| On the Sentence Embeddings from Pre-trained Language Models B Li, H Zhou, J He, M Wang, Y Yang, L Li Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 442 | 2020 |
| Towards a Unified View of Parameter-Efficient Transfer Learning J He, C Zhou, X Ma, T Berg-Kirkpatrick, G Neubig International Conference on Learning Representations (ICLR) 2022, 2022 | 314 | 2022 |
| Lagging Inference Networks and Posterior Collapse in Variational Autoencoders J He, D Spokoyny, G Neubig, T Berg-Kirkpatrick International Conference on Learning Representations (ICLR) 2019, 2019 | 291 | 2019 |
| Revisiting Self-Training for Neural Sequence Generation J He, J Gu, J Shen, MA Ranzato International Conference on Learning Representations (ICLR) 2020, 2020 | 207 | 2020 |
| Choosing Transfer Languages for Cross-Lingual Learning YH Lin, CY Chen, J Lee, Z Li, Y Zhang, M Xia, S Rijhwani, J He, Z Zhang, ... Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 179 | 2019 |
| A Probabilistic Formulation of Unsupervised Text Style Transfer J He, X Wang, G Neubig, T Berg-Kirkpatrick International Conference on Learning Representations (ICLR) 2020, 2020 | 116 | 2020 |
| StructVAE: Tree-structured latent variable models for semi-supervised semantic parsing P Yin, C Zhou, J He, G Neubig Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 111 | 2018 |
| CTRLsum: Towards generic controllable text summarization J He, W Kryściński, B McCann, N Rajani, C Xiong Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2020 | 81 | 2020 |
| Texar: A modularized, versatile, and extensible toolkit for text generation Z Hu, H Shi, B Tan, W Wang, Z Yang, T Zhao, J He, L Qin, D Wang, X Ma, ... arXiv preprint arXiv:1809.00794, 2018 | 73 | 2018 |
| A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text B Li, J He, G Neubig, T Berg-Kirkpatrick, Y Yang Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 72 | 2019 |
| Efficient Nearest Neighbor Language Models J He, G Neubig, T Berg-Kirkpatrick Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 59 | 2021 |
| Efficient correlated topic modeling with topic embedding J He, Z Hu, T Berg-Kirkpatrick, Y Huang, EP Xing Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 54 | 2017 |
| Unsupervised Learning of Syntactic Structure with Invertible Neural Projections J He, G Neubig, T Berg-Kirkpatrick Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 43 | 2018 |
| C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models Y Huang, Y Bai, Z Zhu, J Zhang, J Zhang, T Su, J Liu, C Lv, Y Zhang, J Lei, ... arXiv preprint arXiv:2305.08322, 2023 | 34* | 2023 |
| Mega: moving average equipped gated attention X Ma, C Zhou, X Kong, J He, L Gui, G Neubig, J May, L Zettlemoyer International Conference on Learning Representations (ICLR) 2023, 2023 | 28* | 2023 |
| 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 | 27 | 2022 |
| Prompt consistency for zero-shot task generalization C Zhou, J He, X Ma, T Berg-Kirkpatrick, G Neubig Findings of EMNLP 2022, 2022 | 24 | 2022 |
| Cross-Lingual Syntactic Transfer through Unsupervised Adaptation of Invertible Projections J He, Z Zhang, T Berg-Kirkpatrick, G Neubig Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 23 | 2019 |
| The source-target domain mismatch problem in machine translation J Shen, PJ Chen, M Le, J He, J Gu, M Ott, M Auli, MA Ranzato arXiv preprint arXiv:1909.13151, 2019 | 22 | 2019 |
| Learning Sparse Prototypes for Text Generation J He, T Berg-Kirkpatrick, G Neubig Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), 2020 | 16 | 2020 |
Graham NeubigCarnegie Mellon UniversityVerified email at cs.cmu.edu
