B.A. from Carleton College in 2014, studying computer science and mathematics/statistics. During my time in Northfield, I played ice hockey, hosted a radio show, and was lucky enough to meet and work with a lot of great people. I even returned to Carleton briefly in 2019, this time, as a visiting faculty member! I'm a die hard San Jose Sharks fan, avid consumer (and very occasionally a producer) of electronic music, and, most of the time, a vegetarian (I am no longer a vegan!). During graduate school at Cornell, I was a member of Stewart Little Coop, a cooperative living community of 15 people, I played ice hockey in the Ithaca Hockey Association (and, during summer internships in CA, in the San Jose Adult Hockey League).