| Character-level convolutional networks for text classification X Zhang, J Zhao, Y LeCun Advances in neural information processing systems 28, 2015 | 7608 | 2015 |
| End to end learning for self-driving cars A (All equal contribution), M Bojarski, D Del Testa, D Dworakowski, ... NIPS 2016 Symposium, 2016 | 5746* | 2016 |
| BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer F Sun, J Liu, J Wu, C Pei, X Lin, W Ou, P Jiang Proceedings of the 28th ACM international conference on information and …, 2019 | 2422 | 2019 |
| Energy-based generative adversarial network J Zhao, M Mathieu, Y LeCun ICLR 2017, 2016 | 1650 | 2016 |
| Deep graph library: Towards efficient and scalable deep learning on graphs M Wang, L Yu, D Zheng, Q Gan, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ... arXiv preprint arXiv:1909.01315, 2019 | 896 | 2019 |
| Disentangling factors of variation in deep representation using adversarial training MF Mathieu, J Zhao, A Ramesh, P Sprechmann, Y LeCun Advances in Neural Information Processing Systems, 5041-5049, 2016 | 570 | 2016 |
| Levenshtein transformer J Gu, C Wang, J Zhao Advances in neural information processing systems 32, 2019 | 411 | 2019 |
| Adversarially Regularized Autoencoders J Zhao, Y Kim, K Zhang, AM Rush, Y LeCun ICML 2018, 2017 | 377 | 2017 |
| Stacked What-Where Auto-encoders YLC Junbo Zhao, Michael Mathieu, Ross Goroshin ICLR 2016, 2016 | 365* | 2016 |
| Pico+: Contrastive label disambiguation for robust partial label learning H Wang, R Xiao, Y Li, L Feng, G Niu, G Chen, J Zhao arXiv preprint arXiv:2201.08984, 2022 | 168 | 2022 |
| Identification of potent antimicrobial peptides via a machine-learning pipeline that mines the entire space of peptide sequences J Huang, Y Xu, Y Xue, Y Huang, X Li, X Chen, Y Xu, D Zhang, P Zhang, ... Nature Biomedical Engineering 7 (6), 797-810, 2023 | 125 | 2023 |
| A critical look at the current train/test split in machine learning J Tan, J Yang, S Wu, G Chen, J Zhao arXiv preprint arXiv:2106.04525, 2021 | 77 | 2021 |
| Chatdb: Augmenting llms with databases as their symbolic memory C Hu, J Fu, C Du, S Luo, J Zhao, H Zhao arXiv preprint arXiv:2306.03901, 2023 | 75 | 2023 |
| Prompt as triggers for backdoor attack: Examining the vulnerability in language models S Zhao, J Wen, LA Tuan, J Zhao, J Fu arXiv preprint arXiv:2305.01219, 2023 | 75 | 2023 |
| Adversarially regularized autoencoders for generating discrete structures Y Kim, K Zhang, AM Rush, Y LeCun arXiv preprint arXiv:1706.04223 2, 12, 2017 | 73 | 2017 |
| Glomo: Unsupervised learning of transferable relational graphs Z Yang, J Zhao, B Dhingra, K He, WW Cohen, RR Salakhutdinov, ... Advances in Neural Information Processing Systems 31, 2018 | 69* | 2018 |
| Pianotree vae: Structured representation learning for polyphonic music Z Wang, Y Zhang, Y Zhang, J Jiang, R Yang, J Zhao, G Xia arXiv preprint arXiv:2008.07118, 2020 | 63 | 2020 |
| Promix: Combating label noise via maximizing clean sample utility R Xiao, Y Dong, H Wang, L Feng, R Wu, G Chen, J Zhao arXiv preprint arXiv:2207.10276, 2022 | 58 | 2022 |
| On llms-driven synthetic data generation, curation, and evaluation: A survey L Long, R Wang, R Xiao, J Zhao, X Ding, G Chen, H Wang arXiv preprint arXiv:2406.15126, 2024 | 56 | 2024 |
| Maybe only 0.5% data is needed: A preliminary exploration of low training data instruction tuning H Chen, Y Zhang, Q Zhang, H Yang, X Hu, X Ma, Y Yanggong, J Zhao arXiv preprint arXiv:2305.09246, 2023 | 46 | 2023 |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York University在 cs.nyu.edu 的电子邮件经过验证