| Disan: Directional self-attention network for rnn/cnn-free language understanding T Shen, T Zhou, G Long, J Jiang, S Pan, C Zhang Thirty-Second AAAI Conference on Artificial Intelligence, 5446-5455, 2018 | 899 | 2018 |
| Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion B Wang, T Shen, G Long, T Zhou, Y Wang, Y Chang (WWW) The Web Conference 2021, 2021 | 243 | 2021 |
| Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling T Shen, T Zhou, G Long, J Jiang, C Zhang (ICLR) The International Conference on Learning Representations, 2018 | 180 | 2018 |
| Multi-center federated learning: clients clustering for better personalization G Long, M Xie, T Shen, T Zhou, X Wang, J Jiang World Wide Web 26 (1), 481-500, 2022 | 167 | 2022 |
| Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling T Shen, T Zhou, G Long, J Jiang, S Wang, C Zhang (IJCAI) International Joint Conference on Artificial Intelligence and the …, 2018 | 162 | 2018 |
| Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction Y Li, G Long, T Shen, T Zhou, L Yao, H Huo, J Jiang (AAAI) Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020 | 104 | 2020 |
| Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base T Shen, X Geng, T Qin, D Guo, D Tang, N Duan, G Long, D Jiang (EMNLP-IJCNLP) Conference on Empirical Methods in Natural Language …, 2019 | 99 | 2019 |
| Federated learning for privacy-preserving open innovation future on digital health G Long, T Shen, Y Tan, L Gerrard, A Clarke, J Jiang Humanity Driven AI, 113-133, 2022 | 84 | 2022 |
| A Survey on Knowledge Distillation of Large Language Models X Xu, M Li, C Tao, T Shen, R Cheng, J Li, C Xu, D Tao, T Zhou arXiv preprint arXiv:2402.13116, 2024 | 78 | 2024 |
| Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning T Shen, Y Mao, P He, G Long, A Trischler, W Chen (EMNLP) Conference on Empirical Methods in Natural Language Processing, 2020 | 71 | 2020 |
| Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph Y Zhou, X Geng, T Shen, W Zhang, D Jiang (NAACL) Proceedings of the 2021 Conference of the North American Chapter of …, 2021 | 68 | 2021 |
| ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification Y Zhou, T Shen, X Geng, G Long, D Jiang (ACL) 60th Annual Meeting of the Association for Computational Linguistics, 2022 | 59 | 2022 |
| EventBERT: A Pre-Trained Model for Event Correlation Reasoning Y Zhou, X Geng, T Shen, G Long, D Jiang (WWW) The Web Conference 2022, 2022 | 50 | 2022 |
| Modeling Event-Pair Relations in External Knowledge Graphs for Script Reasoning Y Zhou, X Geng, T Shen, J Pei, W Zhang, D Jiang ACL Findings, 2021 | 40 | 2021 |
| Leveraging Large Language Models for NLG Evaluation: A Survey Z Li, X Xu, T Shen, C Xu, JC Gu, C Tao (EMNLP) The 2024 Conference on Empirical Methods in Natural Language Processing, 2024 | 37 | 2024 |
| LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval T Shen, X Geng, C Tao, C Xu, X Huang, B Jiao, L Yang, D Jiang (ICLR) Eleventh International Conference on Learning Representations, 2023 | 37 | 2023 |
| Large Language Models are Strong Zero-Shot Retriever T Shen, G Long, X Geng, C Tao, T Zhou, D Jiang (ACL-findings) The 62nd Annual Meeting of the Association for Computational …, 2024 | 36 | 2024 |
| Towards Robust Ranker for Text Retrieval Y Zhou, T Shen, X Geng, C Tao, C Xu, G Long, B Jiao, D Jiang ACL-findings, 2023 | 36 | 2023 |
| Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering T Shen, X Geng, G Long, J Jiang, C Zhang, D Jiang (IJCAI-PRICAI) The 29th International Joint Conference on Artificial …, 2020 | 36* | 2020 |
| PCL: Peer-Contrastive Learning with Diverse Augmentations for Unsupervised Sentence Embeddings Q Wu, C Tao, T Shen, C Xu, X Geng, D Jiang (EMNLP) The 2022 Conference on Empirical Methods in Natural Language Processing, 2022 | 35 | 2022 |
Guodong LongAssociate Professor, Faculty of Engineering and IT, University of Technology SydneyDirección de correo verificada de uts.edu.au