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 | 647 | 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 | 83 | 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 | 39 | 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 |