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As online false information continues to grow, automated fact-checking has gained an increasing amount of attention in recent years.
Storks, S., Gao, Q., and Chai, J. Y. (2019a) · 1904
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Storks, S., Gao, Q., and Chai, J. Y. (2019b) · 1904
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V. (2019b) · 1907
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Automatic Fact-Checking Using Context and Discourse Information
Atanasova, P., Nakov, P., Màrquez, L., Barrón-Cedeño, A., Karadzhov, G., Mihaylova, T., Mohtarami, M., and Glass, J. (2019b) · 1908
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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Deep learning methods for knowledge base population
Adel, H. (2018) · 1922
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Claimbuster: The first-ever end-to-end fact-checking system
Hassan, N., Zhang, G., Arslan, F., Caraballo, J., Jimenez, D., Gawsane, S., Hasan, S., Joseph, M., Kulkarni, A., Nayak, A. K., et al. (2017b) · 1948
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ClaimBuster: the first-ever end-to-end fact-checking system
Hassan, N., Zhang, G., Arslan, F., Caraballo, J., Jimenez, D., Gawsane, S., Hasan, S., Joseph, M., Kulkarni, A., Nayak, A. K., Sable, V., Li, C., and Tremayne, M. (2017c) · 1948
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Okapi at TREC-3
Robertson, S., Walker, S., Jones, S., Hancock-Beaulieu, M., and Gatford, M. (1994) · 1994
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Meaning and Grammar: An Introduction to Semantics
Chierchia, G. and McConnell-Ginet, S. (2000) · 2000
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A Benchmark Dataset of Check-worthy Factual Claims
Arslan, F., Hassan, N., Li, C., and Tremayne, M. (2020) · 2004
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The PASCAL Recognising Textual Entailment Challenge
Dagan, I., Glickman, O., and Magnini, B. (2005) · 2005
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The second PASCAL recognising textual entailment challenge
Bar-Haim, R., Dagan, I., Dolan, B., Ferro, L., and Giampiccolo, D. (2006) · 2006
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When logical inference helps determining textual entailment (and when it doesn’t)
Bos, J. and Markert, K. (2006) · 2006
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An Inference Model for Semantic Entailment in Natural Language
de Salvo Braz, R., Girju, R., Punyakanok, V., Roth, D., and Sammons, M. (2006) · 2006
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Learning alignments and leveraging natural logic
Chambers, N., Cer, D., Grenager, T., Hall, D., Kiddon, C., MacCartney, B., de Marneffe, M.-C., Ramage, D., Yeh, E., and Manning, C. D. (2007) · 2007
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The third PASCAL recognizing textual entailment challenge
Giampiccolo, D., Magnini, B., Dagan, I., and Dolan, B. (2007) · 2007
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COGEX at RTE 3
Tatu, M. and Moldovan, D. (2007) · 2007
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Finding contradictions in text
de Marneffe, M.-C., Rafferty, A. N., and Manning, C. D. (2008) · 2008
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The Fourth PASCAL Recognizing Textual Entailment Challenge
Giampiccolo, D., Dang, H., Magnini, B., Dagan, I., Cabrio, E., and Dolan, W. (2008) · 2008
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Recognizing textual entailment: Rational, evaluation and approaches
Dagan, I., Dolan, B., Magnini, B., and Roth, D. (2009) · 2009
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An extended model of natural logic
MacCartney, B. and Manning, C. D. (2009) · 2009
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Multi-Hop Fact Checking of Political Claims
Ostrowski, W., Arora, A., Atanasova, P., and Augenstein, I. (2020) · 2009
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Williams, E., Rodrigues, P., and Novak, V. (2020) · 2009
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A machine learning approach to textual entailment recognition
Zanzotto, F. M., Pennacchiotti, M., and Moschitti, A. (2009) · 2009
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Scientific Claim Verification with VERT5ERINI
Pradeep, R., Ma, X., Nogueira, R., and Lin, J. (2020) · 2010
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Computational journalism: A call to arms to database researchers
