| Simplifying Graph Convolutional Networks F Wu, T Zhang, AH Souza Jr, C Fifty, T Yu, KQ Weinberger Proceedings of the 36th International Conference on Machine Learning, 6861--6871, 2019 | 1688 | 2019 |
| BERTScore: Evaluating Text Generation with BERT T Zhang, V Kishore, F Wu, KQ Weinberger, Y Artzi Eighth International Conference on Learning Representations, 2020 | 1598 | 2020 |
| Multi-scale dense convolutional networks for efficient prediction G Huang, D Chen, T Li, F Wu, L Van Der Maaten, KQ Weinberger Sixth International Conference on Learning Representations, 2018 | 667* | 2018 |
| On fairness and calibration G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger Advances in neural information processing systems 30, 2017 | 641 | 2017 |
| Pay Less Attention with Lightweight and Dynamic Convolutions F Wu, A Fan, A Baevski, YN Dauphin, M Auli Seventh International Conference on Learning Representations, 2019 | 488 | 2019 |
| An empirical study on evaluation metrics of generative adversarial networks Q Xu, G Huang, Y Yuan, C Guo, Y Sun, F Wu, K Weinberger arXiv preprint arXiv:1806.07755, 2018 | 247 | 2018 |
| Revisiting few-sample BERT fine-tuning T Zhang, F Wu, A Katiyar, KQ Weinberger, Y Artzi arXiv preprint arXiv:2006.05987, 2020 | 213 | 2020 |
| AH d. Souza Jr, C. Fifty, T. Yu, and KQ Weinberger,“Simplifying graph convolutional networks,” F Wu, T Zhang arXiv preprint arXiv:1902.07153, 1041-4347, 2019 | 136 | 2019 |
| On feature normalization and data augmentation B Li, F Wu, SN Lim, S Belongie, KQ Weinberger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 85 | 2021 |
| Positional normalization B Li, F Wu, KQ Weinberger, S Belongie Advances in Neural Information Processing Systems 32, 2019 | 68 | 2019 |
| Effective string processing and matching for author disambiguation WS Chin, YC Juan, Y Zhuang, F Wu, HY Tung, T Yu, JP Wang, CX Chang, ... Proceedings of the 2013 KDD Cup 2013 workshop, 1-9, 2013 | 39 | 2013 |
| Attention-based quantum tomography P Cha, P Ginsparg, F Wu, J Carrasquilla, PL McMahon, EA Kim Machine Learning: Science and Technology 3 (1), 01LT01, 2021 | 30 | 2021 |
| Combining global models for parsing universal dependencies T Shi, FG Wu, X Chen, Y Cheng Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw …, 2017 | 29 | 2017 |
| Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013 CL Li, YC Su, TW Lin, CH Tsai, WC Chang, KH Huang, TM Kuo, SW Lin, ... Proceedings of the 2013 KDD Cup 2013 Workshop, 1-7, 2013 | 25 | 2013 |
| Fast reading comprehension with convnets F Wu, N Lao, J Blitzer, G Yang, K Weinberger arXiv preprint arXiv:1711.04352, 2017 | 21 | 2017 |
| Slue: New benchmark tasks for spoken language understanding evaluation on natural speech S Shon, A Pasad, F Wu, P Brusco, Y Artzi, K Livescu, KJ Han ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 18 | 2022 |
| Performance-efficiency trade-offs in unsupervised pre-training for speech recognition F Wu, K Kim, J Pan, KJ Han, KQ Weinberger, Y Artzi ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 17 | 2022 |
| Making paper reviewing robust to bid manipulation attacks R Wu, C Guo, F Wu, R Kidambi, L Van Der Maaten, K Weinberger International Conference on Machine Learning, 11240-11250, 2021 | 13 | 2021 |
| Flickr-tag prediction using multi-modal fusion and meta information YC Su, TH Chiu, GL Wu, CY Yeh, F Wu, W Hsu Proceedings of the 21st ACM international conference on Multimedia, 353-356, 2013 | 9 | 2013 |
| On the use of external data for spoken named entity recognition A Pasad, F Wu, S Shon, K Livescu, KJ Han arXiv preprint arXiv:2112.07648, 2021 | 6 | 2021 |
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
