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nlp:pretraining [2026/01/14 07:40] – [Contextualized Pretrained Models] jmflanignlp:pretraining [2026/02/20 06:35] (current) – [Key and Early Papers] jmflanig
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 For a history, see section 2.4 of [[https://arxiv.org/pdf/2003.08271.pdf|Qiu 2020]] or the related work in the [[https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf|GPT-2 paper]]. For a history, see section 2.4 of [[https://arxiv.org/pdf/2003.08271.pdf|Qiu 2020]] or the related work in the [[https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf|GPT-2 paper]].
   * [[https://arxiv.org/pdf/1103.0398|Collobert et al 2011 - Natural Language Processing (almost) from Scratch]]   * [[https://arxiv.org/pdf/1103.0398|Collobert et al 2011 - Natural Language Processing (almost) from Scratch]]
 +  * [[https://arxiv.org/pdf/1506.06726|Kiros et al 2015 - Skip-Thought Vectors]]
   * [[https://arxiv.org/pdf/1511.01432.pdf|Dai et al 2015 - Semi-supervised Sequence Learning]]   * [[https://arxiv.org/pdf/1511.01432.pdf|Dai et al 2015 - Semi-supervised Sequence Learning]]
 +  * [[https://arxiv.org/pdf/1705.00108|Peters et al 2017 - Semi-supervised Sequence Tagging with Bidirectional Language Models]]
   * [[https://arxiv.org/pdf/1611.02683.pdf|Ramachandran et al 2017 - Unsupervised Pretraining for Sequence to Sequence Learning]]   * [[https://arxiv.org/pdf/1611.02683.pdf|Ramachandran et al 2017 - Unsupervised Pretraining for Sequence to Sequence Learning]]
   * [[https://arxiv.org/pdf/1802.05365.pdf|Peters et al 2018 - Deep Contextualized Word Representations]]   * [[https://arxiv.org/pdf/1802.05365.pdf|Peters et al 2018 - Deep Contextualized Word Representations]]
nlp/pretraining.1768376450.txt.gz · Last modified: 2026/01/14 07:40 by jmflanig

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