Fetching the paper…
Reading the bibliography…
While Wikipedia has been utilized for fact-checking and claim verification to debunk misinformation and disinformation, it is essential to either improve article quality and rule out noisy articles.
G. A. Miller, “Wordnet: A lexical database for english,”
1995
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,”
1997
Earlier work this paper cites.
K. K. Schuler, “Verbnet: A broad-coverage, comprehensive verb lexicon,” Ph.D. dissertation, University of Pennsylvania, 2006
2006
Earlier work this paper cites.
R. Wang and G. Neumann, “Recognizing textual entailment using a subsequence kernel method,” in
2007
Earlier work this paper cites.
M.-C. de Marneffe, A. N. Rafferty, and C. D. Manning, “Finding contradictions in text,” in
2008
Earlier work this paper cites.
R. Wang and G. Neumann, “An divide-and-conquer strategy for recognizing textual entailment,” in
2008
Earlier work this paper cites.
E. Gabrilovich and S. Markovitch, “Wikipedia-based semantic interpretation for natural language processing,”
2009
Earlier work this paper cites.
R. Kanai, V. Walsh, and C. huei Tseng, “Subjective discriminability of invisibility: A framework for distinguishing perceptual and attentional failures of awareness,”
2010
Earlier work this paper cites.
C. C. Aggarwal and C. Zhai,
2012
Earlier work this paper cites.
M. Tsytsarau and T. Palpanas, “Survey on mining subjective data on the web,”
2012
Earlier work this paper cites.
I. Dagan, D. Roth, M. Sammons, and F. M. Zanzotto, “Recognizing textual entailment: Models and applications,”
2013
Earlier work this paper cites.
T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” in
2013
Earlier work this paper cites.
Q. Le and T. Mikolov, “Distributed representations of sentences and documents,” in
2014
Earlier work this paper cites.
Y. Kim, “Convolutional neural networks for sentence classification,” in
2014
Earlier work this paper cites.
A. Alamri and M. Stevensony, “Automatic identification of potentially contradictory claims to support systematic reviews,” in
2015
Earlier work this paper cites.
S. Weissman, S. Ayhan, J. Bradley, and J. Lin, “Identifying duplicate and contradictory information in wikipedia,” in
2015
Earlier work this paper cites.
X. Zhang, J. Zhao, and Y. LeCun, “Character-level convolutional networks for text classification,” in
2015
Earlier work this paper cites.
S. R. Bowman, G. Angeli, C. Potts, and C. D. Manning, “A large annotated corpus for learning natural language inference,” in
2015
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” in
2015
Earlier work this paper cites.
P. Lendvai, I. Augenstein, K. Bontcheva, and T. Declerck, “Monolingual social media datasets for detecting contradiction and entailment,” in
2016
Earlier work this paper cites.
P. Lendvai and U. Reichel, “Contradiction detection for rumorous claims,” in
2016
Cited alongside, same era.
A. Parikh, O. Täckström, D. Das, and J. Uszkoreit, “A decomposable attention model for natural language inference,” in
2016
Cited alongside, same era.
T. Rocktaschel, E. Grefenstette, K. M. Hermann, T. Kocisky, and P. Blunsom, “Reasoning about entailment with neural attention,” in
2016
Cited alongside, same era.
Z. Yang, D. Yang, C. Dyer, X. He, A. Smola, and E. Hovy, “Hierarchical attention networks for document classification,” in
2016
Cited alongside, same era.
S. Banerjee and P. Mitra, “Wikiwrite: Generating wikipedia articles automatically,” in
2016
Cited alongside, same era.
M. Redi, B. Fetahu, J. Morgan, and D. Taraborelli, “Citation needed: A taxonomy and algorithmic assessment of wikipedia’s verifiability,” in
2019
Later among the works it cites.
E. Dinan, S. Roller, K. Shuster, A. Fan, M. Auli, and J. Weston, “Wizard of wikipedia: Knowledge-powered conversational agents,” in
2019
Later among the works it cites.
X. Tan, Y. Cai, and C. Zhu, “Recognizing conflict opinions in aspect-level sentiment classification with dual attention networks,” in
2019
Later among the works it cites.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” in
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2017
Cited alongside, same era.
L. Li, B. Qin, and T. Liu, “Contradiction detection with contradiction-specific word embedding,”
2017
Cited alongside, same era.
R. Zanoli and S. Colombo, “A transformation-driven approach for recognizing textual entailment,”
2017
Cited alongside, same era.
K. Zhang, E. Chen, Q. Liu, C. Liu, and G. Lv, “A context-enriched neural network method for recognizing lexical entailment,” in
2017
Cited alongside, same era.
Q. Chen, X. Zhu, Z.-H. Ling, S. Wei, H. Jiang, and D. Inkpen, “Enhanced LSTM for natural language inference,” in
2017
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin, “Attention is all you need,” in
2017
Cited alongside, same era.
J. Thorne, A. Vlachos, C. Christodoulopoulos, and A. Mittal, “FEVER: a large-scale dataset for fact extraction and VERification,” in
2018
Cited alongside, same era.
2019
Later among the works it cites.
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. R. Salakhutdinov, and Q. V. Le, “Xlnet: Generalized autoregressive pretraining for language understanding,” in
2019
Later among the works it cites.
Kowsari, J. Meimandi, Heidarysafa, Mendu, Barnes, and Brown, “Text classification algorithms: A survey,”
2019
Later among the works it cites.
A. Adhikari, A. Ram, R. Tang, and J. Lin, “Rethinking complex neural network architectures for document classification,” in
2019
Later among the works it cites.
N. Reimers and I. Gurevych, “Sentence-BERT: Sentence embeddings using Siamese BERT-networks,” in
2019
Later among the works it cites.
M. Cha, W. Gao, and C.-T. Li, “Detecting fake news in social media: An asia-pacific perspective,”
2020
Later among the works it cites.
X. Zhou and R. Zafarani, “A survey of fake news: Fundamental theories, detection methods, and opportunities,”
2020
Later among the works it cites.
A. Sathe, S. Ather, T. M. Le, N. Perry, and J. Park, “Automated fact-checking of claims from Wikipedia,” in
2020
Later among the works it cites.
C.-C. Ni, K. Sum Liu, and N. Torzec, “Layered graph embedding for entity recommendation using wikipedia in the yahoo! knowledge graph,” in
2020
Later among the works it cites.
A. Asai, K. Hashimoto, H. Hajishirzi, R. Socher, and C. Xiong, “Learning to retrieve reasoning paths over wikipedia graph for question answering,” in
2020
Later among the works it cites.
I. Beltagy, M. E. Peters, and A. Cohan, “Longformer: The long-document transformer,”
2020
Later among the works it cites.
M. Trokhymovych and D. Saez-Trumper, “Wikicheck: An end-to-end open source automatic fact-checking api based on wikipedia,” in
2021
Closest in time.
S. Minaee, N. Kalchbrenner, E. Cambria, N. Nikzad, M. Chenaghlu, and J. Gao, “Deep learning–based text classification: A comprehensive review,”
2021
Closest in time.
K. Wong, M. Redi, and D. Saez-Trumper, “Wiki-reliability: A large scale dataset for content reliability on wikipedia,”
2021
Closest in time.