| Banditsum: Extractive summarization as a contextual bandit Y Dong, Y Shen, E Crawford, H van Hoof, JCK Cheung Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 22 | 2018 |
| Threaded ensembles of supervised and unsupervised neural networks for stream learning Y Dong, N Japkowicz Canadian conference on artificial intelligence, 304-315, 2016 | 10 | 2016 |
| A survey on neural network-based summarization methods Y Dong arXiv preprint arXiv:1804.04589, 2018 | 9 | 2018 |
| A hierarchical neural attention-based text classifier K Sinha, Y Dong, JCK Cheung, D Ruths Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 9 | 2018 |
| Threaded ensembles of autoencoders for stream learning Y Dong, N Japkowicz Computational Intelligence 34 (1), 261-281, 2018 | 7 | 2018 |
| EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing Y Dong, Z Li, M Rezagholizadeh, JCK Cheung Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 5 | 2019 |
| Learning multi-task communication with message passing for sequence learning P Liu, J Fu, Y Dong, X Qiu, JCK Cheung Proceedings of the AAAI Conference on Artificial Intelligence 33, 4360-4367, 2019 | 3 | 2019 |
| Multi-task learning over graph structures P Liu, J Fu, Y Dong, X Qiu, JCK Cheung arXiv preprint arXiv:1811.10211, 2018 | 3 | 2018 |
| Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses M Grenander, Y Dong, JCK Cheung, A Louis Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 1 | 2019 |
| Higher Order Neural Networks and Neural Networks for Stream Learning Y Dong Carleton University, 2017 | | 2017 |
