Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau. 2020. Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. Journal of Machine Learning Research 21(248):1-43, 2020.

Alex Tamkin, Dan Jurafsky, and Noah Goodman. 2020. Language Through a Prism: A Spectral Approach for Multiscale Language Representations. NeurIPS 2020.

Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald and Dan Jurafsky. 2020. With Little Power Comes Great Responsibility. EMNLP 2020. [pdf] [supplementary] [bib]

Kawin Ethayarajh and Dan Jurafsky. 2020. Utility is in the Eye of the User: A Critique of NLP Leaderboards. EMNLP 2020. [pdf] [bib]

Yiwei Luo, Dallas Card, and Dan Jurafsky. 2020. Detecting Stance in Media On Global Warming. Findings of the ACL: EMNLP 2020. [pdf] [bib]

Isabel Papadimitriou and Dan Jurafsky. 2020. Learning Music Helps You Read: Using transfer to study linguistic structure in language models EMNLP 2020 [pdf] [bib]

Heidi Chen, Emma Pierson, Sonja Schmer-Galunder, Jonathan Altamirano, Dan Jurafsky, Jure Leskovec, Magali Fassiotto, and Nishita Kothary. 2020. Gender differences in patient perceptions of physicians' communal traits and the impact on physician evaluations. Journal of Women's Health, 2020.

Turnwald, B.P., Anderson, K.G., Jurafsky, D., and Crum, A.J. (2020). Five-star prices, appealing healthy item descriptions? Expensive restaurants' descriptive menu language. Health Psychology. [pdf]

Li Lucy, Dora Demszky, Patricia Bromley, Dan Jurafsky. 2020. Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks. AERA Open 2020. 2020 Education Data Science Conference Best Paper Award. [pdf]

Julia Mendelsohn, Yulia Tsvetkov and Dan Jurafsky. 2020. A framework for the computational linguistic analysis of dehumanization. Frontiers in Artificial Intelligence. [pdf].

Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky. 2020. Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. ACL 2020.

Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith and Yejin Choi. 2020. Social Bias Frames: Reasoning about Social and Power Implications of Language. ACL (2020)

Adam S. Miner, Albert Haque, Jason A. Fries, Scott L. Fleming, Denise E. Wilfley, G. Terence Wilson, Arnold Milstein, Dan Jurafsky, Bruce A. Arnow, W. Stewart Agras, Li Fei-Fei, and Nigam H. Shah. 2020. Assessing the accuracy of automatic speech recognition for psychotherapy. npj Digital Medicine 3, 82 (2020).

Bas Hofstra, Vivek V. Kulkarni, Sebastian Munoz-Najar Galvez, Bryan He, Dan Jurafsky, and Daniel A. McFarland. 2020. The Diversity-Innovation Paradox in Science. Proceedings of the National Academy of Sciences. [pdf]

Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John Rickford, Dan Jurafsky, and Sharad Goel. 2020. Racial Disparities in Automated Speech Recognition. Proceedings of the National Academy of Sciences 117 (14) 7684-7689. [pdf] [Press: NY Times]

Michael Hahn, Dan Jurafsky, and Richard Futrell. 2020. Universals of word order reflect optimization of grammars for efficient communication. Proceedings of the National Academy of Sciences 117 (5) 2347-2353. [pdf] [bib] [code]

Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer and Mike Lewis. 2020. Generalization through Memorization: Nearest Neighbor Language Models. International Conference on Learning Representations (ICLR), 2020. [pdf] [code]

Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang. 2020. Automatically Neutralizing Subjective Bias in Text. AAAI, 2020 [pdf] [code]