| Baselines and bigrams: Simple, good sentiment and topic classification SI Wang, CD Manning Proceedings of the 50th Annual Meeting of the Association for Computational …, 2012 | 1645 | 2012 |
| Transforming auto-encoders GE Hinton, A Krizhevsky, SD Wang Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011 | 1630 | 2011 |
| Dropout training as adaptive regularization S Wager, S Wang, PS Liang Advances in neural information processing systems 26, 2013 | 701 | 2013 |
| Fast dropout training SI Wang, CD Manning International Conference on Machine Learning (ICML), 118-126, 2013 | 536 | 2013 |
| Simple recurrent units for highly parallelizable recurrence T Lei, Y Zhang, SI Wang, H Dai, Y Artzi arXiv preprint arXiv:1709.02755, 2017 | 467* | 2017 |
| Data noising as smoothing in neural network language models Z Xie, SI Wang, J Li, D Lévy, A Nie, D Jurafsky, AY Ng International Conference on Learning Representations (ICLR), 2017 | 263 | 2017 |
| Incoder: A generative model for code infilling and synthesis D Fried, A Aghajanyan, J Lin, S Wang, E Wallace, F Shi, R Zhong, W Yih, ... arXiv preprint arXiv:2204.05999, 2022 | 236 | 2022 |
| Learning Language Games through Interaction SI Wang, P Liang, CD Manning Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 188 | 2016 |
| Pre-training via paraphrasing M Lewis, M Ghazvininejad, G Ghosh, A Aghajanyan, S Wang, ... Advances in Neural Information Processing Systems 33, 18470-18481, 2020 | 128 | 2020 |
| Unifiedskg: Unifying and multi-tasking structured knowledge grounding with text-to-text language models T Xie, CH Wu, P Shi, R Zhong, T Scholak, M Yasunaga, CS Wu, M Zhong, ... arXiv preprint arXiv:2201.05966, 2022 | 107 | 2022 |
| Human effort and machine learnability in computer aided translation S Green, SI Wang, J Chuang, J Heer, S Schuster, CD Manning Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014 | 81 | 2014 |
| Naturalizing a programming language via interactive learning SI Wang, S Ginn, P Liang, CD Manning Proceedings of the Association for Computational Linguistics (ACL), 2017 | 79 | 2017 |
| Grounded adaptation for zero-shot executable semantic parsing V Zhong, M Lewis, SI Wang, L Zettlemoyer arXiv preprint arXiv:2009.07396, 2020 | 71 | 2020 |
| Fast and adaptive online training of feature-rich translation models S Green, SI Wang, D Cer, CD Manning Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013 | 60 | 2013 |
| Altitude training: Strong bounds for single-layer dropout S Wager, W Fithian, S Wang, PS Liang Advances in Neural Information Processing Systems 27, 2014 | 57 | 2014 |
| DS-1000: A natural and reliable benchmark for data science code generation Y Lai, C Li, Y Wang, T Zhang, R Zhong, L Zettlemoyer, W Yih, D Fried, ... International Conference on Machine Learning, 18319-18345, 2023 | 42 | 2023 |
| Natural language to code translation with execution F Shi, D Fried, M Ghazvininejad, L Zettlemoyer, SI Wang arXiv preprint arXiv:2204.11454, 2022 | 40 | 2022 |
| Feature noising for log-linear structured prediction SI Wang, M Wang, S Wagner, P Liang, CD Manning Proceedings of the 2013 conference on empirical methods in natural language …, 2013 | 33 | 2013 |
| Bilingual lexicon induction via unsupervised bitext construction and word alignment H Shi, L Zettlemoyer, SI Wang arXiv preprint arXiv:2101.00148, 2021 | 31 | 2021 |
| Lever: Learning to verify language-to-code generation with execution A Ni, S Iyer, D Radev, V Stoyanov, W Yih, S Wang, XV Lin International Conference on Machine Learning, 26106-26128, 2023 | 28 | 2023 |
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford UniversityVerified email at stanford.edu
