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Commonsense knowledge acquisition is a key problem for artificial intelligence.
Automatic acquisition of hyponyms from large text corpora
Marti A. Hearst · 1992
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Selectional preference and sense disambiguation
Philip Resnik · 1997
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Conceptnet: a practical commonsense reasoning tool-kit
Hugo Liu and Push Singh · 2004
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Open information extraction from the web
Oren Etzioni, Michele Banko, Stephen Soderland, and Daniel S. Weld · 2008
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Probase: A probabilistic taxonomy for text understanding
Wentao Wu, Hongsong Li, Haixun Wang, and Kenny Q Zhu · 2012
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Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D. Manning · 2015
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Commonsense knowledge base completion
Xiang Li, Aynaz Taheri, Lifu Tu, and Kevin Gimpel · 2016
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Dailydialog: A manually labelled multi-turn dialogue dataset
Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu · 2017
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, L · 2017
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Semeval-2018 task 11: Machine comprehension using commonsense knowledge
Simon Ostermann, Michael Roth, Ashutosh Modi, Stefan Thater, and Manfred Pinkal · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Commonsense knowledge base completion and generation
Itsumi Saito, Kyosuke Nishida, Hisako Asano, and Junji Tomita · 2018
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Graph attention networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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How large are lions? inducing distributions over quantitative attributes
Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, and Dan Roth · 2019
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Kagnet: Knowledge-aware graph networks for commonsense reasoning
Bill Yuchen Lin, Xinyue Chen, Jamin Chen, and Xiang Ren · 2019
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Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander H. Miller · 2019
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Atomic: an atlas of machine commonsense for if-then reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith, and Yejin Choi · 2019
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Liang Wang, Meng Sun, Wei Zhao, Kewei Shen, and Jingming Liu · 2018
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COMET: commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi · 2019
Cited alongside, same era.
Commonsense knowledge mining from pretrained models
Joe Davison, Joshua Feldman, and Alexander M. Rush · 2019
Cited alongside, same era.
Hongming Zhang, Hantian Ding, and Yangqiu Song · 2019
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ASER: A large-scale eventuality knowledge graph
Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung · 2020
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Temporal common sense acquisition with minimal supervision
Ben Zhou, Qiang Ning, Daniel Khashabi, and Dan Roth · 2020
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