| 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 | 167 | 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 | 123 | 2019 |
| Factual error correction for abstractive summarization models M Cao, Y Dong, J Wu, JCK Cheung arXiv preprint arXiv:2010.08712, 2020 | 69 | 2020 |
| Multi-fact correction in abstractive text summarization Y Dong, S Wang, Z Gan, Y Cheng, JCK Cheung, J Liu arXiv preprint arXiv:2010.02443, 2020 | 58 | 2020 |
| 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 | 43 | 2018 |
| Multi-XScience: A large-scale dataset for extreme multi-document summarization of scientific articles Y Lu, Y Dong, L Charlin arXiv preprint arXiv:2010.14235, 2020 | 39 | 2020 |
| A survey on neural network-based summarization methods Y Dong arXiv preprint arXiv:1804.04589, 2018 | 30 | 2018 |
| Discourse-Aware Unsupervised Summarization of Long Scientific Documents Y Dong, A Romascanu, JCK Cheung arXiv preprint arXiv:2005.00513, 2020 | 29* | 2020 |
| Threaded ensembles of autoencoders for stream learning Y Dong, N Japkowicz Computational Intelligence 34 (1), 261-281, 2018 | 28 | 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 | 25 | 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 (01), 4360-4367, 2019 | 20 | 2019 |
| Threaded ensembles of supervised and unsupervised neural networks for stream learning Y Dong, N Japkowicz Advances in Artificial Intelligence: 29th Canadian Conference on Artificial …, 2016 | 17 | 2016 |
| Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization M Cao, Y Dong, JCK Cheung Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 16 | 2022 |
| Bringing structure into summaries: a faceted summarization dataset for long scientific documents R Meng, K Thaker, L Zhang, Y Dong, X Yuan, T Wang, D He arXiv preprint arXiv:2106.00130, 2021 | 16 | 2021 |
| Multi-task learning over graph structures P Liu, J Fu, Y Dong, X Qiu, JCK Cheung arXiv preprint arXiv:1811.10211, 2018 | 7 | 2018 |
| Inspecting the factuality of hallucinated entities in abstractive summarization M Cao, Y Dong, JCK Cheung arXiv preprint arXiv:2109.09784, 2021 | 6 | 2021 |
| Text generation with text-editing models E Malmi, Y Dong, J Mallinson, A Chuklin, J Adamek, D Mirylenka, ... arXiv preprint arXiv:2206.07043, 2022 | 5 | 2022 |
| Faithful to the document or to the world? mitigating hallucinations via entity-linked knowledge in abstractive summarization Y Dong, J Wieting, P Verga arXiv preprint arXiv:2204.13761, 2022 | 4 | 2022 |
| On-the-fly attention modulation for neural generation Y Dong, C Bhagavatula, X Lu, JD Hwang, A Bosselut, JCK Cheung, ... arXiv preprint arXiv:2101.00371, 2021 | 3 | 2021 |
| Source-Free Domain Adaptation for Question Answering with Masked Self-training M Yin, B Wang, Y Dong, C Ling arXiv preprint arXiv:2212.09563, 2022 | | 2022 |
Jackie Chi Kit CheungMcGill UniversityVerified email at cs.mcgill.ca
