Question Answering
125 items from seriousran/awesome-qa ★771
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"Ask the Right Questions: Active Question Reformulation with Reinforcement Learning" openreview.net
, Christian Buck and Jannis Bulian and Massimiliano Ciaramita and Wojciech Paweł Gajewski and Andrea Gesmundo and Neil Houlsby and Wei Wang, ICLR, 2018.
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"QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension" openreview.net
, Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le, ICLR, 2018.
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TriviaQA nlp.cs.washington.edu
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"Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks" nlp.cs.berkeley.edu
, Matthew Francis-Landau, Greg Durrett and Dan Klei, NAACL-HLT 2016.
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Why question answering is hard nicklothian.com
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MS MARCO msmarco.org
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"Question Answering in Restricted Domains: An Overview" mitpressjournals.org
, Diego Mollá and José Luis Vicedo, Computational Linguistics, 2007
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Paper microsoft.com
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"WIKIQA: A Challenge Dataset for Open-Domain Question Answering" microsoft.com
, Yi Yang, Wen-tau Yih, and Christopher Meek, EMNLP, 2015.
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"An Overview of Microsoft Deep QA System on Stanford WebQuestions Benchmark" microsoft.com
, Zhenghao Wang, Shengquan Yan, Huaming Wang, and Xuedong Huang, MSR-TR, 2014.
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"Web-based Question Answering: Revisiting AskMSR" microsoft.com
, Chen-Tse Tsai, Wen-tau Yih, and Christopher J.C. Burges, MSR-TR, 2015.
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"Question Answering with Knowledge Base, Web and Beyond" microsoft.com
, Yih, Scott Wen-tau and Ma, Hao, ACM SIGIR, 2016.
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WikiQA microsoft.com
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Jeopardy! jeopardy.com
champions in 2011.
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"Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions" ieeexplore.ieee.org
, Wei Shen, Jianyong Wang, Jiawei Han, IEEE Transactions on Knowledge and Data Engineering(TKDE), 2014.
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"Introduction to “This is Watson" ieeexplore.ieee.org
, IBM Journal of Research and Development, D. A. Ferrucci, 2012.
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IBM Watson ibm.com
Has state-of-the-arts performance.
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Question Answering hpi.de
By Dr. Mariana Neves | Hasso Plattner Institut | 2017.
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Question Answering with Knowledge Bases, Web and Beyond github.com
By Scott Wen-tau Yih & Hao Ma | Microsoft Research | 2016.
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NLIWOD's Question answering datasets github.com
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"WatsonPaths: Scenario-based Question Answering and Inference over Unstructured Information" domino.watson.ibm.com
, Adam Lally, Sugato Bachi, Michael A. Barborak, David W. Buchanan, Jennifer Chu-Carroll, David A. Ferrucci*, Michael R. Glass, Aditya Kalyanpur, Erik T. Mueller, J. William Murdock, Siddharth Patwardhan, John M. Prager, Christopher A. Welty, IBM Research Report RC25489, 2014.
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"Table Cell Search for Question Answering" dl.acm.org
, Sun, Huan and Ma, Hao and He, Xiaodong and Yih, Wen-tau and Su, Yu and Yan, Xifeng, WWW, 2016.
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"Open Domain Question Answering via Semantic Enrichment" dl.acm.org
, Huan Sun, Hao Ma, Wen-tau Yih, Chen-Tse Tsai, Jingjing Liu, and Ming-Wei Chang, WWW, 2015.
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AI2 Science Questions v2.1(2017) data.allenai.org
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"Stacked Attention Networks for Image Question Answering" cv-foundation.org
, Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Smola, CVPR, 2016.
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Reading Wikipedia to Answer Open-Domain Questions cs.stanford.edu
, Danqi Chen, Adam Fisch, Jason Weston & Antoine Bordes, ACL, 2017.
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Story cloze test cs.rochester.edu
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Qestion-Answer Dataset by CMU cs.cmu.edu
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Morphological analysis cs.bham.ac.uk
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MIT media lab's Knowledge graph conceptnet.io
Is a freely-available semantic network, designed to help computers understand the meanings of words that people use.
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"Unsupervised Entity-Relation Analysis in IBM Watson" cogsys.org
, Aditya Kalyanpur, J William Murdock, ACS, 2015.
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http://cogcomp.org/page/publication_view/833 cogcomp.org
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MultiRC cogcomp.org
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https://arxiv.org/pdf/2010.08422.pdf arxiv.org
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https://arxiv.org/pdf/2005.00038.pdf arxiv.org
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https://arxiv.org/pdf/2001.09694v2.pdf arxiv.org
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https://arxiv.org/pdf/1911.04118.pdf arxiv.org
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Answering Complex Open-domain Questions Through Iterative Query Generation arxiv.org
, Peng Qi, et al., EMNLP-IJCNLP 2019, Oct 2019.
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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter arxiv.org
, Victor sanh, et al., arXiv, 2019.
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A Discrete Hard EM Approach for Weakly Supervised Question Answering arxiv.org
, Sewon Min, et al., EMNLP-IJCNLP, 2019, Sep 2019.
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KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning arxiv.org
, Bill Yuchen Lin, et al., EMNLP-IJCNLP 2019, Sep 2019.
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Mixture Content Selection for Diverse Sequence Generation arxiv.org
, Jaemin Cho, et al., EMNLP-IJCNLP 2019, Sep 2019.
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Language Models as Knowledge Bases? arxiv.org
, Fabio Petron, et al., EMNLP-IJCNLP 2019, Sep 2019.
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LXMERT: Learning Cross-Modality Encoder Representations from Transformers arxiv.org
, Hao Tan, et al., EMNLP-IJCNLP 2019, Dec 2019.
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SpanBERT: Improving Pre-training by Representing and Predicting Spans arxiv.org
, Mandar Joshi, et al., TACL, 2019.
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Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications arxiv.org
, Wei Zhao, et al., ACL 2019, Jun 2019.
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Cognitive Graph for Multi-Hop Reading Comprehension at Scale arxiv.org
, Ming Ding, et al., ACL 2019, Jun 2019.
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"Did the model understand the question?" arxiv.org
, Pramod K. Mudrakarta and Ankur Taly and Mukund Sundararajan and Kedar Dhamdhere, ACL, 2018.
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"An efficient framework for learning sentence representations" arxiv.org
, Lajanugen Logeswaran, Honglak Lee, ICLR, 2018.
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Matching Article Pairs with Graphical Decomposition and Convolutions arxiv.org
, Bang Liu, et al., ACL 2019, May 2019.
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