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ORCIDBrandon M. Stewart
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2020 – today
- 2024
[c10]Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon M. Stewart, Jonathan K. Kummerfeld, Denis Peskoff, Jordan L. Boyd-Graber:
More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. ACL (1) 2024: 12423-12441- [c9]Till Saenger, Musashi Hinck, Justin Grimmer, Brandon M. Stewart:
AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments. EMNLP 2024: 16325-16342 - [i9]Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon M. Stewart, Jonathan K. Kummerfeld, Denis Peskoff, Jordan Lee Boyd-Graber:
More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. CoRR abs/2406.04643 (2024) - [i8]Denis Peskoff, Adam Visokay, Sander Schulhoff, Benjamin Wachspress, Alan Blinder, Brandon M. Stewart:
GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves. CoRR abs/2407.19110 (2024) - [i7]Till Saenger, Musashi Hinck, Justin Grimmer, Brandon M. Stewart:
AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments. CoRR abs/2410.08917 (2024) - 2023
- [j5]Arunesh Mathur
, Angelina Wang, Carsten Schwemmer, Maia Hamin, Brandon M. Stewart, Arvind Narayanan:
Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle. Big Data Soc. 10(1): 205395172211453 (2023) - [j4]Justin Grimmer, Dean Knox, Brandon M. Stewart:
Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding. J. Mach. Learn. Res. 24: 182:1-182:70 (2023) - [c8]Denis Peskoff, Brandon M. Stewart:
Credible without Credit: Domain Experts Assess Generative Language Models. ACL (2) 2023: 427-438 - [c7]Denis Peskoff, Adam Visokay, Sander Schulhoff, Benjamin Wachspress, Alan Blinder, Brandon M. Stewart:
GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves. EMNLP (Findings) 2023: 6529-6539 - [c6]Naoki Egami, Musashi Hinck, Brandon M. Stewart, Hanying Wei:
Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models. NeurIPS 2023 - [i6]Naoki Egami, Musashi Jacobs-Harukawa, Brandon M. Stewart, Hanying Wei:
Using Large Language Model Annotations for Valid Downstream Statistical Inference in Social Science: Design-Based Semi-Supervised Learning. CoRR abs/2306.04746 (2023) - [i5]Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - 2022
- [j3]Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang:
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. Trans. Assoc. Comput. Linguistics 10: 1138-1158 (2022) - 2021
- [i4]Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang:
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. CoRR abs/2109.00725 (2021) - 2020
- [i3]Justin Grimmer, Dean Knox, Brandon M. Stewart:
Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding. CoRR abs/2007.12702 (2020)
2010 – 2019
- 2018
- [j2]Michael Yeomans, Brandon M. Stewart, Kimia Mavon, Alexander Kindel, Dustin Tingley, Justin Reich:
The Civic Mission of MOOCs: Engagement across Political Differences in Online Forums. Int. J. Artif. Intell. Educ. 28(4): 553-589 (2018) - [c5]Allison June-Barlow Chaney, Brandon M. Stewart, Barbara E. Engelhardt:
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. RecSys 2018: 224-232 - [i2]Naoki Egami, Christian J. Fong, Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart:
How to Make Causal Inferences Using Texts. CoRR abs/1802.02163 (2018) - 2017
- [c4]Alexander Kindel, Michael Yeomans, Justin Reich, Brandon M. Stewart, Dustin Tingley:
Discourse: MOOC Discussion Forum Analysis at Scale. L@S 2017: 141-142 - [i1]Allison June-Barlow Chaney, Brandon M. Stewart, Barbara E. Engelhardt:
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility. CoRR abs/1710.11214 (2017) - 2016
- [c3]Justin Reich, Brandon M. Stewart, Kimia Mavon, Dustin Tingley:
The Civic Mission of MOOCs: Measuring Engagement across Political Differences in Forums. L@S 2016: 1-10 - [p1]Margaret E. Roberts, Brandon M. Stewart, Dustin Tingley:
Navigating the Local Modes of Big Data: The Case of Topic Models. Computational Social Science 2016: 51-97 - 2015
- [c2]Jason Chuang, Margaret E. Roberts, Brandon M. Stewart, Rebecca Weiss, Dustin Tingley, Justin Grimmer, Jeffrey Heer:
TopicCheck: Interactive Alignment for Assessing Topic Model Stability. HLT-NAACL 2015: 175-184 - 2014
- [j1]Justin Reich, Dustin Tingley, Jetson Leder-Luis, Margaret E. Roberts, Brandon M. Stewart:
Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses. J. Learn. Anal. 2(1) (2014) - 2013
- [c1]Brendan O'Connor, Brandon M. Stewart, Noah A. Smith:
Learning to Extract International Relations from Political Context. ACL (1) 2013: 1094-1104
Coauthor Index
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