| Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks X Li, X Yin, C Li, X Hu, P Zhang, L Zhang, L Wang, H Hu, L Dong, F Wei, ... European Conference on Computer Vision (ECCV), 2020 | 929 | 2020 |
| Variational Autoencoder for Deep Learning of Images, Labels and Captions Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens, L Carin Neural Information Processing Systems (NIPS), 2016 | 732 | 2016 |
| 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 Annual Meeting of the Association for Computational Linguistics (ACL), 2018 | 358 | 2018 |
| 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, ... Annual Meeting of the Association for Computational Linguistics (ACL), 2018 | 341 | 2018 |
| Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks C Li, C Chen, D Carlson, L Carin AAAI Conference on Artificial Intelligence, 2016 | 282 | 2016 |
| Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing H Fu, C Li, X Liu, J Gao, A Celikyilmaz, L Carin NAACL, 2019 | 245 | 2019 |
| ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching C Li, H Liu, C Chen, Y Pu, L Chen, R Henao, L Carin Neural Information Processing Systems (NIPS), 2017 | 238 | 2017 |
| Focal Attention for Long-Range Interactions in Vision Transformers J Yang, C Li, P Zhang, X Dai, B Xiao, L Yuan, J Gao Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 210* | 2021 |
| Measuring the Intrinsic Dimension of Objective Landscapes C Li, H Farkhoor, R Liu, J Yosinski International Conference on Learning Representations (ICLR), 2018 | 202 | 2018 |
| Soloist: BuildingTask Bots at Scale with Transfer Learning and Machine Teaching B Peng, C Li, J Li, S Shayandeh, L Liden, J Gao Transactions of the Association for Computational Linguistics 9, 807-824, 2021 | 181* | 2021 |
| Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning R Zhang, C Li, J Zhang, C Chen, AG Wilson International Conference on Learning Representations (ICLR), 2020 | 181 | 2020 |
| Florence: A New Foundation Model for Computer Vision L Yuan, D Chen, YL Chen, N Codella, X Dai, J Gao, H Hu, X Huang, B Li, ... arXiv preprint arXiv:2111.11432, 2021 | 178 | 2021 |
| Shape retrieval of non-rigid 3D human models D Pickup, X Sun, PL Rosin, RR Martin, Z Cheng, Z Lian, M Aono, ... International Journal of Computer Vision (IJCV), 2016 | 142 | 2016 |
| Few-shot Natural Language Generation for Task-Oriented Dialog B Peng, C Zhu, C Li, X Li, J Li, M Zeng, J Gao Empirical Methods in Natural Language Processing (EMNLP), 2020 | 141 | 2020 |
| Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training W Hao, C Li, X Li, L Carin, J Gao Computer Vision and Pattern Recognition (CVPR), 2020 | 140 | 2020 |
| A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries B Li, Y Lu, C Li, A Godil, T Schreck, M Aono, M Burtscher, Q Chen, ... Computer Vision and Image Understanding (CVIU) 131, 1-27, 2015 | 140 | 2015 |
| Triangle Generative Adversarial Networks Z Gan, L Chen, W Wang, Y Pu, Y Zhang, H Liu, C Li, L Carin Neural Information Processing Systems (NIPS), 2017 | 137 | 2017 |
| Learning Generic Sentence Representations Using Convolutional Neural Networks Z Gan, Y Pu, R Henao, C Li, X He, L Carin Empirical Methods on Natural Language Processing (EMNLP), 2017 | 136* | 2017 |
| Persistence-based structural recognition C Li, M Ovsjanikov, F Chazal Computer Vision and Pattern Recognition (CVPR), 2014, 2003-2010, 2014 | 131 | 2014 |
| SHRECą14 Track: Extended Large Scale Sketch-Based 3D Shape Retrieval B Li, Y Lu, C Li, A Godil, T Schreck, M Aono, M Burtscher, H Fu, T Furuya, ... Eurographics Workshop on 3D Object Retrieval 2014 (3DOR 2014), 121-130, 2014 | 124 | 2014 |
Lawrence CarinProvost, King Abdullah University of Science & Technology (KAUST)Verified email at kaust.edu.sa
