[CaCL] Reading for 1/27

[White, Michael]

There is also this more recent CL squib by Belinkov that I was the editor for; this is the early access version:

https://direct.mit.edu/coli/article/doi/10.1162/coli_a_00422/107571/Probing-Classifiers-Promises-Shortcomings-and


From: CaCL <cacl-bounces at lists.osu.edu> on behalf of Cheung, Willy via CaCL <cacl at lists.osu.edu>
Date: Friday, January 21, 2022 at 9:45 AM
To: cacl at lists.osu.edu <cacl at lists.osu.edu>
Subject: [CaCL] Reading for 1/27
Hi CaCLers,

For our next meeting on 1/27, we will be discussing "Analysis Methods in Neural Language Processing: A Survey" by Yonatan Belinkov and James Glass.

Paper link: https://aclanthology.org/Q19-1004.pdf<https://urldefense.com/v3/__https:/aclanthology.org/Q19-1004.pdf__;!!KGKeukY!mcO8hEzbNle0xb13Uf8DVWBdyiclO0XrNt7m6gF3jhrwq7qXorYLDEvdcJuzDikfkg$>
Analysis Methods in Neural Language Processing: A Survey<https://urldefense.com/v3/__https:/aclanthology.org/Q19-1004.pdf__;!!KGKeukY!mcO8hEzbNle0xb13Uf8DVWBdyiclO0XrNt7m6gF3jhrwq7qXorYLDEvdcJuzDikfkg$>
Analysis Methods in Neural Language Processing: A Survey Yonatan Belinkov 1;2 and James Glass 1MIT Computer Science and Artificial Intelligence Laboratory 2Harvard School of Engineering and Applied Sciences Cambridge, MA, USA fbelinkov, glassg at mit.edu Abstract The field of natural language processing has
aclanthology.org
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Zoom link: https://osu.zoom.us/j/95536921111?pwd=TG9YdVZ0Wk45R2hCdHhTYk5ubkhIQT09<https://urldefense.com/v3/__https:/osu.zoom.us/j/95536921111?pwd=TG9YdVZ0Wk45R2hCdHhTYk5ubkhIQT09__;!!KGKeukY!mcO8hEzbNle0xb13Uf8DVWBdyiclO0XrNt7m6gF3jhrwq7qXorYLDEvdcJuq6SFj_Q$>

Abstract: The field of natural language processing has seen impressive progress in recent years, with neural network models replacing many of the traditional systems. A plethora of new models have been proposed, many of which are thought to be opaque compared to their feature rich counterparts. This has led researchers to analyze, interpret, and evaluate neural networks in novel and more fine-grained ways. In this survey paper, we review analysis methods in neural language processing, categorize them according to prominent research trends, highlight existing limitations, and point to potential directions for future work.
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