| Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering B Liu, LM Zhan, L Xu, L Ma, Y Yang, XM Wu 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1650-1654, 2021 | 111 | 2021 |
| Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima G Shi, J Chen, W Zhang, LM Zhan, XM Wu Advances in neural information processing systems 34, 6747-6761, 2021 | 105 | 2021 |
| Medical visual question answering via conditional reasoning LM Zhan, B Liu, L Fan, J Chen, XM Wu Proceedings of the 28th ACM International Conference on Multimedia, 2345-2354, 2020 | 103 | 2020 |
| Contrastive pre-training and representation distillation for medical visual question answering based on radiology images B Liu, LM Zhan, XM Wu Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 65 | 2021 |
| Out-of-scope intent detection with self-supervision and discriminative training LM Zhan, H Liang, B Liu, L Fan, XM Wu, A Lam arXiv preprint arXiv:2106.08616, 2021 | 62 | 2021 |
| Effectiveness of pre-training for few-shot intent classification H Zhang, Y Zhang, LM Zhan, J Chen, G Shi, XM Wu, A Lam arXiv preprint arXiv:2109.05782, 2021 | 42 | 2021 |
| Variational metric scaling for metric-based meta-learning J Chen, LM Zhan, XM Wu, F Chung Proceedings of the AAAI conference on artificial intelligence 34 (04), 3478-3485, 2020 | 39 | 2020 |
| New intent discovery with pre-training and contrastive learning Y Zhang, H Zhang, LM Zhan, XM Wu, A Lam arXiv preprint arXiv:2205.12914, 2022 | 34 | 2022 |
| A closer look at the training strategy for modern meta-learning J Chen, XM Wu, Y Li, Q Li, LM Zhan, F Chung Advances in Neural Information Processing Systems 33, 396-406, 2020 | 33 | 2020 |
| Fine-tuning pre-trained language models for few-shot intent detection: Supervised pre-training and isotropization H Zhang, H Liang, Y Zhang, L Zhan, XM Wu, X Lu, A Lam arXiv preprint arXiv:2205.07208, 2022 | 20 | 2022 |
| Medical visual question answering via conditional reasoning and contrastive learning B Liu, LM Zhan, L Xu, XM Wu IEEE transactions on medical imaging 42 (5), 1532-1545, 2022 | 11 | 2022 |
| Revisit few-shot intent classification with PLMs: Direct fine-tuning vs. continual pre-training H Zhang, H Liang, L Zhan, XM Wu, A Lam arXiv preprint arXiv:2306.05278, 2023 | 1 | 2023 |
| A closer look at few-shot out-of-distribution intent detection LM Zhan, H Liang, L Fan, XM Wu, AYS Lam Proceedings of the 29th International Conference on Computational …, 2022 | 1 | 2022 |
| VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection LM Zhan, B Liu, XM Wu arXiv preprint arXiv:2404.06217, 2024 | | 2024 |
| Adaptation-Agnostic Meta-Training J Chen, LM Zhan, XM Wu, FL Chung arXiv preprint arXiv:2108.10557, 2021 | | 2021 |
| current position: Home> NLP paper reading| improving semantic representation of intention recognition: isotropic regularization method in supervised pre training NLP paper … H Zhang, H Liang, Y Zhang, L Zhan, XM Wu, X Lu, AYS Lam | | |
Xiao-Ming WuAssociate Professor, The Hong Kong Polytechnic UniversityVerified email at polyu.edu.hk
