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2020 – today
- 2024
[c15]Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Continual Dialogue State Tracking via Reason-of-Select Distillation. ACL (Findings) 2024: 7075-7087- [c14]Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu:
How Good Are LLMs at Out-of-Distribution Detection? LREC/COLING 2024: 8211-8222 - [c13]Li-Ming Zhan, Bo Liu, Xiao-Ming Wu:
VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection. LREC/COLING 2024: 17371-17383 - [i11]Li-Ming Zhan, Bo Liu, Xiao-Ming Wu:
VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection. CoRR abs/2404.06217 (2024) - [i10]Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Continual Dialogue State Tracking via Reason-of-Select Distillation. CoRR abs/2408.09846 (2024) - 2023
- [j1]Bo Liu
, Li-Ming Zhan, Li Xu, Xiao-Ming Wu:
Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning. IEEE Trans. Medical Imaging 42(5): 1532-1545 (2023) - [c12]Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. ACL (Findings) 2023: 11105-11121 - [i9]Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. CoRR abs/2306.05278 (2023) - 2022
- [c11]Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
New Intent Discovery with Pre-training and Contrastive Learning. ACL (1) 2022: 256-269 - [c10]Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
A Closer Look at Few-Shot Out-of-Distribution Intent Detection. COLING 2022: 451-460 - [c9]Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam:
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. NAACL-HLT 2022: 532-542 - [i8]Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam:
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. CoRR abs/2205.07208 (2022) - [i7]Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
New Intent Discovery with Pre-training and Contrastive Learning. CoRR abs/2205.12914 (2022) - 2021
- [c8]Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. ACL/IJCNLP (1) 2021: 3521-3532 - [c7]Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam:
Effectiveness of Pre-training for Few-shot Intent Classification. EMNLP (Findings) 2021: 1114-1120 - [c6]Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu:
Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering. ISBI 2021: 1650-1654 - [c5]Bo Liu, Li-Ming Zhan, Xiao-Ming Wu:
Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images. MICCAI (2) 2021: 210-220 - [c4]Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu:
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. NeurIPS 2021: 6747-6761 - [i6]Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu:
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering. CoRR abs/2102.09542 (2021) - [i5]Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. CoRR abs/2106.08616 (2021) - [i4]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Adaptation-Agnostic Meta-Training. CoRR abs/2108.10557 (2021) - [i3]Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam:
Effectiveness of Pre-training for Few-shot Intent Classification. CoRR abs/2109.05782 (2021) - [i2]Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu:
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. CoRR abs/2111.01549 (2021) - 2020
- [c3]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Variational Metric Scaling for Metric-Based Meta-Learning. AAAI 2020: 3478-3485 - [c2]Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu:
Medical Visual Question Answering via Conditional Reasoning. ACM Multimedia 2020: 2345-2354 - [c1]Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung:
A Closer Look at the Training Strategy for Modern Meta-Learning. NeurIPS 2020
2010 – 2019
- 2019
- [i1]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Variational Metric Scaling for Metric-Based Meta-Learning. CoRR abs/1912.11809 (2019)
Coauthor Index
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last updated on 2024-09-26 00:52 CEST by the dblp team
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