What Makes Good In-Context Examples for GPT- J Liu, D Shen, Y Zhang, B Dolan, L Carin, W Chen
arXiv preprint arXiv:2101.06804, 2021
1201 2021 Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation X Wang, Q Huang, A Celikyilmaz, J Gao, D Shen, YF Wang, WY Wang, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
605 2019 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
536 2018 Adversarial feature matching for text generation Y Zhang, Z Gan, K Fan, Z Chen, R Henao, D Shen, L Carin
International conference on machine learning, 4006-4015, 2017
473 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
451 2018 Video generation from text Y Li, M Min, D Shen, D Carlson, L Carin
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
289 2018 Understanding the solvent-assisted crystallization mechanism inherent in efficient organic–inorganic halide perovskite solar cells D Shen, X Yu, X Cai, M Peng, Y Ma, X Su, L Xiao, D Zou
Journal of Materials Chemistry A 2 (48), 20454-20461, 2014
180 2014 Adversarial text generation via feature-mover's distance L Chen, S Dai, C Tao, H Zhang, Z Gan, D Shen, Y Zhang, G Wang, ...
Advances in neural information processing systems 31, 2018
170 2018 Topic-guided variational autoencoders for text generation W Wang, Z Gan, H Xu, R Zhang, G Wang, D Shen, C Chen, L Carin
arXiv preprint arXiv:1903.07137, 2019
156 2019 A simple but tough-to-beat data augmentation approach for natural language understanding and generation D Shen, M Zheng, Y Shen, Y Qu, W Chen
arXiv preprint arXiv:2009.13818, 2020
146 2020 Deconvolutional paragraph representation learning Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin
Advances in Neural Information Processing Systems 30, 2017
119 2017 Improving disentangled text representation learning with information-theoretic guidance P Cheng, MR Min, D Shen, C Malon, Y Zhang, Y Li, L Carin
arXiv preprint arXiv:2006.00693, 2020
105 2020 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
104 2019 Coda: Contrast-enhanced and diversity-promoting data augmentation for natural language understanding Y Qu, D Shen, Y Shen, S Sajeev, J Han, W Chen
arXiv preprint arXiv:2010.08670, 2020
95 2020 Topic compositional neural language model W Wang, Z Gan, W Wang, D Shen, J Huang, W Ping, S Satheesh, L Carin
International Conference on Artificial Intelligence and Statistics, 356-365, 2018
93 2018 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
88 2018 Mixkd: Towards efficient distillation of large-scale language models KJ Liang, W Hao, D Shen, Y Zhou, W Chen, C Chen, L Carin
arXiv preprint arXiv:2011.00593, 2020
74 2020 Nash: Toward end-to-end neural architecture for generative semantic hashing D Shen, Q Su, P Chapfuwa, W Wang, G Wang, L Carin, R Henao
arXiv preprint arXiv:1805.05361, 2018
69 2018 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
67 2019 Syntax-infused variational autoencoder for text generation X Zhang, Y Yang, S Yuan, D Shen, L Carin
arXiv preprint arXiv:1906.02181, 2019
65 2019 
Lawrence CarinDuke UniversityПодтвержден адрес электронной почты в домене duke.edu
