| Topic-to-essay generation with neural networks. X Feng, M Liu, J Liu, B Qin, Y Sun, T Liu IJCAI 2018, 4078-4084, 2018 | 79 | 2018 |
| 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 ACL 2021 (long paper), 2020 | 60* | 2020 |
| RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank J Liu, J Liu, Q Wang, J Wang, W Wu, Y Xian, D Zhao, K Chen, R Yan ACL 2023 (long paper, oral), 13785–13802, 2023 | 15 | 2023 |
| VIRT: Improving Representation-based Text Matching via Virtual Interaction D Li, Y Yang, H Tang, J Liu, Q Wang, J Wang, T Xu, W Wu, E Chen EMNLP 2022, 914-925, 2022 | 13* | 2022 |
| A practical semi-parametric contextual bandit. Y Peng, M Xie, J Liu, X Meng, N Li, C Yang, T Yao, R Jin IJCAI 2019, 3246-3252, 2019 | 11 | 2019 |
| A planning based framework for essay generation B Qin, D Tang, X Geng, D Ning, J Liu, T Liu arXiv preprint arXiv:1512.05919, 2015 | 8 | 2015 |
| mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learning Y Mo, J Yang, J Liu, Q Wang, R Chen, J Wang, Z Li AAAI 2024, 2023 | 5 | 2023 |
| Multi-Task Transformer with Relation-Attention and Type-Attention for Named Entity Recognition Y Mo, H Tang, J Liu, Q Wang, Z Xu, J Wang, W Wu, Z Li ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 5 | 2023 |
| Lifting the Curse of Capacity Gap in Distilling Language Models C Zhang, Y Yang, J Liu, J Wang, Y Xian, B Wang, D Song ACL 2023 (long paper), 4535–4553, 2023 | 5 | 2023 |
| PreQuant: A Task-agnostic Quantization Approach for Pre-trained Language Models Z Gong, J Liu, Q Wang, Y Yang, J Wang, W Wu, Y Xian, D Zhao, R Yan Findings of ACL 2023, 8065–8079, 2023 | 4 | 2023 |
| Minimal Distillation Schedule for Extreme Language Model Compression C Zhang, Y Yang, Q Wang, J Liu, J Wang, W Wu, D Song Findings of EACL 2024, 1378-1394, 2024 | 2* | 2024 |
| GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval J Liu, J Liu, Y Yang, J Wang, W Wu, D Zhao, R Yan Findings of EMNLP2022, 2022 | 1 | 2022 |
| Parallel Decoding via Hidden Transfer for Lossless Large Language Model Acceleration P Wu, J Liu, Z Gong, Q Wang, J Li, J Wang, X Cai, D Zhao arXiv preprint arXiv:2404.12022, 2024 | | 2024 |
| What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation Z Gong, J Liu, J Wang, X Cai, D Zhao, R Yan AAAI 2024, 2024 | | 2024 |
| Improving Input-label Mapping with Demonstration Replay for In-context Learning Z Gong, J Liu, Q Wang, J Wang, X Cai, D Zhao, R Yan Findings of EMNLP2023, 2023 | | 2023 |
| Retrieval-based Knowledge Transfer: An Effective Approach for Extreme Large Language Model Compression J Liu, J Liu, Q Wang, J Wang, X Cai, D Zhao, RL Wang, R Yan Findings of EMNLP2023, 2023 | | 2023 |
| Deep Learning Based Document Theme Analysis for Composition Generation J Liu, C Sun, B Qin Chinese Computational Linguistics and Natural Language Processing Based on …, 2017 | | 2017 |
Qifan WangResearch Scientist, Meta AI在 fb.com 的电子邮件经过验证
