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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020): Tutorial Abstracts

Authors: Savary, Agata; Zhang, Yue;

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020): Tutorial Abstracts

Abstract

International audience

Country
France
Related Organizations
Keywords

[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]

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Hans-Jo¨rg Ehni. 2008. Dual use and the ethical responsibility of scientists. Archivum immunologiae et therapiae experimentalis, 56(3):147.

Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. 2015. Certifying and removing disparate impact. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 259-268. ACM.

Arpita Ghosh, Tim Roughgarden, and Mukund Sundararajan. 2012. Universally utility-maximizing privacy mechanisms. SIAM Journal on Computing, 41(6):1673-1693.

Dirk Hovy and Shannon L. Spruit. 2016. The social impact of natural language processing. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 591-598. Association for Computational Linguistics.

Ben Hutchinson and Margaret Mitchell. 2019. 50 years of test (un)fairness: Lessons for machine learning. In Proceedings of FAT* 19: Conference on Fairness, Accountability, and Transparency (FAT* 19), volume abs/1811.10104, New York. ACM.

Roger T Johnson and David W Johnson. 2008. Active learning: Cooperation in the classroom. The annual report of educational psychology in Japan, 47:29- 30.

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    popularity
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    influence
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    impulse
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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