Fetching the paper…
Reading the bibliography…
Generative commonsense reasoning which aims to empower machines to generate sentences with the capacity of reasoning over a set of concepts is a critical bottleneck for text generation.
Roberta: A robustly optimized bert pretraining approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; and Stoyanov, V. 2019 · 1907
Earlier work this paper cites.
Critical values and probability levels for the Wilcoxon rank sum test and the Wilcoxon signed rank test
Wilcoxon, F.; Katti, S.; and Wilcox, R. A. 1970 · 1970
Earlier work this paper cites.
Unilmv2: Pseudo-masked language models for unified language model pre-training
Bao, H.; Dong, L.; Wei, F.; Wang, W.; Yang, N.; Liu, X.; Wang, Y.; Piao, S.; Gao, J.; Zhou, M.; et al. 2020 · 2002
Earlier work this paper cites.
BLEU: a method for automatic evaluation of machine translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Lin, C.-Y. 2004 · 2004
Earlier work this paper cites.
METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Banerjee, S.; and Lavie, A. 2005 · 2005
Earlier work this paper cites.
Dbpedia: A nucleus for a web of open data
Auer, S.; Bizer, C.; Kobilarov, G.; Lehmann, J.; Cyganiak, R.; and Ives, Z. 2007 · 2007
Earlier work this paper cites.
Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K.; Evans, C.; Paritosh, P.; Sturge, T.; and Taylor, J. 2008 · 2008
Earlier work this paper cites.
Enhancing topic-to-essay generation with external commonsense knowledge
Yang, P.; Li, L.; Luo, F.; Liu, T.; and Sun, X. 2019a · 2012
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Bordes, A.; Usunier, N.; Garcia-Duran, A.; Weston, J.; and Yakhnenko, O. 2013 · 2013
Earlier work this paper cites.
Convolutional neural networks for sentence classification
Kim, Y. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Pennington, J.; Socher, R.; and Manning, C. D. 2014 · 2014
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
Vedantam, R.; Lawrence Zitnick, C.; and Parikh, D. 2015 · 2015
Earlier work this paper cites.
Spice: Semantic propositional image caption evaluation
Anderson, P.; Fernando, B.; Johnson, M.; and Gould, S. 2016 · 2016
Cited alongside, same era.
Gaussian error linear units (gelus)
Hendrycks, D.; and Gimpel, K. 2016 · 2016
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; and Wojna, Z. 2016 · 2016
Cited alongside, same era.
ConceptNet 5.5: an open multilingual graph of general knowledge
Speer, R.; Chin, J.; and Havasi, C. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Graph attention networks
Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2017 · 2017
Language models are unsupervised multitask learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
Later among the works it cites.
Atomic: An atlas of machine commonsense for if-then reasoning
Sap, M.; Le Bras, R.; Allaway, E.; Bhagavatula, C.; Lourie, N.; Rashkin, H.; Roof, B.; Smith, N. A.; and Choi, Y. 2019 · 2019
Later among the works it cites.
Mass: Masked sequence to sequence pre-training for language generation
Song, K.; Tan, X.; Qin, T.; Lu, J.; and Liu, T.-Y. 2019 · 2019
Later among the works it cites.
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Talmor, A.; Herzig, J.; Lourie, N.; and Berant, J. 2019 · 2019
Later among the works it cites.
ERNIE: Enhanced language representation with informative entities
Zhang, Z.; Han, X.; Liu, Z.; Jiang, X.; Sun, M.; and Liu, Q. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Neural baby talk
Lu, J.; Yang, J.; Batra, D.; and Parikh, D. 2018 · 2018
Cited alongside, same era.
Unified language model pre-training for natural language understanding and generation
Dong, L.; Yang, N.; Wang, W.; Wei, F.; Liu, X.; Wang, Y.; Gao, J.; Zhou, M.; and Hon, H.-W. 2019 · 2019
Cited alongside, same era.
Story ending generation with incremental encoding and commonsense knowledge
Guan, J.; Wang, Y.; and Huang, M. 2019 · 2019
Cited alongside, same era.
Cosmos qa: Machine reading comprehension with contextual commonsense reasoning
Huang, L.; Bras, R. L.; Bhagavatula, C.; and Choi, Y. 2019 · 2019
Cited alongside, same era.
Kagnet: Knowledge-aware graph networks for commonsense reasoning
Lin, B. Y.; Chen, X.; Chen, J.; and Ren, X. 2019 · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
Cited alongside, same era.
Language models are few-shot learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 2020
Closest in time.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2020 · 2020
Closest in time.
CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning
Lin, B. Y.; Shen, M.; Zhou, W.; Zhou, P.; Bhagavatula, C.; Choi, Y.; and Ren, X. 2020 · 2020
Closest in time.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Closest in time.
Winogrande: An adversarial winograd schema challenge at scale
Sakaguchi, K.; Bras, R. L.; Bhagavatula, C.; and Choi, Y. 2020 · 2020
Closest in time.
KEPLER: A unified model for knowledge embedding and pre-trained language representation
Wang, X.; Gao, T.; Zhu, Z.; Liu, Z.; Li, J.; and Tang, J. 2020 · 2020
Closest in time.
Grounded conversation generation as guided traverses in commonsense knowledge graphs
Zhang, H.; Liu, Z.; Xiong, C.; and Liu, Z. 2020 · 2043
Closest in time.