2020

Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering

Wang, Peifeng, Peng, Nanyun, Ilievski, Filip et al.

Understand

Commonsense question answering (QA) requires background knowledge which is not explicitly stated in a given context.

Prior works use commonsense knowledge graphs (KGs) to obtain this knowledge for reasoning.
However, relying entirely on these KGs may not suffice, considering their limited coverage and the contextual dependence of their knowledge.
In this paper, we augment a general commonsense QA framework with a knowledgeable path generator.

Built on

Ranking and selecting multi-hop knowledge paths to better predict human needs
Original
Debjit Paul and Anette Frank. 2019 · 1904
Earlier work this paper cites.
Commonsense reasoning for natural language understanding: A survey of benchmarks, resources, and approaches
Original
Shane Storks, Qiaozi Gao, and Joyce Y Chai. 2019 · 1904
Earlier work this paper cites.
Comet: Commonsense transformers for automatic knowledge graph construction
Original
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019 · 1906
Earlier work this paper cites.
Careful selection of knowledge to solve open book question answering
Original
Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra, and Chitta Baral. 2019 · 1907
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Probing neural network comprehension of natural language arguments
Original
Timothy Niven and Hung-Yu Kao. 2019 · 1907
Earlier work this paper cites.
Abductive commonsense reasoning
Original
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, and Yejin Choi. 2019 · 1908
Earlier work this paper cites.
From’f’to’a’on the ny regents science exams: An overview of the aristo project
Original
Peter Clark, Oren Etzioni, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, et al. 2019 · 1909
Earlier work this paper cites.
Collaborative policy learning for open knowledge graph reasoning
Original
Cong Fu, Tong Chen, Meng Qu, Woojeong Jin, and Xiang Ren. 2019 · 1909
Earlier work this paper cites.
Cosmos qa: Machine reading comprehension with contextual commonsense reasoning
Original
Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2019 · 1909
Earlier work this paper cites.
Albert: A lite bert for self-supervised learning of language representations
Original
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 1909
Earlier work this paper cites.
Kagnet: Knowledge-aware graph networks for commonsense reasoning
Original
Bill Yuchen Lin, Xinyue Chen, Jamin Chen, and Xiang Ren. 2019 · 1909
Earlier work this paper cites.
Graph-based reasoning over heterogeneous external knowledge for commonsense question answering
Original
Shangwen Lv, Daya Guo, Jingjing Xu, Duyu Tang, Nan Duan, Ming Gong, Linjun Shou, Daxin Jiang, Guihong Cao, and Songlin Hu. 2019 · 1909
Earlier work this paper cites.
Exploring ways to incorporate additional knowledge to improve natural language commonsense question answering
Original
Arindam Mitra, Pratyay Banerjee, Kuntal Kumar Pal, Swaroop Mishra, and Chitta Baral. 2019 · 1909
Earlier work this paper cites.
Freelb: Enhanced adversarial training for language understanding
Original
Chen Zhu, Yu Cheng, Zhe Gan, Siqi Sun, Thomas Goldstein, and Jingjing Liu. 2019 · 1909
Earlier work this paper cites.

Similar

Towards generalizable neuro-symbolic systems for commonsense question answering
Original
Kaixin Ma, Jonathan Francis, Quanyang Lu, Eric Nyberg, and Alessandro Oltramari. 2019 · 1910
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Original
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019 · 1910
Cited alongside, same era.
Learning to retrieve reasoning paths over wikipedia graph for question answering
Original
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. 2019 · 1911
Cited alongside, same era.
Dynamic knowledge graph construction for zero-shot commonsense question answering
Original
Antoine Bosselut and Yejin Choi. 2019 · 1911
Cited alongside, same era.
Heuristics for interpretable knowledge graph contextualization
Original
Kshitij Fadnis, Kartik Talamadupula, Pavan Kapanipathi, Haque Ishfaq, Salim Roukos, and Achille Fokoue. 2019 · 1911
Cited alongside, same era.
Infusing knowledge into the textual entailment task using graph convolutional networks
Original
Pavan Kapanipathi, Veronika Thost, Siva Sankalp Patel, Spencer Whitehead, Ibrahim Abdelaziz, Avinash Balakrishnan, Maria Chang, Kshitij Fadnis, Chulaka Gunasekara, Bassem Makni, et al. 2019 · 1911
Cited alongside, same era.
Knowledge fusion and semantic knowledge ranking for open domain question answering
Original
Pratyay Banerjee and Chitta Baral. 2020 · 2004
Cited alongside, same era.
Scalable multi-hop relational reasoning for knowledge-aware question answering
Original
Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, Peifeng Wang, Jun Yan, and Xiang Ren. 2020 · 2005
Cited alongside, same era.
Unifiedqa: Crossing format boundaries with a single qa system
Original
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 2005
Cited alongside, same era.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Cited alongside, same era.
Commonsense knowledge base completion
Xiang Li, Aynaz Taheri, Lifu Tu, and Kevin Gimpel. 2016 · 2016
Cited alongside, same era.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Cited alongside, same era.

Then

Commonsense for generative multi-hop question answering tasks
Original
Lisa Bauer, Yicheng Wang, and Mohit Bansal. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Original
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
Exploiting explicit paths for multi-hop reading comprehension
Original
Souvik Kundu, Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
Later among the works it cites.
Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018
Later among the works it cites.
Knowledgeable reader: Enhancing cloze-style reading comprehension with external commonsense knowledge
Original
Todor Mihaylov and Anette Frank. 2018 · 2018
Later among the works it cites.
Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Later among the works it cites.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Original
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2018 · 2018
Later among the works it cites.
Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Original
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Swag: A large-scale adversarial dataset for grounded commonsense inference
Original
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
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 · 2019
Later among the works it cites.
Improving natural language inference using external knowledge in the science questions domain
Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa, Mo Yu, Kartik Talamadupula, Ibrahim Abdelaziz, Maria Chang, Achille Fokoue, Bassem Makni, Nicholas Mattei, et al. 2019 · 2019
Later among the works it cites.
Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Reading the bibliography…