Remove 2011 Remove Computational Linguistics Remove NLP
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Testing the Robustness of LSTM-Based Sentiment Analysis Models

John Snow Labs

Sentiment analysis, a branch of natural language processing (NLP), has evolved as an effective method for determining the underlying attitudes, emotions, and views represented in textual information. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). abs/2005.03993 Andrew L.

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The State of Multilingual AI

Sebastian Ruder

At the same time, a wave of NLP startups has started to put this technology to practical use. I will be focusing on topics related to natural language processing (NLP) and African languages as these are the domains I am most familiar with. Bender [2] highlighted the need for language independence in 2011.

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Multi-domain Multilingual Question Answering

Sebastian Ruder

Among current key applications of NLP, QA has the lowest linguistic global utility, i.e. performance averaged across the world's languages ( Blasi et al., Linguistic and demographic utility of different NLP applications ( Blasi et al., 2021 ), which can be seen below. In COPA ( Roemmele et al.,

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Parsing English in 500 Lines of Python

Explosion

A favourite example: They ate the pizza with anchovies A correct parse links “with” to “pizza”, while an incorrect parse links “with” to “eat”: The Natural Language Processing (NLP) community has made big progress in syntactic parsing over the last few years. The Cython system, Redshift, was written for my current research.

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