Cohen, S., Li, C., Yang, J., and Yu, C. (2011) · 2011
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CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims
Diggelmann, T., Boyd-Graber, J., Bulian, J., Ciaramita, M., and Leippold, M. (2021) · 2012
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A Paragraph-level Multi-task Learning Model for Scientific Fact-Verification
Li, X., Burns, G., and Peng, N. (2021) · 2012
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DBpedia: A multilingual cross-domain knowledge base
Mendes, P., Jakob, M., and Bizer, C. (2012) · 2012
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Real-time population of knowledge bases: Opportunities and challenges
Nakashole, N. and Weikum, G. (2012) · 2012
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Benchmarking Applied Semantic Inference: The PASCAL Recognising Textual Entailment Challenges
Bar-Haim, R., Dagan, I., and Szpektor, I. (2014) · 2014
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Fact checking: Task definition and dataset construction
Vlachos, A. and Riedel, S. (2014) · 2014
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A large annotated corpus for learning natural language inference
Bowman, S. R., Angeli, G., Potts, C., and Manning, C. D. (2015) · 2015
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Misleading Online Content: Recognizing Clickbait as "False News"
Chen, Y., Conroy, N. J., and Rubin, V. L. (2015) · 2015
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Detecting check-worthy factual claims in presidential debates
Hassan, N., Li, C., and Tremayne, M. (2015) · 2015
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Farasa: A fast and furious segmenter for arabic
Abdelali, A., Darwish, K., Durrani, N., and Mubarak, H. (2016) · 2016
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The State of Automated Factchecking
Babakar, M. and Moy, W. (2016) · 2016
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Stop clickbait: Detecting and preventing clickbaits in online news media
Chakraborty, A., Paranjape, B., Kakarla, S., and Ganguly, N. (2016) · 2016
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Emergent: a novel data-set for stance classification
Ferreira, W. and Vlachos, A. (2016) · 2016
Cited alongside, same era.
Fast & furious fact check challenge
Francis, D. and Fact, F. (2016) · 2016
Cited alongside, same era.
Harnessing deep neural networks with logic rules
Hu, Z., Ma, X., Liu, Z., Hovy, E., and Xing, E. (2016) · 2016
Cited alongside, same era.
Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims
Elsayed, T., Nakov, P., Barrón-Cedeño, A., Hasanain, M., Suwaileh, R., Martino, G., and Atanasova, P. (2019) · 2019
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RumourEval 2019: Determining Rumour Veracity and Support for Rumours
Gorrell, G., Bontcheva, K., Derczynski, L., Kochkina, E., Liakata, M., and Zubiaga, A. (2018) · 2019
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A richly annotated corpus for different tasks in automated fact-checking
Hanselowski, A., Stab, C., Schulz, C., Li, Z., and Gurevych, I. (2019) · 2019
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KnowledgeNet: A benchmark dataset for knowledge base population
Mesquita, F., Cannaviccio, M., Schmidek, J., Mirza, P., and Barbosa, D. (2019) · 2019
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Combining fact extraction and verification with neural semantic matching networks
Nie, Y., Chen, H., and Bansal, M. (2019) · 2019
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Clickbait Detection
Potthast, M., Köpsel, S., Stein, B., and Hagen, M. (2016) · 2016
Cited alongside, same era.
Discriminative Predicate Path Mining for Fact Checking in Knowledge Graphs
Shi, B. and Weninger, T. (2016) · 2016
Cited alongside, same era.
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
Besold, T. R., Garcez, A. d., Bader, S., Bowman, H., Domingos, P., Hitzler, P., Kuehnberger, K.-U., Lamb, L. C., Lowd, D., Lima, P. M. V., de Penning, L., Pinkas, G., Poon, H., and Zaverucha, G. (2017) · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Conneau, A., Kiela, D., Schwenk, H., Barrault, L., and Bordes, A. (2017) · 2017
Cited alongside, same era.
Semeval-2017 task 8: Rumoureval: Determining rumour veracity and support for rumours
Derczynski, L., Bontcheva, K., Liakata, M., Procter, R., Hoi, G. W. S., and Zubiaga, A. (2017a) · 2017
Cited alongside, same era.
