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Peer Review Has Improved My Papers

Ehud Reiter

BLEU survey: better presentation of results Another example is my 2018 paper which presented a structured survey of the validity of BLEU; this was published in Computational Linguistics journal. In short, by insisting that we do a proper evaluation, the reviewers massively improved our paper.

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The Seven Trends in Machine Translation for 2019

NLP People

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP). According to what was discussed at WMT 2018 that might not be the case — at least not anytime soon.

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A Gentle Introduction to GPTs

Mlearning.ai

It combines techniques from computational linguistics, probabilistic modeling, deep learning to make computers intelligent enough to grasp the context and the intent of the language. GPT-3 is a successor to the earlier GPT-2 (released in Feb 2019) and GPT-1 (released in June 2018) models .

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The three levels of NLP for your business

NLP People

According to Gartner’s hype cycle, NLP has reached the peak of inflated expectations in 2018, and many businesses see it as a “go-to” solution to generate value from the 80% of business-relevant data that comes in unstructured form. The folks here often split into two camps — the mathematicians and the linguists.

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The State of Transfer Learning in NLP

Sebastian Ruder

2018 ; Akbik et al., 2018 ; Baevski et al., Given enough data, a large number of parameters, and enough compute, a model can do a reasonable job. 2018 ; Wang et al., 2018 , Ruder et al., 2017 ) and pretrained language models ( Peters et al., 2019 ) of recent years. 2017 ; Peters et al.,

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Reward Isn't Free: Supervising Robot Learning with Language and Video from the Web

The Stanford AI Lab Blog

Conference of the North American Chapter of the Association for Computational Linguistics. ↩ Devlin, J., Annual Meeting of the Association for Computational Linguistics. ↩ Brown et al. Kalashnikov, D., Quillen, D., Kalakrishnan, M., Vanhoucke, V., Conference on Robot Learning. ↩ Kumar, A., Neumann, M.,

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Multi-domain Multilingual Question Answering

Sebastian Ruder

2018 ), Children's Book Test ( Hill et al., 2018 ), Children's Book Test ( Hill et al., 2018 ), college-level exam resources such as ReClor ( Yu et al., Instead, domain-adaptive fine-tuning ( Howard & Ruder, 2018 ; Gururangan et al., 2018 ; Lewis et al., 2018 ; Gupta et al.,

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