BERT (Chinese Wikipedia)
Analysis of information sources in references of the Wikipedia article "BERT" in Chinese language version.
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aclanthology.org
- Rogers, Anna; Kovaleva, Olga; Rumshisky, Anna. A Primer in BERTology: What We Know About How BERT Works. Transactions of the Association for Computational Linguistics. 2020, 8: 842–866 [2021-11-24]. doi:10.1162/tacl_a_00349. （原始内容存档于2022-04-03）.
aclweb.org
- Kovaleva, Olga; Romanov, Alexey; Rogers, Anna; Rumshisky, Anna. Revealing the Dark Secrets of BERT. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). November 2019: 4364–4373 [2020-10-19]. doi:10.18653/v1/D19-1445. （原始内容存档于2020-10-20） （美国英语）.
arxiv.org
- Devlin, Jacob; Chang, Ming-Wei; Lee, Kenton; Toutanova, Kristina. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. 2018-10-11. arXiv:1810.04805v2
[cs.CL]. - Zhu, Yukun; Kiros, Ryan; Zemel, Rich; Salakhutdinov, Ruslan; Urtasun, Raquel; Torralba, Antonio; Fidler, Sanja. Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books: 19–27. 2015. arXiv:1506.06724 [cs.CV].
- Annamoradnejad, Issa. ColBERT: Using BERT Sentence Embedding for Humor Detection. 2020-04-27. arXiv:2004.12765 [cs.CL].
- Polosukhin, Illia; Kaiser, Lukasz; Gomez, Aidan N.; Jones, Llion; Uszkoreit, Jakob; Parmar, Niki; Shazeer, Noam; Vaswani, Ashish. Attention Is All You Need. 2017-06-12. arXiv:1706.03762 [cs.CL].
- Khandelwal, Urvashi; He, He; Qi, Peng; Jurafsky, Dan. Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 284–294. Bibcode:2018arXiv180504623K. arXiv:1805.04623 . doi:10.18653/v1/p18-1027.
- Gulordava, Kristina; Bojanowski, Piotr; Grave, Edouard; Linzen, Tal; Baroni, Marco. Colorless Green Recurrent Networks Dream Hierarchically. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 1195–1205. Bibcode:2018arXiv180311138G. arXiv:1803.11138 . doi:10.18653/v1/n18-1108.
- Giulianelli, Mario; Harding, Jack; Mohnert, Florian; Hupkes, Dieuwke; Zuidema, Willem. Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 240–248. Bibcode:2018arXiv180808079G. arXiv:1808.08079 . doi:10.18653/v1/w18-5426.
- Dai, Andrew; Le, Quoc. Semi-supervised Sequence Learning. 2015-11-04. arXiv:1511.01432 [cs.LG].
- Peters, Matthew; Neumann, Mark; Iyyer, Mohit; Gardner, Matt; Clark, Christopher; Lee, Kenton; Luke, Zettlemoyer. Deep contextualized word representations. 2018-02-15. arXiv:1802.05365v2 [cs.CL].
- Howard, Jeremy; Ruder, Sebastian. Universal Language Model Fine-tuning for Text Classification. 2018-01-18. arXiv:1801.06146v5 [cs.CL].
blog.google
- Understanding searches better than ever before. Google. 2019-10-25 [2019-11-27]. （原始内容存档于2021-01-27） （英语）.
- Nayak, Pandu. Understanding searches better than ever before. Google Blog. 2019-10-25 [2019-12-10]. （原始内容存档于2019-12-05）.
doi.org
- Rogers, Anna; Kovaleva, Olga; Rumshisky, Anna. A Primer in BERTology: What We Know About How BERT Works. Transactions of the Association for Computational Linguistics. 2020, 8: 842–866 [2021-11-24]. doi:10.1162/tacl_a_00349. （原始内容存档于2022-04-03）.
- Kovaleva, Olga; Romanov, Alexey; Rogers, Anna; Rumshisky, Anna. Revealing the Dark Secrets of BERT. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). November 2019: 4364–4373 [2020-10-19]. doi:10.18653/v1/D19-1445. （原始内容存档于2020-10-20） （美国英语）.
- Khandelwal, Urvashi; He, He; Qi, Peng; Jurafsky, Dan. Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 284–294. Bibcode:2018arXiv180504623K. arXiv:1805.04623 . doi:10.18653/v1/p18-1027.
