2020-01-01 · conference-paper · Topic Modeling · en
highly citedfrom the source record
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, Alexander Rush. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2020.
Claims drawn from cited facts, not live model generation.
This work is a conference paper concerned with topic modeling. Because it is a conference paper, it has undergone peer review and therefore carries more weight than a preprint.
4 cited facts
This work is the product of a small team of 3 researchers.
1 cited fact
The work has a citation count of 8694, and its highly cited status indicates it is already an established reference point in its field. It references 39 works.
3 cited facts
Transformers: State-of-the-Art Natural Language Processing is a conference-paper, focusing on Topic Modeling, published in 2020.
Transformers: State-of-the-Art Natural Language Processing has 8,694 citations in our record, placing it among the highly cited works we track.
Our record lists 3 authors for Transformers: State-of-the-Art Natural Language Processing and references 39 other works. Author names aren't in our data yet — the source link on the page lists the full byline.
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