| A syntactic neural model for general-purpose code generation P Yin, G Neubig ACL 2017, 2017 | 581 | 2017 |
| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311, 2022 | 537 | 2022 |
| Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017 | 421* | 2017 |
| TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data P Yin, G Neubig, W Yih, S Riedel ACL 2020, 2020 | 277 | 2020 |
| Learning to mine aligned code and natural language pairs from stack overflow P Yin, B Deng, E Chen, B Vasilescu, G Neubig 2018 IEEE/ACM 15th International Conference on Mining Software Repositories …, 2018 | 174 | 2018 |
| Tranx: A transition-based neural abstract syntax parser for semantic parsing and code generation P Yin, G Neubig EMNLP 2018 (Demo Track), 2018 | 157 | 2018 |
| Neural enquirer: Learning to query tables with natural language P Yin, Z Lu, H Li, B Kao arXiv preprint arXiv:1512.00965, 2015 | 111 | 2015 |
| StructVAE: Tree-structured latent variable models for semi-supervised semantic parsing P Yin, C Zhou, J He, G Neubig ACL 2018, 2018 | 107 | 2018 |
| Learning to represent edits P Yin, G Neubig, M Allamanis, M Brockschmidt, AL Gaunt ICLR 2019, 2018 | 99 | 2018 |
| Answering questions with complex semantic constraints on open knowledge bases P Yin, N Duan, B Kao, J Bao, M Zhou Proceedings of the 24th acm international on conference on information and …, 2015 | 84 | 2015 |
| Retrieval-based neural code generation SA Hayati, R Olivier, P Avvaru, P Yin, A Tomasic, G Neubig arXiv preprint arXiv:1808.10025, 2018 | 75 | 2018 |
| Dire: A neural approach to decompiled identifier naming J Lacomis, P Yin, E Schwartz, M Allamanis, C Le Goues, G Neubig, ... 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 70 | 2019 |
| Incorporating external knowledge through pre-training for natural language to code generation FF Xu, Z Jiang, P Yin, B Vasilescu, G Neubig arXiv preprint arXiv:2004.09015, 2020 | 58 | 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 | 54 | 2022 |
| Reranking for neural semantic parsing P Yin, G Neubig Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 52 | 2019 |
| A tree-based decoder for neural machine translation X Wang, H Pham, P Yin, G Neubig arXiv preprint arXiv:1808.09374, 2018 | 46 | 2018 |
| Lingpeng Kong, Rui Zhang, Noah A T Xie, CH Wu, P Shi, R Zhong, T Scholak, M Yasunaga, CS Wu, M Zhong, ... Smith, Luke Zettlemoyer, and Tao Yu, 2022 | 31 | 2022 |
| Compositional generalization for neural semantic parsing via span-level supervised attention P Yin, H Fang, G Neubig, A Pauls, EA Platanios, Y Su, S Thomson, ... Association for Computational Linguistics (ACL), 2021 | 30 | 2021 |
| Towards practical open knowledge base canonicalization TH Wu, Z Wu, B Kao, P Yin Proceedings of the 27th ACM International Conference on Information and …, 2018 | 26 | 2018 |
| Learning structural edits via incremental tree transformations Z Yao, FF Xu, P Yin, H Sun, G Neubig arXiv preprint arXiv:2101.12087, 2021 | 19 | 2021 |
Graham NeubigCarnegie Mellon University, Inspired CognitionVerified email at cs.cmu.edu
