| A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics K He, R Mao, Q Lin, Y Ruan, X Lan, M Feng, E Cambria Information Fusion, 102963, 2025 | 142 | 2025 |
| Multi-source aggregated classification for stock price movement prediction Y Ma, R Mao, Q Lin, P Wu, E Cambria Information Fusion 91, 515-528, 2023 | 101 | 2023 |
| Lexical based automated teaching evaluation via students’ short reviews Q Lin, Y Zhu, S Zhang, P Shi, Q Guo, Z Niu Computer Applications in Engineering Education 27 (1), 194-205, 2019 | 82 | 2019 |
| Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond F Xu*, Q Lin*, J Han, T Zhao, J Liu, E Cambria IEEE Transactions on Knowledge and Data Engineering, 2025 | 73* | 2025 |
| Recommending scientific paper via heterogeneous knowledge embedding based attentive recurrent neural networks Y Zhu, Q Lin, H Lu, K Shi, P Qiu, Z Niu Knowledge-Based Systems 215, 106744, 2021 | 62 | 2021 |
| Fusing topology contexts and logical rules in language models for knowledge graph completion Q Lin, R Mao, J Liu, F Xu, E Cambria Information Fusion, 2023 | 57 | 2023 |
| Incorporating context graph with logical reasoning for inductive relation prediction Q Lin, J Liu, F Xu, Y Pan, Y Zhu, L Zhang, T Zhao SIGIR 2022, 893-903, 2022 | 53 | 2022 |
| Heterogeneous knowledge-based attentive neural networks for short-term music recommendations Q Lin, Y Niu, Y Zhu, H Lu, KZ Mushonga, Z Niu IEEE Access 6, 58990-59000, 2018 | 49 | 2018 |
| WinGNN: dynamic graph neural networks with random gradient aggregation window Y Zhu, F Cong, D Zhang, W Gong, Q Lin, W Feng, Y Dong, J Tang KDD, 3650-3662, 2023 | 44 | 2023 |
| Improving university faculty evaluations via multi-view knowledge graph Q Lin, Y Zhu, H Lu, K Shi, Z Niu Future Generation Computer Systems 117, 181-192, 2021 | 40 | 2021 |
| TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning Q Lin, J Liu, R Mao, F Xu, E Cambria ACL 2023, 2023 | 39 | 2023 |
| Recommending learning objects through attentive heterogeneous graph convolution and operation-aware neural network Y Zhu*, Q Lin*, H Lu, K Shi, D Liu, J Chambua, S Wan, Z Niu IEEE Transactions on Knowledge and Data Engineering 35 (4), 4178-4189, 2021 | 37 | 2021 |
| Academic rising star prediction via scholar’s evaluation model and machine learning techniques Y Nie, Y Zhu, Q Lin, S Zhang, P Shi, Z Niu Scientometrics 120 (2), 461-476, 2019 | 36 | 2019 |
| Quantitative stock portfolio optimization by multi-task learning risk and return Y Ma, R Mao, Q Lin, P Wu, E Cambria Information Fusion 104, 102165, 2024 | 33 | 2024 |
| Rule-enhanced iterative complementation for knowledge graph reasoning Q Lin, J Liu, Y Pan, L Zhang, X Hu, J Ma Information Sciences 575, 66-79, 2021 | 33 | 2021 |
| Multitask learning for visual question answering J Ma, J Liu, Q Lin, B Wu, Y Wang, Y You IEEE Transactions on neural networks and learning systems 34 (3), 1380-1394, 2021 | 31 | 2021 |
| Inductive relation prediction with logical reasoning using contrastive representations Y Pan, J Liu, L Zhang, T Zhao, Q Lin, X Hu, Q Wang EMNLP 2022, 4261-4274, 2022 | 30* | 2022 |
| Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning F Xu, Q Lin, J Liu, Y Pan, L Zhang SIGIR 2022, 2022 | 27 | 2022 |
| Symbol-llm: Towards foundational symbol-centric interface for large language models F Xu, Z Wu, Q Sun, S Ren, F Yuan, S Yuan, Q Lin, Y Qiao, J Liu ACL 2024, 2023 | 26 | 2023 |
| MuL-GRN: Multi-level graph relation network for few-shot node classification L Zhang, S Wang, J Liu, X Chang, Q Lin, Y Wu, Q Zheng IEEE Transactions on Knowledge and Data Engineering 35 (6), 6085-6098, 2022 | 25 | 2022 |
Fangzhi XuXi'an Jiaotong Universitystu.xjtu.edu.cn의 이메일 확인됨