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Social Bias Frames: Reasoning about Social and Power Implications of Language
- Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, Yejin Choi
- Computer ScienceACL
- 10 November 2019
It is found that while state-of-the-art neural models are effective at high-level categorization of whether a given statement projects unwanted social bias, they are not effective at spelling out more detailed explanations in terms of Social Bias Frames.
The Multilingual Amazon Reviews Corpus
The use of mean absolute error (MAE) instead of classification accuracy for this task, since MAE accounts for the ordinal nature of the ratings, is proposed.
Citation Text Generation
- Kelvin Luu, Rik Koncel-Kedziorski, Kyle Lo, Isabel Cachola, Noah A. Smith
- Computer ScienceArXiv
- 2 February 2020
This paper establishes the task of citation text generation with a standard evaluation corpus and develops several strong baseline models for this task, and provides extensive automatic and human evaluations to illustrate the successes and shortcomings of current text generation techniques.
Computational Text Analysis for Social Science: Model Assumptions and Complexity
The spectrum of current methods, which lie on two dimensions: computational and statistical model complexity; and domain assumptions, are surveyed to suggest directions of research to better align new methods with the goals of social scientists.
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Proceedings of the 5th ACL Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, LaTeCH@ACL 2011, 24 June, 2011, Portland, Oregon, USA
Etch-a-Sketching: Evaluating the Post-Primary Rhetorical Moderation Hypothesis
- Brice D. L. Acree, J. Gross, Noah A. Smith, Yanchuan Sim, Amber E. Boydstun
- Political ScienceAmerican Politics Research
- 1 October 2018
Candidates have incentives to present themselves as strong partisans in primary elections, and then move “toward the center” upon advancing to the general election. Yet, candidates also face…
Contextual word representations
- Noah A. Smith
- Computer ScienceCommun. ACM
- 21 May 2020
Advances in how programs treat natural language words have a big impact in AI, and this research highlights the need to understand these words in more detail.
Choose Your Own Adventure: Paired Suggestions in Collaborative Writing for Evaluating Story Generation Models
This work presents Choose Your Own Adventure, a collaborative writing setup for pairwise model evaluation, where two models generate suggestions to people as they write a short story; writers are asked to choose one of the two suggestions, and they observe which model’s suggestions they prefer.
On Consequentialism and Fairness
This paper provides a consequentialist critique of common definitions of fairness within machine learning, as well as a machine learning perspective on consequentialism, which brings to the fore some of the tradeoffs involved.