| 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 | 259 | 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 | 171 | 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 | 145 | 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 | 99 | 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 | 74 | 2021 |
| 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 | 58 | 2022 |
| Effectiveness of pre-training for few-shot intent classification H Zhang, Y Zhang, LM Zhan, J Chen, G Shi, A Lam, XM Wu arXiv preprint arXiv:2109.05782, 2021 | 50 | 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 | 50 | 2020 |
| 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 | 41 | 2020 |
| Towards LLM-driven dialogue state tracking Y Feng, Z Lu, B Liu, L Zhan, XM Wu arXiv preprint arXiv:2310.14970, 2023 | 37 | 2023 |
| Fine-tuning pre-trained language models for few-shot intent detection: Supervised pre-training and isotropization H Zhang, H Liang, Y Zhang, L Zhan, X Lu, A Lam, XM Wu arXiv preprint arXiv:2205.07208, 2022 | 33 | 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 | 30 | 2022 |
| How Good Are LLMs at Out-of-Distribution Detection? B Liu, L Zhan, Z Lu, Y Feng, L Xue, XM Wu arXiv preprint arXiv:2308.10261, 2023 | 13 | 2023 |
| Revisit few-shot intent classification with PLMs: Direct fine-tuning vs. continual pre-training H Zhang, H Liang, L Zhan, A Lam, XM Wu arXiv preprint arXiv:2306.05278, 2023 | 13 | 2023 |
| How good are llms at out-of-distribution detection? B Liu, LM Zhan, Z Lu, Y Feng, L Xue, XM Wu Proceedings of the 2024 Joint International Conference on Computational …, 2024 | 11 | 2024 |
| 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 | 5 | 2022 |
| Continual dialogue state tracking via reason-of-select distillation Y Feng, B Liu, X Dong, Z Lu, LM Zhan, A Lam, XM Wu arXiv preprint arXiv:2408.09846, 2024 | 3 | 2024 |
| GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis B Liu, K Zou, L Zhan, Z Lu, X Dong, Y Chen, C Xie, J Cao, XM Wu, H Fu arXiv preprint arXiv:2411.16778, 2024 | 2 | 2024 |
| VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection LM Zhan, B Liu, XM Wu Proceedings of the 2024 Joint International Conference on Computational …, 2024 | 1 | 2024 |
| 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 | 1 | 2024 |
Xiao-Ming WuAssociate Professor, The Hong Kong Polytechnic UniversityOverená e-mailová adresa na: polyu.edu.hk