| Controlling length in abstractive summarization using a convolutional neural network Y Liu, Z Luo, K Zhu Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 72 | 2018 |
| Multi-turn response selection using dialogue dependency relations Q Jia, Y Liu, S Ren, KQ Zhu, H Tang arXiv preprint arXiv:2010.01502, 2020 | 30 | 2020 |
| Length control in abstractive summarization by pretraining information selection Y Liu, Q Jia, K Zhu Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 13 | 2022 |
| Keyword-aware abstractive summarization by extracting set-level intermediate summaries Y Liu, Q Jia, K Zhu Proceedings of the Web Conference 2021, 3042-3054, 2021 | 11 | 2021 |
| Reference-free summarization evaluation via semantic correlation and compression ratio Y Liu, Q Jia, K Zhu Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 7 | 2022 |
| Post-training dialogue summarization using pseudo-paraphrasing Q Jia, Y Liu, H Tang, KQ Zhu arXiv preprint arXiv:2204.13498, 2022 | 3 | 2022 |
| Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions Q Jia, Y Liu, S Ren, KQ Zhu ACM Computing Surveys, 2022 | 3 | 2022 |
| Reducing repetition in convolutional abstractive summarization Y Liu, X Chen, X Luo, KQ Zhu Natural Language Engineering 29 (1), 81-109, 2023 | 2 | 2023 |
| Opinion Summarization by Weak-Supervision from Mix-structured Data Y Liu, Q Jia, K Zhu Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | | 2022 |
| In-sample Curriculum Learning by Sequence Completion for Natural Language Generation Q Jia, Y Liu, H Tang, KQ Zhu arXiv preprint arXiv:2211.11297, 2022 | | 2022 |
Kenny Q. ZhuUniversity of Texas at ArlingtonVahvistettu sähköpostiosoite verkkotunnuksessa uta.edu