- Gulordava, Kristina; Bojanowski, Piotr; Grave, Edouard; Linzen, Tal; Baroni, Marco. Colorless Green Recurrent Networks Dream Hierarchically. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 1195–1205. Bibcode:2018arXiv180311138G. arXiv:1803.11138 . doi:10.18653/v1/n18-1108.
- Giulianelli, Mario; Harding, Jack; Mohnert, Florian; Hupkes, Dieuwke; Zuidema, Willem. Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 240–248. Bibcode:2018arXiv180808079G. arXiv:1808.08079 . doi:10.18653/v1/w18-5426.
- Zhang, Kelly; Bowman, Samuel. Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 359–361. doi:10.18653/v1/w18-5448.
googleblog.com
ai.googleblog.com
- Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing. Google AI Blog. [2019-11-27]. （原始内容存档于2021-01-13） （英语）.
harvard.edu
ui.adsabs.harvard.edu
- Khandelwal, Urvashi; He, He; Qi, Peng; Jurafsky, Dan. Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 284–294. Bibcode:2018arXiv180504623K. arXiv:1805.04623 . doi:10.18653/v1/p18-1027.
- Gulordava, Kristina; Bojanowski, Piotr; Grave, Edouard; Linzen, Tal; Baroni, Marco. Colorless Green Recurrent Networks Dream Hierarchically. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 1195–1205. Bibcode:2018arXiv180311138G. arXiv:1803.11138 . doi:10.18653/v1/n18-1108.
- Giulianelli, Mario; Harding, Jack; Mohnert, Florian; Hupkes, Dieuwke; Zuidema, Willem. Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (Stroudsburg, PA, USA: Association for Computational Linguistics). 2018: 240–248. Bibcode:2018arXiv180808079G. arXiv:1808.08079 . doi:10.18653/v1/w18-5426.
naacl2019.org
- Best Paper Awards. NAACL. 2019 [2020-03-28]. （原始内容存档于2020-10-19）.
searchenginejournal.com
- Montti, Roger. Google's BERT Rolls Out Worldwide. Search Engine Journal. Search Engine Journal. 2019-12-10 [2019-12-10]. （原始内容存档于2020-11-29）.
searchengineland.com
- Google: BERT now used on almost every English query. Search Engine Land. 2020-10-15 [2020-11-24]. （原始内容存档于2022-05-06）.
towardsdatascience.com
- Horev, Rani. BERT Explained: State of the art language model for NLP. Towards Data Science. 2018 [27 September 2021]. （原始内容存档于2022-10-17）.
web.archive.org
- Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing. Google AI Blog. [2019-11-27]. （原始内容存档于2021-01-13） （英语）.
- Understanding searches better than ever before. Google. 2019-10-25 [2019-11-27]. （原始内容存档于2021-01-27） （英语）.
- Rogers, Anna; Kovaleva, Olga; Rumshisky, Anna. A Primer in BERTology: What We Know About How BERT Works. Transactions of the Association for Computational Linguistics. 2020, 8: 842–866 [2021-11-24]. doi:10.1162/tacl_a_00349. （原始内容存档于2022-04-03）.
- Horev, Rani. BERT Explained: State of the art language model for NLP. Towards Data Science. 2018 [27 September 2021]. （原始内容存档于2022-10-17）.
- Kovaleva, Olga; Romanov, Alexey; Rogers, Anna; Rumshisky, Anna. Revealing the Dark Secrets of BERT. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). November 2019: 4364–4373 [2020-10-19]. doi:10.18653/v1/D19-1445. （原始内容存档于2020-10-20） （美国英语）.
- Nayak, Pandu. Understanding searches better than ever before. Google Blog. 2019-10-25 [2019-12-10]. （原始内容存档于2019-12-05）.
- Montti, Roger. Google's BERT Rolls Out Worldwide. Search Engine Journal. Search Engine Journal. 2019-12-10 [2019-12-10]. （原始内容存档于2020-11-29）.
- Google: BERT now used on almost every English query. Search Engine Land. 2020-10-15 [2020-11-24]. （原始内容存档于2022-05-06）.
- Best Paper Awards. NAACL. 2019 [2020-03-28]. （原始内容存档于2020-10-19）.