| Transprompt: Towards an automatic transferable prompting framework for few-shot text classification C Wang, J Wang, M Qiu, J Huang, M Gao EMNLP 2021, 2792-2802, 2021 | 59 | 2021 |
| Boosting Language Models Reasoning with Chain-of-Knowledge Prompting J Wang, Q Sun, X Li, M Gao ACL 2024, 2023 | 54 | 2023 |
| Spanproto: A two-stage span-based prototypical network for few-shot named entity recognition J Wang, C Han, C Wang, C Tan, M Qiu, S Huang, J Huang, M Gao EMNLP 2022, 2022 | 36 | 2022 |
| 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 Findings of EMNLP 2022, 2022 | 35 | 2022 |
| A survey of neural code intelligence: Paradigms, advances and beyond Q Sun, Z Chen, F Xu, K Cheng, C Ma, Z Yin, J Wang, C Han, R Zhu, ... arXiv preprint arXiv:2403.14734, 2024 | 33* | 2024 |
| Prompting large language models with chain-of-thought for few-shot knowledge base question generation Y Liang, J Wang, H Zhu, L Wang, W Qian, Y Lan EMNLP 2023, 2023 | 30 | 2023 |
| Making pre-trained language models end-to-end few-shot learners with contrastive prompt tuning Z Xu, C Wang, J Wang, M Qiu, F Luo, R Xu, S Huang, J Huang Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 30 | 2023 |
| Easynlp: A comprehensive and easy-to-use toolkit for natural language processing C Wang, M Qiu, C Shi, T Zhang, T Liu, L Li, J Wang, M Wang, J Huang, ... EMNLP (Demos) 2022, 2022 | 28 | 2022 |
| InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment J Wang, J Wu, Y Hou, Y Liu, M Gao, J McAuley Findings of ACL 2024, 2024 | 27 | 2024 |
| Knowledge prompting in pre-trained language model for natural language understanding J Wang, W Huang, Q Shi, H Wang, M Qiu, X Li, M Gao EMNLP 2022, 2022 | 25 | 2022 |
| Kecp: Knowledge enhanced contrastive prompting for few-shot extractive question answering J Wang, C Wang, M Qiu, Q Shi, H Wang, J Huang, M Gao EMNLP 2022, 2022 | 19 | 2022 |
| CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation J Wu, CC Chang, T Yu, Z He, J Wang, Y Hou, J McAuley KDD 2024, 2024 | 14 | 2024 |
| Revisiting and advancing Chinese natural language understanding with accelerated heterogeneous knowledge pre-training T Zhang, J Dong, J Wang, C Wang, A Wang, Y Liu, J Huang, Y Li, X He EMNLP (Industry) 2022, 2022 | 9 | 2022 |
| RH-Net: Improving neural relation extraction via reinforcement learning and hierarchical relational searching J Wang arXiv preprint arXiv:2010.14255, 2020 | 9 | 2020 |
| HugNLP: A Unified and Comprehensive Library for Natural Language Processing J Wang, N Chen, Q Sun, W Huang, C Wang, M Gao CIKM (Best Demo Paper) 2023, 2023 | 8 | 2023 |
| When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario C Han, L Cui, R Zhu, J Wang, N Chen, Q Sun, X Li, M Gao Findings of ACL 2023, 2023 | 7 | 2023 |
| Math-KG: Construction and applications of mathematical knowledge graph J Wang arXiv preprint arXiv:2205.03772, 2022 | 7 | 2022 |
| Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning J Wang, C Wang, C Tan, J Huang, M Gao arXiv preprint arXiv:2309.14771, 2023 | 6* | 2023 |
| Transcoder: Towards unified transferable code representation learning inspired by human skills Q Sun, N Chen, J Wang, X Li, M Gao COLING 2024, 2023 | 6 | 2023 |
| Pass-Tuning: Towards Structure-Aware Parameter-Efficient Tuning for Code Representation Learning N Chen, Q Sun, J Wang, X Li, M Gao Findings of the Association for Computational Linguistics: EMNLP 2023, 577--591, 2023 | 5 | 2023 |
Ming GaoSchool of Data Science and Engineering, East China Normal UniversityPreverjeni e-poštni naslov na dase.ecnu.edu.cn
