Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. In Findings of the Association for Computational Linguistics: ACL 2022 (pp. 2340–2354). Winata, G.

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The Stanford AI Lab Blog

FEBRUARY 1, 2022

In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5370-5381, Florence, Italy. Association for Computational Linguistics. ↩ Sheryl Brahnam. Interact 2005 work- shop Abuse: The darker side of Human-Computer Interaction , pages 62–67. ↩ John Suler.

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Sebastian Ruder

AUGUST 18, 2019

Later approaches then scaled these representations to sentences and documents ( Le and Mikolov, 2014 ; Conneau et al., LM pretraining   Many successful pretraining approaches are based on variants of language modelling (LM). Early approaches such as word2vec ( Mikolov et al., 2017 ; Peters et al.,

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NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. On the other hand, a new and pretty disruptive mechanism for sequential processing – attention – has been introduced in the sequence-to-sequence (seq2seq) model by Sutskever et al. White (2014).

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