Question Answering
125 items from seriousran/awesome-qa ★771
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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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"Analyzing Language Learned by an Active Question Answering Agent" arxiv.org
, Christian Buck and Jannis Bulian and Massimiliano Ciaramita and Wojciech Gajewski and Andrea Gesmundo and Neil Houlsby and Wei Wang, NIPS, 2017.
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https://arxiv.org/pdf/1712.07040v1.pdf arxiv.org
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"Learning to Skim Text" arxiv.org
, Adams Wei Yu, Hongrae Lee, Quoc V. Le, 2017. : Show only what you want in Text
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"Deep Joint Entity Disambiguation with Local Neural Attention" arxiv.org
, Octavian-Eugen Ganea and Thomas Hofmann, 2017.
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"Neural Paraphrase Identification of Questions with Noisy Pretraining" arxiv.org
, Gaurav Singh Tomar and Thyago Duque and Oscar Täckström and Jakob Uszkoreit and Dipanjan Das, SCLeM, 2017.
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"Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors" arxiv.org
, Radu Soricut, Nan Ding, 2018.
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https://arxiv.org/pdf/1611.09830.pdf arxiv.org
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"BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION" arxiv.org
, Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, Hananneh Hajishirzi, ICLR, 2017.
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"Learning Recurrent Span Representations for Extractive Question Answering" arxiv.org
, Kenton Lee and Shimi Salant and Tom Kwiatkowski and Ankur Parikh and Dipanjan Das and Jonathan Berant, ICLR, 2017.
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MINILM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers arxiv.org
, Wenhui Wang, et al., arXiv, 2020.
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T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arxiv.org
, Colin Raffel, et al., arXiv preprint, 2019.
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ALBERT: A Lite BERT for Self-supervised Learning of Language Representations arxiv.org
, Zhenzhong Lan, et al., arXiv preprint, 2019.
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RoBERTa: A Robustly Optimized BERT Pretraining Approach arxiv.org
, Yinhan Liu, et al., arXiv preprint, 2019.
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ELI5: Long Form Question Answering arxiv.org
, Angela Fan, et al., ACL 2019, Jul 2019
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XLNet: Generalized Autoregressive Pretraining for Language Understanding arxiv.org
, Zhilin Yang, et al., arXiv preprint, 2019.
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Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index arxiv.org
, Minjoon Seo, et al., ACL 2019, Jun 2019.
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