| K-bert: Enabling language representation with knowledge graph W Liu, P Zhou, Z Zhao, Z Wang, Q Ju, H Deng, P Wang Proceedings of the AAAI Conference on Artificial Intelligence 34 (03), 2901-2908, 2020 | 909 | 2020 |
| Analogical reasoning on chinese morphological and semantic relations S Li, Z Zhao, R Hu, W Li, T Liu, X Du arXiv preprint arXiv:1805.06504, 2018 | 572 | 2018 |
| Fastbert: a self-distilling bert with adaptive inference time W Liu, P Zhou, Z Zhao, Z Wang, H Deng, Q Ju arXiv preprint arXiv:2004.02178, 2020 | 363 | 2020 |
| CLUE: A Chinese language understanding evaluation benchmark L Xu, H Hu, X Zhang, L Li, C Cao, Y Li, Y Xu, K Sun, D Yu, C Yu, Y Tian, ... arXiv preprint arXiv:2004.05986, 2020 | 339 | 2020 |
| UER: An open-source toolkit for pre-training models Z Zhao, H Chen, J Zhang, X Zhao, T Liu, W Lu, X Chen, H Deng, Q Ju, ... arXiv preprint arXiv:1909.05658, 2019 | 108 | 2019 |
| Ngram2vec: Learning improved word representations from ngram co-occurrence statistics Z Zhao, T Liu, S Li, B Li, X Du Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 81 | 2017 |
| Initializing convolutional filters with semantic features for text classification S Li, Z Zhao, T Liu, R Hu, X Du Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 66 | 2017 |
| CSL: A large-scale Chinese scientific literature dataset Y Li, Y Zhang, Z Zhao, L Shen, W Liu, W Mao, H Zhang arXiv preprint arXiv:2209.05034, 2022 | 44 | 2022 |
| Investigating different syntactic context types and context representations for learning word embeddings B Li, T Liu, Z Zhao, B Tang, A Drozd, A Rogers, X Du Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 44 | 2017 |
| Weighted neural bag-of-n-grams model: New baselines for text classification B Li, Z Zhao, T Liu, P Wang, X Du Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 38 | 2016 |
| Neural bag-of-ngrams B Li, T Liu, Z Zhao, P Wang, X Du Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 32 | 2017 |
| Learning document embeddings by predicting n-grams for sentiment classification of long movie reviews B Li, T Liu, X Du, D Zhang, Z Zhao arXiv preprint arXiv:1512.08183, 2015 | 32 | 2015 |
| Tencentpretrain: A scalable and flexible toolkit for pre-training models of different modalities Z Zhao, Y Li, C Hou, J Zhao, R Tian, W Liu, Y Chen, N Sun, H Liu, W Mao, ... arXiv preprint arXiv:2212.06385, 2022 | 19 | 2022 |
| Guiding the training of distributed text representation with supervised weighting scheme for sentiment analysis Z Zhao, T Liu, S Li, B Li, X Du Data Science and Engineering 2, 178-186, 2017 | 12 | 2017 |
| Document-level event argument extraction with a chain reasoning paradigm J Liu, C Liang, J Xu, H Liu, Z Zhao Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 11 | 2023 |
| A Simple and Effective Method to Improve Zero-Shot Cross-Lingual Transfer Learning K Ding, W Liu, Y Fang, W Mao, Z Zhao, T Zhu, H Liu, R Tian, Y Chen arXiv preprint arXiv:2210.09934, 2022 | 8 | 2022 |
| Weight-inherited distillation for task-agnostic bert compression T Wu, C Hou, S Lao, J Li, N Wong, Z Zhao, Y Yang arXiv preprint arXiv:2305.09098, 2023 | 7 | 2023 |
| Edge-free but structure-aware: Prototype-guided knowledge distillation from gnns to mlps T Wu, Z Zhao, J Wang, X Bai, L Wang, N Wong, Y Yang arXiv preprint arXiv:2303.13763, 2023 | 7 | 2023 |
| Cluster-driven model for improved word and text embedding Z Zhao, T Liu, B Li, X Du ECAI 2016, 99-106, 2016 | 7 | 2016 |
| An empirical study on adaptive inference for pretrained language model W Liu, X Zhao, Z Zhao, Q Ju, X Yang, W Lu IEEE Transactions on Neural Networks and Learning Systems 34 (8), 4321-4331, 2021 | 6 | 2021 |
