| Simlex-999: Evaluating semantic models with (genuine) similarity estimation F Hill, R Reichart, A Korhonen Computational Linguistics 41 (4), 665-695, 2015 | 1407 | 2015 |
| Modeling the detection of textual cyberbullying K Dinakar, R Reichart, H Lieberman Proceedings of the International AAAI Conference on Web and Social Media 5 …, 2011 | 644 | 2011 |
| The hitchhiker’s guide to testing statistical significance in natural language processing R Dror, G Baumer, S Shlomov, R Reichart Proceedings of the 56th annual meeting of the association for computational …, 2018 | 315 | 2018 |
| SimVerb-3500: A large-scale evaluation set of verb similarity D Gerz, I Vulić, F Hill, R Reichart, A Korhonen Proceedings of EMNLP 2016, 2016 | 267 | 2016 |
| Semantic specialisation of distributional word vector spaces using monolingual and cross-lingual constraints N Mrkšić, I Vulić, DÓ Séaghdha, I Leviant, R Reichart, M Gašić, ... Transactions of the Association for Computational Linguistics 5, 309--324, 2017 | 231 | 2017 |
| Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction. R Schwartz, R Reichart, A Rappoport CoNLL 2015, 258-267, 2015 | 135 | 2015 |
| Thinking ahead: spontaneous prediction in context as a keystone of language in humans and machines A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... BioRxiv, 2020.12. 02.403477, 2020 | 133* | 2020 |
| Self-training for enhancement and domain adaptation of statistical parsers trained on small datasets R Reichart, A Rappoport Proceedings of the 45th Annual Meeting of the Association of Computational …, 2007 | 119 | 2007 |
| Multi-task active learning for linguistic annotations R Reichart, K Tomanek, U Hahn, A Rappoport Proceedings of ACL-08: HLT, 861-869, 2008 | 112 | 2008 |
| The Turker blues: Hidden factors behind increased depression rates among Amazon’s Mechanical Turkers Y Ophir, I Sisso, CSC Asterhan, R Tikochinski, R Reichart Clinical Psychological Science 8 (1), 65-83, 2020 | 109 | 2020 |
| Modeling language variation and universals: A survey on typological linguistics for natural language processing EM Ponti, H O’horan, Y Berzak, I Vulić, R Reichart, T Poibeau, E Shutova, ... Computational Linguistics 45 (3), 559-601, 2019 | 109 | 2019 |
| Pivot based language modeling for improved neural domain adaptation Y Ziser, R Reichart Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 105 | 2018 |
| Neural structural correspondence learning for domain adaptation Y Ziser, R Reichart Proceedings of the 21st Conference on Computational Natural Language …, 2016 | 104 | 2016 |
| Separated by an Un-common Language: Towards Judgment Language Informed Vector Space Modeling I Leviant, R Reichart arXiv preprint arxiv:1508.00106, 2015 | 103* | 2015 |
| An Unsupervised Model for Instance Level Subcategorization Acquisition. S Baker, R Reichart, A Korhonen EMNLP, 278-289, 2014 | 95 | 2014 |
| Causal inference in natural language processing: Estimation, prediction, interpretation and beyond A Feder, KA Keith, E Manzoor, R Pryzant, D Sridhar, Z Wood-Doughty, ... Transactions of the Association for Computational Linguistics 10, 1138-1158, 2022 | 94 | 2022 |
| Causalm: Causal model explanation through counterfactual language models A Feder, N Oved, U Shalit, R Reichart Computational Linguistics 47 (2), 333-386, 2021 | 83 | 2021 |
| Confidence driven unsupervised semantic parsing D Goldwasser, R Reichart, J Clarke, D Roth Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011 | 83 | 2011 |
| Do we really need fully unsupervised cross-lingual embeddings? I Vulić, G Glavaš, R Reichart, A Korhonen arXiv preprint arXiv:1909.01638, 2019 | 76 | 2019 |
| Deep dominance-how to properly compare deep neural models R Dror, S Shlomov, R Reichart Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 73 | 2019 |
Anna KorhonenProfessor, Computer Science and Linguistics, University of CambridgeVerified email at cam.ac.uk
