| A dual reinforcement learning framework for unsupervised text style transfer F Luo, P Li, J Zhou, P Yang, B Chang, Z Sui, X Sun arXiv preprint arXiv:1905.10060, 2019 | 171 | 2019 |
| Raise a child in large language model: Towards effective and generalizable fine-tuning R Xu, F Luo, Z Zhang, C Tan, B Chang, S Huang, F Huang arXiv preprint arXiv:2109.05687, 2021 | 123 | 2021 |
| Incorporating glosses into neural word sense disambiguation F Luo, T Liu, Q Xia, B Chang, Z Sui arXiv preprint arXiv:1805.08028, 2018 | 114 | 2018 |
| Enhancing topic-to-essay generation with external commonsense knowledge P Yang, L Li, F Luo, T Liu, X Sun Proceedings of the 57th annual meeting of the association for computational …, 2019 | 90 | 2019 |
| Leveraging gloss knowledge in neural word sense disambiguation by hierarchical co-attention F Luo, T Liu, Z He, Q Xia, Z Sui, B Chang Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 74 | 2018 |
| Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual Storytelling. P Yang, F Luo, P Chen, L Li, Z Yin, X He, X Sun IJCAI 3 (6), 7, 2019 | 67 | 2019 |
| A hierarchical reinforced sequence operation method for unsupervised text style transfer C Wu, X Ren, F Luo, X Sun arXiv preprint arXiv:1906.01833, 2019 | 62 | 2019 |
| VECO: Variable and flexible cross-lingual pre-training for language understanding and generation F Luo, W Wang, J Liu, Y Liu, B Bi, S Huang, F Huang, L Si arXiv preprint arXiv:2010.16046, 2020 | 60* | 2020 |
| Learning to control the fine-grained sentiment for story ending generation F Luo, D Dai, P Yang, T Liu, B Chang, Z Sui, X Sun Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 59 | 2019 |
| A deep reinforced sequence-to-set model for multi-label classification P Yang, F Luo, S Ma, J Lin, X Sun Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 59 | 2019 |
| Hierarchical encoder with auxiliary supervision for neural table-to-text generation: Learning better representation for tables T Liu, F Luo, Q Xia, S Ma, B Chang, Z Sui Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6786-6793, 2019 | 46 | 2019 |
| Towards fine-grained text sentiment transfer F Luo, P Li, P Yang, J Zhou, Y Tan, B Chang, Z Sui, X Sun Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 45 | 2019 |
| Cross-language document summarization via extraction and ranking of multiple summaries X Wan, F Luo, X Sun, S Huang, J Yao Knowledge and Information Systems 58, 481-499, 2019 | 37 | 2019 |
| DeepSeek-Coder: When the Large Language Model Meets Programming--The Rise of Code Intelligence D Guo, Q Zhu, D Yang, Z Xie, K Dong, W Zhang, G Chen, X Bi, Y Wu, ... arXiv preprint arXiv:2401.14196, 2024 | 36 | 2024 |
| Pun-gan: Generative adversarial network for pun generation F Luo, S Li, P Yang, B Chang, Z Sui, X Sun arXiv preprint arXiv:1910.10950, 2019 | 23 | 2019 |
| Towards comprehensive description generation from factual attribute-value tables T Liu, F Luo, P Yang, W Wu, B Chang, Z Sui Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 21 | 2019 |
| SemVLP: Vision-language pre-training by aligning semantics at multiple levels C Li, M Yan, H Xu, F Luo, W Wang, B Bi, S Huang arXiv preprint arXiv:2103.07829, 2021 | 20 | 2021 |
| Towards unified prompt tuning for few-shot text classification J Wang, C Wang, F Luo, C Tan, M Qiu, F Yang, Q Shi, S Huang, M Gao arXiv preprint arXiv:2205.05313, 2022 | 19 | 2022 |
| CAPT: contrastive pre-training for learning denoised sequence representations F Luo, P Yang, S Li, X Ren, X Sun arXiv preprint arXiv:2010.06351, 2020 | 19 | 2020 |
| Making pre-trained language models end-to-end few-shot learners with contrastive prompt tuning Z Xu, C Wang, M Qiu, F Luo, R Xu, S Huang, J Huang Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 18 | 2023 |
Xu SunAssociate Professor, Peking UniversityDirección de correo verificada de pku.edu.cn
