| FEVER: a large-scale dataset for fact extraction and VERification J Thorne, A Vlachos, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1803.05355, 2018 | 1725 | 2018 |
| A massively parallel corpus: the Bible in 100 languages C Christodouloupoulos, M Steedman Language Resources and Evaluation 49 (2), 375-395, 2014 | 292 | 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 | 249 | 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 | 185 | 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 | 174 | 2021 |
| A group formation tool in an e-learning context CE Christodoulopoulos, KA Papanikolaou 19th IEEE international conference on tools with artificial intelligence …, 2007 | 126 | 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 | 124 | 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 | 93 | 2022 |
| Measuring social bias in knowledge graph embeddings J Fisher, D Palfrey, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1912.02761, 2019 | 91 | 2019 |
| The fact extraction and VERification over unstructured and structured information (FEVEROUS) shared task R Aly, Z Guo, MS Schlichtkrull, J Thorne, A Vlachos, ... Proceedings of the Fourth Workshop on Fact Extraction and VERification …, 2021 | 83 | 2021 |
| 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 | 63 | 2023 |
| 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 | 61 | 2022 |
| Generating token-level explanations for natural language inference J Thorne, A Vlachos, C Christodoulopoulos, A Mittal arXiv preprint arXiv:1904.10717, 2019 | 60 | 2019 |
| 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 | 44 | 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 |
| Investigation of group formation using low complexity algorithms CE Christodoulopoulos, K Papanikolaou Proc. of PING Workshop, 57-60, 2007 | 38 | 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 | 32 | 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 | 22 | 2018 |
| 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 |
| Hidden biases in unreliable news detection datasets X Zhou, H Elfardy, C Christodoulopoulos, T Butler, M Bansal arXiv preprint arXiv:2104.10130, 2021 | 17 | 2021 |
Arpit MittalFacebookVerified email at robots.ox.ac.uk