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Understanding narratives requires reasoning about implicit world knowledge related to the causes, effects, and states of situations described in text.
Ranking and Selecting Multi-Hop Knowledge Paths to Better Predict Human Needs
Paul, D.; and Frank, A. 2019 · 1904
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Social IQA: Commonsense Reasoning about Social Interactions
Sap, M.; Rashkin, H.; Chen, D.; Le Bras, R.; and Choi, Y. 2019b · 1904
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Roberta: A robustly optimized bert pretraining approach
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KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
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Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
Fan, A.; Gardent, C.; Braud, C.; and Bordes, A. 2019 · 1910
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Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion
Malaviya, C.; Bhagavatula, C.; Bosselut, A.; and Choi, Y. 2019 · 1910
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A general psychoevolutionary theory of emotion
Plutchik, R. 1980 · 1980
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Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets
Lewis, P.; Stenetorp, P.; and Riedel, S. 2020 · 2008
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Automated Storytelling via Causal, Commonsense Plot Ordering
Ammanabrolu, P.; Cheung, W.; Broniec, W.; and Riedl, M. O. 2020 · 2009
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Commonsense Knowledge Base Completion
Li, X.; Taheri, A.; Tu, L.; and Gimpel, K. 2016 · 2016
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Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
Weston, J.; Bordes, A.; Chopra, S.; and Mikolov, T. 2016 · 2016
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Annotation Artifacts in Natural Language Inference Data
Gururangan, S.; Swayamdipta, S.; Levy, O.; Schwartz, R.; Bowman, S.; and Smith, N. A. 2018 · 2017
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Li, L.; and Gauthier, J. 2017 · 2017
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ConceptNet 5.5: An open multilingual graph of general knowledge
Speer, R.; Chin, J.; and Havasi, C. 2017 · 2017
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Dynamic Integration of Background Knowledge in Neural NLU Systems
Weissenborn, D.; Kovcisk’y, T.; and Dyer, C. 2017 · 2017
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Commonsense for Generative Multi-Hop Question Answering Tasks
Bauer, L.; Wang, Y.; and Bansal, M. 2018 · 2018
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Simulating Action Dynamics with Neural Process Networks
Bosselut, A.; Levy, O.; Holtzman, A.; Ennis, C.; Fox, D.; and Choi, Y. 2018 · 2018
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Question Answering by Reasoning Across Documents with Graph Convolutional Networks
Cao, N. D.; Aziz, W.; and Titov, I. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Welbl, J.; Stenetorp, P.; and Riedel, S. 2018 · 2018
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Yang, Z.; Qi, P.; Zhang, S.; Bengio, Y.; Cohen, W. W.; Salakhutdinov, R.; and Manning, C. D. 2018 · 2018
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
Bosselut, A.; Rashkin, H.; Sap, M.; Malaviya, C.; Çelikyilmaz, A.; and Choi, Y. 2019 · 2019
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Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
Das, R.; Munkhdalai, T.; Yuan, X.; Trischler, A.; and McCallum, A. 2019 · 2019
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Commonsense Knowledge Mining from Pretrained Models
Davison, J.; Feldman, J.; and Rush, A. 2019 · 2019
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Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning
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Neural Models for Reasoning over Multiple Mentions Using Coreference
Dhingra, B.; Jin, Q.; Yang, Z.; Cohen, W. W.; and Salakhutdinov, R. 2018 · 2018
Cited alongside, same era.
Hierarchical Neural Story Generation
Fan, A.; Lewis, M.; and Dauphin, Y. 2018 · 2018
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Learning to Write with Cooperative Discriminators
Holtzman, A.; Buys, J.; Forbes, M.; Bosselut, A.; Golub, D.; and Choi, Y. 2018 · 2018
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Commonsense mining as knowledge base completion? A study on the impact of novelty
Jastrzębski, S.; Bahdanau, D.; Hosseini, S.; Noukhovitch, M.; Bengio, Y.; and Cheung, J. 2018 · 2018
Cited alongside, same era.
Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge
Mihaylov, T.; and Frank, A. 2018 · 2018
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Improving language understanding by generative pre-training
Radford, A.; Narasimhan, K.; Salimans, T.; and Sutskever, I. 2018 · 2018
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Modeling Naive Psychology of Characters in Simple Commonsense Stories
Rashkin, H.; Bosselut, A.; Sap, M.; Knight, K.; and Choi, Y. 2018 · 2018
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Jiang, Y.; and Bansal, M. 2019 · 2019
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Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
Jiang, Y.; Joshi, N.; Chen, Y.-C.; and Bansal, M. 2019 · 2019
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Language Models as Knowledge Bases?
Petroni, F.; Rocktäschel, T.; Riedel, S.; Lewis, P.; Bakhtin, A.; Wu, Y.; and Miller, A. 2019 · 2019
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Language models are unsupervised multitask learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
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Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Zhong, V.; Xiong, C.; Keskar, N. S.; and Socher, R. 2019 · 2019
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Rˆ3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge
Chakrabarty, T.; Ghosh, D.; Muresan, S.; and Peng, N. 2020 · 2020
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Modeling Label Semantics for Predicting Emotional Reactions
Gaonkar, R.; Kwon, H.; Bastan, M.; Balasubramanian, N.; and Chambers, N. 2020 · 2020
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A Wizard-of-Oz Interface and Persona-based Methodology for Collecting Health Counseling Dialog
Kearns, W. R.; Kaura, N.; Divina, M.; Vo, C. V.; Si, D.; Ward, T. M.; and Yuwen, W. 2020 · 2020
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Unsupervised Commonsense Question Answering with Self-Talk
Shwartz, V.; West, P.; Bras, R. L.; Bhagavatula, C.; and Choi, Y. 2020 · 2020
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