SemEval-2017 task 8: RumourEval: Determining rumour veracity and support for rumours
Derczynski, L., Bontcheva, K., Liakata, M., Procter, R., Wong Sak Hoi, G., and Zubiaga, A. (2017b) · 2017
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Reimers, N. and Gurevych, I. (2019) · 2019
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Unsupervised Discovery of Corroborative Paths for Fact Validation
Syed, Z. H., Röder, M., and Ngomo, A.-C. N. (2019) · 2019
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The FEVER2.0 shared task
Thorne, J., Vlachos, A., Cocarascu, O., Christodoulopoulos, C., and Mittal, A. (2019) · 2019
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Checkworthiness in automatic claim detection models: Definitions and analysis of datasets
Allein, L. and Moens, M.-F. (2020) · 2020
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Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media
Barron-Cedeno, A., Elsayed, T., Nakov, P., Martino, G., Hasanain, M., Suwaileh, R., Haouari, F., Babulkov, N., Hamdan, B., Nikolov, A., Shaar, S., and Sheikh Ali, Z. (2020) · 2020
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FactRank: Developing Automated Claim Detection for Dutch-Language Fact-Checkers
Berendt, B., Burger, P., Hautekiet, R., Jagers, J., Pleijter, A., and Aelst, P. V. (2020) · 2020
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Team Buster.ai at CheckThat! 2020: Insights And Recommendations To Improve Fact-Checking
Bouziane, M., Perrin, H., Cluzeau, A., Mardas, J., and Sadeq, A. (2020) · 2020
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Machine reasoning: Technology, dilemma and future
Duan, N., Tang, D., and Zhou, M. (2020) · 2020
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Exploring end-to-end differentiable natural logic modeling
Feng, Y., Zheng, Z., Liu, Q., Greenspan, M., and Zhu, X. (2020) · 2020
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A Machine-Learning-Based Pipeline Approach to Automated Fact-Checking
Hanselowski, A. (2020) · 2020
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bigIR at CheckThat! 2020: Multilingual BERT for Ranking Arabic Tweets by Check-worthiness
Hasanain, M. and Elsayed, T. (2020) · 2020
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Overview of checkthat! 2020i arabic: Automatic identification and verification of claims in social media
Hasanain, M., Haouari, F., Suwaileh, R., Ali, Z. S., Hamdan, B., Elsayed, T., Barrón-Cedeño, A., Martino, G. D. S., and Nakov, P. (2020) · 2020
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TrClaim-19: The first collection for Turkish check-worthy claim detection with annotator rationales
Kartal, Y. S. and Kutlu, M. (2020) · 2020
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ALBERT: A lite BERT for self-supervised learning of language representations
Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., and Soricut, R. (2020) · 2020
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UNIPI-NLE at CheckThat! 2020: Approaching Fact Checking from a Sentence Similarity Perspective Through the Lens of Transformers
Passaro, L. C., Bondielli, A., and Lenci, A. (2020) · 2020
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YAGO 4: A Reason-able Knowledge Base
Pellissier Tanon, T., Weikum, G., and Suchanek, F. (2020) · 2020
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Commonsense reasoning for natural language processing
Sap, M., Shwartz, V., Bosselut, A., Choi, Y., and Roth, D. (2020) · 2020
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Automated fact-checking of claims from Wikipedia
Sathe, A., Ather, S., Le, T. M., Perry, N., and Park, J. (2020) · 2020
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Learning explainable linguistic expressions with neural inductive logic programming for sentence classification
Sen, P., Danilevsky, M., Li, Y., Brahma, S., Boehm, M., Chiticariu, L., and Krishnamurthy, R. (2020) · 2020
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Overview of CheckThat! 2020 English: Automatic Identification and Verification of Claims in Social Media
Shaar, S., Nikolov, A., Babulkov, N., Alam, F., Barron-Cedeno, A., Elsayed, T., Hasanain, M., Suwaileh, R., and Haouari, F. (2020b) · 2020
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Overview of checkthat! 2020 english: Automatic identification and verification of claims in social media
Shaar, S., Nikolov, A., Babulkov, N., Alam, F., Barrón-Cedeno, A., Elsayed, T., Hasanain, M., Suwaileh, R., Haouari, F., Da San Martino, G., et al. (2020c) · 2020
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Fact or fiction: Verifying scientific claims
Wadden, D., Lin, S., Lo, K., Wang, L. L., van Zuylen, M., Cohan, A., and Hajishirzi, H. (2020) · 2020
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Claim check-worthiness detection as positive unlabelled learning
Wright, D. and Augenstein, I. (2020) · 2020
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FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
Aly, R., Guo, Z., Schlichtkrull, M., Thorne, J., Vlachos, A., Christodoulopoulos, C., Cocarascu, O., and Mittal, A. (2021) · 2021
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Toward automated factchecking: Developing an annotation schema and benchmark for consistent automated claim detection
Konstantinovskiy, L., Price, O., Babakar, M., and Zubiaga, A. (2021) · 2021
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The clef-2021 checkthat! lab on detecting check-worthy claims, previously fact-checked claims, and fake news
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