| How can we know what language models know? Z Jiang, FF Xu, J Araki, G Neubig Transactions of the Association for Computational Linguistics 8, 423-438, 2020 | 1462 | 2020 |
| A systematic evaluation of large language models of code FF Xu, U Alon, G Neubig, VJ Hellendoorn Proceedings of the 6th ACM SIGPLAN International Symposium on Machine …, 2022 | 691 | 2022 |
| Empower sequence labeling with task-aware neural language model L Liu, J Shang, X Ren, F Xu, H Gui, J Peng, J Han Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 454 | 2018 |
| Active retrieval augmented generation Z Jiang, FF Xu, L Gao, Z Sun, Q Liu, J Dwivedi-Yu, Y Yang, J Callan, ... arXiv preprint arXiv:2305.06983, 2023 | 418 | 2023 |
| Webarena: A realistic web environment for building autonomous agents S Zhou, FF Xu, H Zhu, X Zhou, R Lo, A Sridhar, X Cheng, T Ou, Y Bisk, ... arXiv preprint arXiv:2307.13854, 2023 | 256 | 2023 |
| In-ide code generation from natural language: Promise and challenges FF Xu, B Vasilescu, G Neubig ACM Transactions on Software Engineering and Methodology (TOSEM) 31 (2), 1-47, 2022 | 172 | 2022 |
| Multi-channel bilstm-crf model for emerging named entity recognition in social media BY Lin, FF Xu, Z Luo, K Zhu Proceedings of the 3rd Workshop on Noisy User-generated Text, 160-165, 2017 | 167 | 2017 |
| Docprompting: Generating code by retrieving the docs S Zhou, U Alon, FF Xu, Z Wang, Z Jiang, G Neubig arXiv preprint arXiv:2207.05987, 2022 | 149* | 2022 |
| 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 | 96 | 2020 |
| Neuro-symbolic language modeling with automaton-augmented retrieval U Alon, F Xu, J He, S Sengupta, D Roth, G Neubig International Conference on Machine Learning, 468-485, 2022 | 64 | 2022 |
| Higitclass: Keyword-driven hierarchical classification of github repositories Y Zhang, FF Xu, S Li, Y Meng, X Wang, Q Li, J Han 2019 IEEE International Conference on Data Mining (ICDM), 876-885, 2019 | 58 | 2019 |
| AlpacaTag: An active learning-based crowd annotation framework for sequence tagging BY Lin, DH Lee, FF Xu, O Lan, X Ren Proceedings of the 57th Conference of the Association for Computational …, 2019 | 46 | 2019 |
| Mconala: a benchmark for code generation from multiple natural languages Z Wang, G Cuenca, S Zhou, FF Xu, G Neubig arXiv preprint arXiv:2203.08388, 2022 | 43 | 2022 |
| Statelens: A reverse engineering solution for making existing dynamic touchscreens accessible A Guo, J Kong, M Rivera, FF Xu, JP Bigham Proceedings of the 32nd Annual ACM Symposium on User Interface Software and …, 2019 | 40 | 2019 |
| Mining cross-cultural differences and similarities in social media BY Lin, FF Xu, K Zhu, S Hwang Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 36 | 2018 |
| Data-to-text generation with style imitation S Lin, W Wang, Z Yang, X Liang, FF Xu, E Xing, Z Hu arXiv preprint arXiv:1901.09501, 2019 | 35* | 2019 |
| Opendevin: An open platform for ai software developers as generalist agents X Wang, B Li, Y Song, FF Xu, X Tang, M Zhuge, J Pan, Y Song, B Li, ... arXiv preprint arXiv:2407.16741, 2024 | 33 | 2024 |
| Minimally supervised categorization of text with metadata Y Zhang, Y Meng, J Huang, FF Xu, X Wang, J Han Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 33 | 2020 |
| Learning structural edits via incremental tree transformations Z Yao, FF Xu, P Yin, H Sun, G Neubig arXiv preprint arXiv:2101.12087, 2021 | 31 | 2021 |
| Automatic extraction of commonsense locatednear knowledge FF Xu, BY Lin, KQ Zhu arXiv preprint arXiv:1711.04204, 2017 | 30 | 2017 |
Graham NeubigCarnegie Mellon University, All Hands AIcs.cmu.edu의 이메일 확인됨