| A knowledge-enhanced pretraining model for commonsense story generation J Guan, F Huang, Z Zhao, X Zhu, M Huang Transactions of the Association for Computational Linguistics 8, 93-108, 2020 | 175 | 2020 |
| Story ending generation with incremental encoding and commonsense knowledge J Guan, Y Wang, M Huang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6473-6480, 2019 | 142 | 2019 |
| Generating informative responses with controlled sentence function P Ke, J Guan, M Huang, X Zhu Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 76 | 2018 |
| CPM: A large-scale generative Chinese pre-trained language model Z Zhang, X Han, H Zhou, P Ke, Y Gu, D Ye, Y Qin, Y Su, H Ji, J Guan, F Qi, ... AI Open 2, 93-99, 2021 | 68 | 2021 |
| A model-based reinforcement learning with adversarial training for online recommendation X Bai, J Guan, H Wang Advances in Neural Information Processing Systems 32, 2019 | 68 | 2019 |
| Cpm-2: Large-scale cost-effective pre-trained language models Z Zhang, Y Gu, X Han, S Chen, C Xiao, Z Sun, Y Yao, F Qi, J Guan, P Ke, ... AI Open 2, 216-224, 2021 | 49 | 2021 |
| Union: An unreferenced metric for evaluating open-ended story generation J Guan, M Huang arXiv preprint arXiv:2009.07602, 2020 | 38 | 2020 |
| Long text generation by modeling sentence-level and discourse-level coherence J Guan, X Mao, C Fan, Z Liu, W Ding, M Huang arXiv preprint arXiv:2105.08963, 2021 | 34 | 2021 |
| LOT: A story-centric benchmark for evaluating Chinese long text understanding and generation J Guan, Z Feng, Y Chen, R He, X Mao, C Fan, M Huang Transactions of the Association for Computational Linguistics 10, 434-451, 2022 | 20* | 2022 |
| Openmeva: A benchmark for evaluating open-ended story generation metrics J Guan, Z Zhang, Z Feng, Z Liu, W Ding, X Mao, C Fan, M Huang arXiv preprint arXiv:2105.08920, 2021 | 18 | 2021 |
| Stylized story generation with style-guided planning X Kong, J Huang, Z Tung, J Guan, M Huang arXiv preprint arXiv:2105.08625, 2021 | 16 | 2021 |
| Cuge: A chinese language understanding and generation evaluation benchmark Y Yao, Q Dong, J Guan, B Cao, Z Zhang, C Xiao, X Wang, F Qi, J Bao, ... arXiv preprint arXiv:2112.13610, 2021 | 6 | 2021 |
| CPM-2: Large-scale Cost-efficient Pre-trained Language Models Z Zhang, Y Gu, X Han, S Chen, C Xiao, Z Sun, Y Yao, F Qi, J Guan, K Pei, ... no, 2021 | 6 | 2021 |
| Persona-Guided Planning for Controlling the Protagonist's Persona in Story Generation Z Zhang, J Wen, J Guan, M Huang arXiv preprint arXiv:2204.10703, 2022 | 5 | 2022 |
| A text GAN for language generation with non-autoregressive generator F Huang, J Guan, P Ke, Q Guo, X Zhu, M Huang | 4 | 2021 |
| A corpus for understanding and generating moral stories J Guan, Z Liu, M Huang arXiv preprint arXiv:2204.09438, 2022 | 3 | 2022 |
| Cotk: An open-source toolkit for fast development and fair evaluation of text generation F Huang, D Wan, Z Shao, P Ke, J Guan, Y Niu, X Zhu, M Huang arXiv preprint arXiv:2002.00583, 2020 | 3 | 2020 |
| Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework J Guan, Z Yang, R Zhang, Z Hu, M Huang arXiv preprint arXiv:2208.03985, 2022 | 2 | 2022 |
| Automatic Comment Generation for Chinese Student Narrative Essays Z Zhang, J Guan, G Xu, Y Tian, M Huang Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | | 2022 |
| A Benchmark for Understanding and Generating Dialogue between Characters in Stories J Yao, Z Liu, J Guan, M Huang arXiv preprint arXiv:2209.08524, 2022 | | 2022 |
Minlie HuangTsinghua UniversityVerified email at tsinghua.edu.cn
