FEVER: a large-scale dataset for fact extraction and VERification J Thorne, A Vlachos, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1803.05355, 2018 | 1407 | 2018 |
A massively parallel corpus: the Bible in 100 languages C Christodouloupoulos, M Steedman Language Resources and Evaluation 49 (2), 375-395, 2014 | 269 | 2014 |
The fact extraction and VERification (FEVER) shared task J Thorne, A Vlachos, O Cocarascu, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1811.10971, 2018 | 220 | 2018 |
Two decades of unsupervised POS induction: How far have we come? C Christodoulopoulos, S Goldwater, M Steedman Proceedings of the 2010 Conference on Empirical Methods in Natural Language …, 2010 | 179 | 2010 |
Feverous: Fact extraction and verification over unstructured and structured information R Aly, Z Guo, M Schlichtkrull, J Thorne, A Vlachos, C Christodoulopoulos, ... arXiv preprint arXiv:2106.05707, 2021 | 168 | 2021 |
A group formation tool in an e-learning context CE Christodoulopoulos, KA Papanikolaou 19th IEEE international conference on tools with artificial intelligence …, 2007 | 121 | 2007 |
The FEVER2. 0 shared task J Thorne, A Vlachos, O Cocarascu, C Christodoulopoulos, A Mittal Proceedings of the second workshop on Fact Extraction and VERification …, 2019 | 102 | 2019 |
Refined: An efficient zero-shot-capable approach to end-to-end entity linking T Ayoola, S Tyagi, J Fisher, C Christodoulopoulos, A Pierleoni arXiv preprint arXiv:2207.04108, 2022 | 63 | 2022 |
Debiasing knowledge graph embeddings J Fisher, A Mittal, D Palfrey, C Christodoulopoulos Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 54 | 2020 |
Generating token-level explanations for natural language inference J Thorne, A Vlachos, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1904.10717, 2019 | 53 | 2019 |
State-of-the-art generalisation research in NLP: a taxonomy and review D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ... arXiv preprint arXiv:2210.03050, 2022 | 52 | 2022 |
Measuring social bias in knowledge graph embeddings J Fisher, D Palfrey, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1912.02761, 2019 | 45 | 2019 |
A Bayesian Mixture Model for Part-of-Speech Induction Using Multiple Features C Christodoulopoulos, S Goldwater, M Steedman Proceedings of the 2011 Conference on Empirical Methods in Natural Language …, 2011 | 44 | 2011 |
Evaluating adversarial attacks against multiple fact verification systems J Thorne, A Vlachos, C Christodoulopoulos, A Mittal Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 41 | 2019 |
Investigation of group formation using low complexity algorithms CE Christodoulopoulos, K Papanikolaou Proc. of PING Workshop, 57-60, 2007 | 36 | 2007 |
Edison: Feature extraction for nlp, simplified M Sammons, C Christodoulopoulos, P Kordjamshidi, D Khashabi, ... Proceedings of the Tenth International Conference on Language Resources and …, 2016 | 28 | 2016 |
A taxonomy and review of generalization research in NLP D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ... Nature Machine Intelligence 5 (10), 1161-1174, 2023 | 27 | 2023 |
Revisiting the evaluation for cross document event coreference S Upadhyay, N Gupta, C Christodoulopoulos, D Roth Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 22 | 2016 |
Cogcompnlp: Your swiss army knife for nlp D Khashabi, M Sammons, B Zhou, T Redman, C Christodoulopoulos, ... Proceedings of the Eleventh International Conference on Language Resources …, 2018 | 21 | 2018 |
Subhro Roy D Khashabi, M Sammons, B Zhou, T Redman, C Christodoulopoulos, ... Stephen Mayhew, Zhili Feng, John Wieting, Xiaodong Yu, Yangqiu Song …, 2018 | 17 | 2018 |