| On the Sentence Embeddings from Pre-trained Language Models B Li, H Zhou, J He, M Wang, Y Yang, L Li arXiv preprint arXiv:2011.05864, 2020 | 687 | 2020 |
| A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text B Li, J He, G Neubig, T Berg-Kirkpatrick, Y Yang Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019 | 85 | 2019 |
| An Adversarial Approach to High-Quality, Sentiment-Controlled Neural Dialogue Generation X Kong, B Li, G Neubig, E Hovy, Y Yang AAAI 2019 Workshop on Reasoning and Learning for Human-Machine Dialogues …, 2019 | 42 | 2019 |
| Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data G Lai, B Li, G Zheng, Y Yang ICML 2018 Workshop on Theoretical Foundations and Applications of Deep …, 2018 | 29 | 2018 |
| On the Sentence Embeddings from BERT for Semantic Textual Similarity B Li, H Zhou, J He, M Wang, Y Yang, L Li Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 28 | 2020 |
| Follow your path: a progressive method for knowledge distillation W Shi, Y Song, H Zhou, B Li, L Li Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 22 | 2021 |
| Proximal Knowledge Teaching for Neural Networks W Shi, Y Song, H Zhou, B Li, L Li ECML-PKDD 2021, 2021 | | 2021 |
| UNMAT: Visual comparison and exploration of uncertainty in large graph sampling T Tang, S Wang, Y Li, B Li, Y Wu Journal of Visual Languages & Computing 41, 71-78, 2017 | | 2017 |
Yiming YangProfessor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
