| RoBERTa: A Robustly Optimized BERT Pretraining Approach Y Liu, M Ott, N Goyal, J Du, M Joshi, D Chen, O Levy, M Lewis, ... arXiv preprint arXiv:1907.11692, 2019 | 13678* | 2019 |
| Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension M Lewis, Y Liu, N Goyal, M Ghazvininejad, A Mohamed, O Levy, ... arXiv preprint arXiv:1910.13461, 2019 | 4670 | 2019 |
| Unsupervised Cross-lingual Representation Learning at Scale A Conneau, K Khandelwal, N Goyal, V Chaudhary, G Wenzek, F Guzmán, ... arXiv preprint arXiv:1911.02116, 2019 | 3038 | 2019 |
| SemEval-2016 task 4: Sentiment analysis in Twitter P Nakov, A Ritter, S Rosenthal, F Sebastiani, V Stoyanov Proceedings of the 10th International Workshop on Semantic Evaluation …, 2016 | 1235 | 2016 |
| SemEval-2017 task 4: Sentiment analysis in Twitter S Rosenthal, N Farra, P Nakov Proceedings of the 11th International Workshop on Semantic Evaluation …, 2017 | 1231 | 2017 |
| XNLI: Evaluating Cross-lingual Sentence Representations A Conneau, G Lample, R Rinott, A Williams, SR Bowman, H Schwenk, ... arXiv preprint arXiv:1809.05053, 2018 | 835 | 2018 |
| Semeval-2015 task 10: Sentiment analysis in twitter S Rosenthal, P Nakov, S Kiritchenko, S Mohammad, A Ritter, V Stoyanov Proceedings of the 9th international workshop on semantic evaluation …, 2015 | 460 | 2015 |
| System and method for automatically summarizing fine-grained opinions in digital text C Cardie, V Stoyanov, Y Choi, E Breck US Patent 8,280,885, 2012 | 412 | 2012 |
| Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning B Gunel, J Du, A Conneau, V Stoyanov arXiv preprint arXiv:2011.01403, 2020 | 225 | 2020 |
| Conundrums in noun phrase coreference resolution: Making sense of the state-of-the-art V Stoyanov, N Gilbert, C Cardie, E Riloff Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009 | 198 | 2009 |
| Topic identification for fine-grained opinion analysis V Stoyanov, C Cardie Proceedings of the 22nd International Conference on Computational …, 2008 | 188 | 2008 |
| Multi-perspective question answering using the OpQA corpus V Stoyanov, C Cardie, J Wiebe Proceedings of Human Language Technology Conference and Conference on …, 2005 | 170 | 2005 |
| Emerging Cross-lingual Structure in Pretrained Language Models A Conneau, S Wu, H Li, L Zettlemoyer, V Stoyanov Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 169* | 2020 |
| Pretrained encyclopedia: Weakly supervised knowledge-pretrained language model W Xiong, J Du, W Wang, V Stoyanov ICLR, 2019 | 154 | 2019 |
| Empirical risk minimization of graphical model parameters given approximate inference, decoding, and model structure V Stoyanov, A Ropson, J Eisner Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 150 | 2011 |
| Coreference resolution with reconcile V Stoyanov, C Cardie, N Gilbert, E Riloff, D Buttler, D Hysom Proceedings of the ACL 2010 Conference Short Papers, 156-161, 2010 | 119 | 2010 |
| QA with Attitude: Exploiting Opinion Type Analysis for Improving Question Answering in On-line Discussions and the News. S Somasundaran, T Wilson, J Wiebe, V Stoyanov ICWSM, 2007 | 105 | 2007 |
| A multi-lingual multi-task architecture for low-resource sequence labeling Y Lin, S Yang, V Stoyanov, H Ji Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 104 | 2018 |
| Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts P Nakov, S Rosenthal, S Kiritchenko, SM Mohammad, Z Kozareva, ... Language Resources and Evaluation 50, 35-65, 2016 | 104 | 2016 |
| Self-training improves pre-training for natural language understanding J Du, E Grave, B Gunel, V Chaudhary, O Celebi, M Auli, V Stoyanov, ... arXiv preprint arXiv:2010.02194, 2020 | 100 | 2020 |
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