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Several recent works have suggested to represent semantic relations with questions and answers, decomposing textual information into separate interrogative natural language statements.
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George A Miller. 1995 · 1995
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The berkeley framenet project
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CatVar: a database of categorial variations for English
Nizar Habash and Bonnie Dorr. 2003 · 2003
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Annotating noun argument structure for NomBank
Adam Meyers, Ruth Reeves, Catherine Macleod, Rachel Szekely, Veronika Zielinska, Brian Young, and Ralph Grishman. 2004 · 2004
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The penn discourse treebank
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Minimal recursion semantics: An introduction
Ann Copestake, Dan Flickinger, Carl Pollard, and Ivan A Sag. 2005 · 2005
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VerbNet: A broad-coverage, comprehensive verb lexicon
Karin Kipper Schuler. 2005 · 2005
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Unsupervised transfer of semantic role models from verbal to nominal domain
Yanpeng Zhao and Ivan Titov. 2020 · 2005
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Open information extraction from the web
Oren Etzioni, Michele Banko, Stephen Soderland, and Daniel S Weld. 2008 · 2008
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The penn discourse treebank 2.0
Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Miltsakaki, Livio Robaldo, Aravind Joshi, and Bonnie Webber. 2008 · 2008
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Semeval-2010 task 9: The interpretation of noun compounds using paraphrasing verbs and prepositions
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Nominalizations: A probe into the architecture of grammar part i: The nominalization puzzle
Artemis Alexiadou. 2010 · 2010
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Discourse representation theory
Hans Kamp, Josef van Genabith, and Uwe Reyle. 2011 · 2011
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Universal conceptual cognitive annotation (ucca)
Omri Abend and Ari Rappoport. 2013 · 2013
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Abstract meaning representation for sembanking
Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Philipp Koehn, Martha Palmer, and Nathan Schneider. 2013 · 2013
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Question-answer driven semantic role labeling: Using natural language to annotate natural language
Luheng He, Mike Lewis, and Luke S. Zettlemoyer. 2015 · 2015
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Toward abstractive summarization using semantic representations
Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh, and Noah A Smith. 2015 · 2015
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Semeval 2015 task 18: Broad-coverage semantic dependency parsing
Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Silvie Cinková, Dan Flickinger, Jan Hajic, and Zdenka Uresova. 2015 · 2015
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Data recombination for neural semantic parsing
Robin Jia and Percy Liang. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Creating a large benchmark for open information extraction
Gabriel Stanovsky and Ido Dagan. 2016 · 2016
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Universal decompositional semantics on universal dependencies
Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2016 · 2016
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The state of the art in semantic representation
Omri Abend and Ari Rappoport. 2017 · 2017
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Will my auxiliary tagging task help? estimating auxiliary tasks effectivity in multi-task learning
Johannes Bjerva. 2017 · 2017
Evaluating and comparing textual summaries using question answering models and reading comprehension datasets
Mantas Gavenavicius. 2020 · 2020
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QuASE: Question-answer driven sentence encoding
Hangfeng He, Qiang Ning, and Dan Roth. 2020 · 2020
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QANom: Question-answer driven SRL for nominalizations
Ayal Klein, Jonathan Mamou, Valentina Pyatkin, Daniela Stepanov, Hangfeng He, Dan Roth, Luke Zettlemoyer, and Ido Dagan. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines
Valentina Pyatkin, Ayal Klein, Reut Tsarfaty, and Ido Dagan. 2020 · 2020
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The groningen meaning bank
Johan Bos, Valerio Basile, Kilian Evang, Noortje J Venhuizen, and Johannes Bjerva. 2017 · 2017
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Large-scale qa-srl parsing
Nicholas Fitzgerald, Julian Michael, Luheng He, and Luke S. Zettlemoyer. 2018 · 2018
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Guided neural language generation for abstractive summarization using abstract meaning representation
Hardy Hardy and Andreas Vlachos. 2018 · 2018
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Abstract meaning representation for multi-document summarization
Kexin Liao, Logan Lebanoff, and Fei Liu. 2018 · 2018
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Crowdsourcing question-answer meaning representations
Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, and Luke Zettlemoyer. 2018 · 2018
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Controlled crowdsourcing for high-quality QA-SRL annotation
Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, and Ido Dagan. 2020 · 2020
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Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks
Fynn Schröder and Chris Biemann. 2020 · 2020
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Robust question answering through sub-part alignment
Jifan Chen and Greg Durrett. 2021 · 2021
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Pix2seq: A language modeling framework for object detection
Ting Chen, Saurabh Saxena, Lala Li, David J Fleet, and Geoffrey Hinton. 2021 · 2021
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Towards question-answering as an automatic metric for evaluating the content quality of a summary
Daniel Deutsch, Tania Bedrax-Weiss, and Dan Roth. 2021 · 2021
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Yanai Elazar, Victoria Basmov, Yoav Goldberg, and Reut Tsarfaty. 2021 · 2021
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Q2:: Evaluating factual consistency in knowledge-grounded dialogues via question generation and question answering
Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, and Omri Abend. 2021 · 2021
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Extractive summarization considering discourse and coreference relations based on heterogeneous graph
Yin Jou Huang and Sadao Kurohashi. 2021 · 2021
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Simplifying paragraph-level question generation via transformer language models
Luis Enrico Lopez, Diane Kathryn Cruz, Jan Christian Blaise Cruz, and Charibeth Cheng. 2021 · 2021
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Efficiently summarizing text and graph encodings of multi-document clusters
Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi, and Markus Dreyer. 2021 · 2021
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Investigating pretrained language models for graph-to-text generation
Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, and Iryna Gurevych. 2021 · 2021
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Enhancing factual consistency of abstractive summarization
Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, and Meng Jiang. 2021 · 2021
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Conditional generation with a question-answering blueprint
Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, Kuzman Ganchev, Annie Louis, Fantine Huot, Dipanjan Das, and Mirella Lapata. 2022 · 2022
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