Corrected CBOW Performs as well as Skip-gram

30 December 2020

Papers citing "Corrected CBOW Performs as well as Skip-gram"

9 / 9 papers shown

Title
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 258 19,824 0 23 Oct 2019
Better Word Embeddings by Disentangling Contextual n-Gram Information Prakhar Gupta Matteo Pagliardini Martin Jaggi 13 39 0 10 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 882 93,936 0 11 Oct 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 594 7,080 0 20 Apr 2018
Learning Word Vectors for 157 Languages Edouard Grave Piotr Bojanowski Prakhar Gupta Armand Joulin Tomas Mikolov SSL FaML 80 1,421 0 19 Feb 2018
Enriching Word Vectors with Subword Information Piotr Bojanowski Edouard Grave Armand Joulin Tomas Mikolov NAI SSL VLM 187 9,924 0 15 Jul 2016
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 282 33,445 0 16 Oct 2013
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 534 31,406 0 16 Jan 2013
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 129 2,195 0 24 Jun 2012