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Automated claim checking is the task of determining the veracity of a claim given evidence found in a knowledge base of trustworthy facts.
Induction Therapy With Autologous Mesenchymal Stem Cells in Living-Related Kidney Transplants: A Randomized Controlled Trial
Jianming Tan, Weizhen Wu, Xiumin Xu, Lianming Liao, Feng Zheng, Shari Messinger, Xinhui Sun, Jin Chen, Shunliang Yang, Jinquan Cai, Xia Gao, Antonello Pileggi, and Camillo Ricordi · 2012
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Fact checking and analyzing the web
François Goasdoué, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, and Stamatis Zampetakis · 2013
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In kidney transplant patients, alemtuzumab but not basiliximab/low-dose rabbit anti-thymocyte globulin induces b cell depletion and regeneration, which associates with a high incidence of de novo donor-specific anti-hla antibody development
Marta Todeschini, Monica Cortinovis, Norberto Perico, Francesca Poli, Annalisa Innocente, Regiane Aparecida Cavinato, Eliana Gotti, Piero Ruggenenti, Flavio Gaspari, Marina Noris, Giuseppe Remuzzi, and Federica Casiraghi · 2013
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Fact checking: Task definition and dataset construction
Andreas Vlachos and Sebastian Riedel · 2014
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Credibility assessment of textual claims on the web
Kashyap Popat, Subhabrata Mukherjee, Jannik Strötgen, and Gerhard Weikum · 2016
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Emergent: a novel data-set for stance classification
William Ferreira and Andreas Vlachos · 2016
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Fully automated fact checking using external sources
Georgi Karadzhov, Preslav Nakov, Lluís Màrquez, Alberto Barrón-Cedeño, and Ivan Koychev · 2017
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The knowledge graph as the default data model for learning on heterogeneous knowledge
Xander Wilcke, Peter Bloem, and Victor De Boer · 2017
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Anserini: Enabling the use of lucene for information retrieval research
Peilin Yang, Hui Fang, and Jimmy Lin · 2017
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The spread of true and false news online
Soroush Vosoughi, Deb Roy, and Sinan Aral · 2018
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FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 2018
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A content management perspective on fact-checking
Sylvie Cazalens, Philippe Lamarre, Julien Leblay, Ioana Manolescu, and Xavier Tannier · 2018
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Feature engineering for machine learning: principles and techniques for data scientists
Alice Zheng and Amanda Casari · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Cited alongside, same era.
MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, and Jakob Grue Simonsen · 2019
Cited alongside, same era.
Overview of the CLEF-2019 checkthat! lab: Automatic identification and verification of claims. task 2: Evidence and factuality
Maram Hasanain, Reem Suwaileh, Tamer Elsayed, Alberto Barrón-Cedeño, and Preslav Nakov · 2019
Cited alongside, same era.
FAKTA: An automatic end-to-end fact checking system
Moin Nadeem, Wei Fang, Brian Xu, Mitra Mohtarami, and James Glass · 2019
Cited alongside, same era.
Claimskg: A knowledge graph of fact-checked claims
Andon Tchechmedjiev, Pavlos Fafalios, Katarina Boland, Malo Gasquet, Matthäus Zloch, Benjamin Zapilko, Stefan Dietze, and Konstantin Todorov · 2019
Cited alongside, same era.
Fine-grained fact verification with kernel graph attention network
Zhenghao Liu, Chenyan Xiong, Maosong Sun, and Zhiyuan Liu · 2020
Later among the works it cites.
spaCy: Industrial-strength Natural Language Processing in Python, 2020
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, and Adriane Boyd · 2020
Later among the works it cites.
S2ORC: The semantic scholar open research corpus
Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel Weld · 2020
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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
Later among the works it cites.
The pile: An 800gb dataset of diverse text for language modeling, 2020
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy · 2020
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Extracting statistical mentions from textual claims to provide trusted content
Tien Duc Cao, Ioana Manolescu, and Xavier Tannier · 2019
Cited alongside, same era.
Mechanism-Based Treatment Strategies for IBD: Cytokines, Cell Adhesion Molecules, JAK Inhibitors, Gut Flora, and More
Philipp Schreiner, Markus F. Neurath, Siew C. Ng, Emad M. El-Omar, Ala I. Sharara, Taku Kobayashi, Tadakazu Hisamatsu, Toshifumi Hibi, and Gerhard Rogler · 2019
Cited alongside, same era.
Fact or fiction: Verifying scientific claims
David Wadden, Shanchuan Lin, Kyle Lo, Lucy Lu Wang, Madeleine van Zuylen, Arman Cohan, and Hannaneh Hajishirzi · 2020
Cited alongside, same era.
Climate-fever: A dataset for verification of real-world climate claims
Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, and Markus Leippold · 2020
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Cited alongside, same era.
Explainable automated fact-checking for public health claims
Neema Kotonya and Francesca Toni · 2020
Cited alongside, same era.
e-fever: Explanations and summaries forautomated fact checking
Dominik Stammbach and Elliott Ash · 2020
Cited alongside, same era.
A review on fact extraction and verification
Giannis Bekoulis, Christina Papagiannopoulou, and Nikos Deligiannis · 2021
Closest in time.
Evidence-based verification for real world information needs, 2021
James Thorne, Max Glockner, Gisela Vallejo, Andreas Vlachos, and Iryna Gurevych · 2021
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How robust are fact checking systems on colloquial claims?
Byeongchang Kim, Hyunwoo Kim, Seokhee Hong, and Gunhee Kim · 2021
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Automatic claim review for climate science via explanation generation, 2021
Shraey Bhatia, Jey Han Lau, and Timothy Baldwin · 2021
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Mlops: From model-centric to data-centric ai
Andrew Ng · 2021
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Fool me twice: Entailment from Wikipedia gamification
Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Börschinger, and Jordan Boyd-Graber · 2021
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Retrieving and reading: A comprehensive survey on open-domain question answering
Fengbin Zhu, Wenqiang Lei, Chao Wang, Jianming Zheng, Soujanya Poria, and Tat-Seng Chua · 2021
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The fake news challenge: Exploring how artificial intelligence technologies could be leveraged to combat fake news
Dean Pomerleau and Delip Rao · 2021
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