This page shows the most relevant public items for Awesome List: nlp-classic, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Paper • May 24, 2019 • arxiv.org • Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designe...
Paper • Sep 12, 2018 • arxiv.org • Jinman Zhao, Sidharth Mudgal, Yingyu Liang
We approach the problem of generalizing pre-trained word embeddings beyond fixed-size vocabularies without using additional contextual information. We propose a subword-level word vector generation...
Paper • May 11, 2018 • arxiv.org • Prathusha K Sarma, YIngyu Liang, William A Sethares
Generic word embeddings are trained on large-scale generic corpora; Domain Specific (DS) word embeddings are trained only on data from a domain of interest. This paper proposes a method to combine ...
Paper • Mar 7, 2018 • arxiv.org • Lajanugen Logeswaran, Honglak Lee
In this work we propose a simple and efficient framework for learning sentence representations from unlabelled data. Drawing inspiration from the distributional hypothesis and recent work on learni...
Paper • Apr 13, 2018 • arxiv.org • Guillaume Lample, Alexis Conneau, Ludovic Denoyer, Marc'Aurelio Ranzato
Machine translation has recently achieved impressive performance thanks to recent advances in deep learning and the availability of large-scale parallel corpora. There have been numerous attempts t...
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Use weekly for fast-moving updates, monthly for stable trend confirmation, and all-time for evergreen references. This guidance is specific to Awesome List: nlp-classic topic page on Attendemia and is written so it still makes sense without reading other sections on the page.
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