| Towards unifying Hamiltonian Monte Carlo and slice sampling Y Zhang, X Wang, C Chen, R Henao, K Fan, L Carin Advances in Neural Information Processing Systems, 1741-1749, 2016 | 772* | 2016 |
| Dialogpt: Large-scale generative pre-training for conversational response generation Y Zhang, S Sun, M Galley, YC Chen, C Brockett, X Gao, J Gao, J Liu, ... arXiv preprint arXiv:1911.00536, 2019 | 331 | 2019 |
| Adversarial feature matching for text generation Y Zhang, Z Gan, K Fan, Z Chen, R Henao, D Shen, L Carin arXiv preprint arXiv:1706.03850, 2017 | 265 | 2017 |
| Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms D Shen, G Wang, W Wang, MR Min, Q Su, Y Zhang, C Li, R Henao, ... arXiv preprint arXiv:1805.09843, 2018 | 252 | 2018 |
| Joint embedding of words and labels for text classification G Wang, C Li, W Wang, Y Zhang, D Shen, X Zhang, R Henao, L Carin arXiv preprint arXiv:1805.04174, 2018 | 217 | 2018 |
| Generating informative and diverse conversational responses via adversarial information maximization Y Zhang, M Galley, J Gao, Z Gan, X Li, C Brockett, B Dolan arXiv preprint arXiv:1809.05972, 2018 | 158 | 2018 |
| Generating text via adversarial training Y Zhang, Z Gan, L Carin NIPS workshop on Adversarial Training 21, 2016 | 138 | 2016 |
| Zero-shot learning via class-conditioned deep generative models W Wang, Y Pu, VK Verma, K Fan, Y Zhang, C Chen, P Rai, L Carin Thirty-second AAAI conference on artificial intelligence, 2018 | 120 | 2018 |
| Triangle generative adversarial networks Z Gan, L Chen, W Wang, Y Pu, Y Zhang, H Liu, C Li, L Carin arXiv preprint arXiv:1709.06548, 2017 | 117 | 2017 |
| Adversarial text generation via feature-mover's distance L Chen, S Dai, C Tao, D Shen, Z Gan, H Zhang, Y Zhang, L Carin arXiv preprint arXiv:1809.06297, 2018 | 95 | 2018 |
| Deconvolutional paragraph representation learning Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin arXiv preprint arXiv:1708.04729, 2017 | 95 | 2017 |
| Composition-based classification of short metagenomic sequences elucidates the landscapes of taxonomic and functional enrichment of microorganisms J Liu, H Wang, H Yang, Y Zhang, J Wang, F Zhao, J Qi Nucleic acids research 41 (1), e3-e3, 2013 | 70 | 2013 |
| Deconvolutional latent-variable model for text sequence matching D Shen, Y Zhang, R Henao, Q Su, L Carin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 59 | 2018 |
| Jointly optimizing diversity and relevance in neural response generation X Gao, S Lee, Y Zhang, C Brockett, M Galley, J Gao, B Dolan arXiv preprint arXiv:1902.11205, 2019 | 55 | 2019 |
| Improving sequence-to-sequence learning via optimal transport L Chen, Y Zhang, R Zhang, C Tao, Z Gan, H Zhang, B Li, D Shen, C Chen, ... arXiv preprint arXiv:1901.06283, 2019 | 43 | 2019 |
| Optimus: Organizing sentences via pre-trained modeling of a latent space C Li, X Gao, Y Li, B Peng, X Li, Y Zhang, J Gao arXiv preprint arXiv:2004.04092, 2020 | 41 | 2020 |
| Towards generating long and coherent text with multi-level latent variable models D Shen, A Celikyilmaz, Y Zhang, L Chen, X Wang, J Gao, L Carin arXiv preprint arXiv:1902.00154, 2019 | 31 | 2019 |
| Jointgan: Multi-domain joint distribution learning with generative adversarial nets Y Pu, S Dai, Z Gan, W Wang, G Wang, Y Zhang, R Henao, LC Duke International Conference on Machine Learning, 4151-4160, 2018 | 31 | 2018 |
| POINTER: Constrained progressive text generation via insertion-based generative pre-training Y Zhang, G Wang, C Li, Z Gan, C Brockett, B Dolan arXiv preprint arXiv:2005.00558, 2020 | 28 | 2020 |
| Structuring latent spaces for stylized response generation X Gao, Y Zhang, S Lee, M Galley, C Brockett, J Gao, B Dolan arXiv preprint arXiv:1909.05361, 2019 | 23 | 2019 |
Lawrence CarinProvost, King Abdullah University of Science & Technology (KAUST)Verifierad e-postadress på kaust.edu.sa
