Fetching the paper…
Reading the bibliography…
We propose an unsupervised strategy for the selection of justification sentences for multi-hop question answering (QA) that (a) maximizes the relevance of the selected sentences, (b) minimizes the overlap between the selected facts, and (c) maximizes the coverage of both question and answer.
Improving question answering with external knowledge
Xiaoman Pan, Kai Sun, Dian Yu, Heng Ji, and Dong Yu. 2019 · 1902
Earlier work this paper cites.
Dream: A challenge dataset and models for dialogue-based reading comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, and Claire Cardie. 2019 · 1902
Earlier work this paper cites.
Evidence sentence extraction for machine reading comprehension
Hai Wang, Dian Yu, Kai Sun, Jianshu Chen, Dong Yu, Dan Roth, and David McAllester. 2019 · 1902
Earlier work this paper cites.
Understanding dataset design choices for multi-hop reasoning
Jifan Chen and Greg Durrett. 2019 · 1904
Earlier work this paper cites.
Repurposing entailment for multi-hop question answering tasks
Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, and Niranjan Balasubramanian. 2019 · 1904
Earlier work this paper cites.
Learning to rank answers on large online qa collections
Mihai Surdeanu, Massimiliano Ciaramita, and Hugo Zaragoza. 2008 · 2008
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
Earlier work this paper cites.
Deep learning for answer sentence selection
Lei Yu, Karl Moritz Hermann, Phil Blunsom, and Stephen Pulman. 2014 · 2014
Earlier work this paper cites.
A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning. 2015 · 2015
Earlier work this paper cites.
Constraint-based question answering with knowledge graph
Junwei Bao, Nan Duan, Zhao Yan, Ming Zhou, and Tiejun Zhao. 2016 · 2016
Earlier work this paper cites.
Question answering via integer programming over semi-structured knowledge
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, and Dan Roth. 2016 · 2016
Earlier work this paper cites.
Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2016 · 2016
Earlier work this paper cites.
A compare-aggregate model for matching text sequences
Shuohang Wang and Jing Jiang. 2016 · 2016
Earlier work this paper cites.
A joint model for question answering over multiple knowledge bases
Yuanzhe Zhang, Shizhu He, Kang Liu, and Jun Zhao. 2016 · 2016
Earlier work this paper cites.
A causal framework for explaining the predictions of black-box sequence-to-sequence models
David Alvarez-Melis and Tommi S Jaakkola. 2017 · 2017
Earlier work this paper cites.
” what is relevant in a text document?”: An interpretable machine learning approach
Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, and Wojciech Samek. 2017 · 2017
Earlier work this paper cites.
Explanation and justification in machine learning: A survey
Or Biran and Courtenay Cotton. 2017 · 2017
Earlier work this paper cites.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Earlier work this paper cites.
Coarse-to-fine question answering for long documents
Eunsol Choi, Daniel Hewlett, Jakob Uszkoreit, Illia Polosukhin, Alexandre Lacoste, and Jonathan Berant. 2017 · 2017
Earlier work this paper cites.
Supervised and unsupervised transfer learning for question answering
Yu-An Chung, Hung-Yi Lee, and James Glass. 2017 · 2017
Cited alongside, same era.
Kbqa: learning question answering over qa corpora and knowledge bases
Wanyun Cui, Yanghua Xiao, Haixun Wang, Yangqiu Song, Seung-won Hwang, and Wei Wang. 2017 · 2017
Cited alongside, same era.
Quasar: Datasets for question answering by search and reading
Bhuwan Dhingra, Kathryn Mazaitis, and William W Cohen. 2017 · 2017
Cited alongside, same era.
Searchqa: A new q&a dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V Ugur Guney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
Cited alongside, same era.
An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge
Cross attention for selection-based question answering
Alessio Gravina, Federico Rossetto, Silvia Severini, and Giuseppe Attardi. 2018 · 2018
Later among the works it cites.
Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Later among the works it cites.
Looking beyond the surface: A challenge set for reading comprehension over multiple sentences
Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth. 2018a · 2018
Later among the works it cites.
Scitail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
Later among the works it cites.
A review on deep learning techniques applied to answer selection
Tuan Manh Lai, Trung Bui, and Sheng Li. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yanchao Hao, Yuanzhe Zhang, Kang Liu, Shizhu He, Zhanyi Liu, Hua Wu, and Jun Zhao. 2017 · 2017
Cited alongside, same era.
Answering complex questions using open information extraction
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2017 · 2017
Cited alongside, same era.
Race: Large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
Cited alongside, same era.
Question answering through transfer learning from large fine-grained supervision data
Sewon Min, Minjoon Seo, and Hannaneh Hajishirzi. 2017 · 2017
Cited alongside, same era.
Wojciech Samek, Thomas Wiegand, and Klaus-Robert Müller. 2017 · 2017
Cited alongside, same era.
Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
Cited alongside, same era.
Ranking kernels for structures and embeddings: A hybrid preference and classification model
Kateryna Tymoshenko, Daniele Bonadiman, and Alessandro Moschitti. 2017 · 2017
Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman. 2017 · 2017
Cited alongside, same era.
Denoising distantly supervised open-domain question answering
Yankai Lin, Haozhe Ji, Zhiyuan Liu, and Maosong Sun. 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.
Efficient and robust question answering from minimal context over documents
Sewon Min, Victor Zhong, Richard Socher, and Caiming Xiong. 2018 · 2018
Later among the works it cites.
Minghui Qiu, Liu Yang, Feng Ji, Weipeng Zhao, Wei Zhou, Jun Huang, Haiqing Chen, W Bruce Croft, and Wei Lin. 2018 · 2018
Later among the works it cites.
Know what you don’t know: Unanswerable questions for squad
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
Later among the works it cites.
Improving machine reading comprehension with general reading strategies
Kai Sun, Dian Yu, Dong Yu, and Claire Cardie. 2018 · 2018
Later among the works it cites.
Multihop attention networks for question answer matching
Nam Khanh Tran and Claudia Niedereée. 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.
Sanity check: A strong alignment and information retrieval baseline for question answering
Vikas Yadav, Rebecca Sharp, and Mihai Surdeanu. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
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.
Kg2̂: Learning to reason science exam questions with contextual knowledge graph embeddings
Yuyu Zhang, Hanjun Dai, Kamil Toraman, and Le Song. 2018 · 2018
Later among the works it cites.
An interpretable reasoning network for multi-relation question answering
Mantong Zhou, Minlie Huang, and Xiaoyan Zhu. 2018 · 2018
Later among the works it cites.
Learning to transform, combine, and reason in open-domain question answering
Mostafa Dehghani, Hosein Azarbonyad, Jaap Kamps, and Maarten de Rijke. 2019 · 2019
Closest in time.
Alignment over heterogeneous embeddings for question answering
Vikas Yadav, Steven Bethard, and Mihai Surdeanu. 2019 · 2019
Closest in time.