Variational Metric Scaling for Metric-Based Meta-Learning. - Jiaxin Chen; Li-Ming Zhan; Xiao-Ming Wu 003; Fu-Lai Chung (AAAI, 2020)

Medical Visual Question Answering via Conditional Reasoning. - Li-Ming Zhan; Bo Liu 049; Lu Fan; Jiaxin Chen; Xiao-Ming Wu 003 (ACM Multimedia, 2020)

A Closer Look at the Training Strategy for Modern Meta-Learning. - Jiaxin Chen; Xiao-Ming Wu 003; Yanke Li; Qimai Li; Li-Ming Zhan; Fu-Lai Chung (NeurIPS, 2020)

Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. - Li-Ming Zhan; Haowen Liang; Bo Liu 049; Lu Fan; Xiao-Ming Wu 003; Albert Y. S. Lam (ACL/IJCNLP (1), 2021)

Effectiveness of Pre-training for Few-shot Intent Classification. - Haode Zhang; Yuwei Zhang 001; Li-Ming Zhan; Jiaxin Chen; Guangyuan Shi; Xiao-Ming Wu 003; Albert Y. S. Lam (EMNLP (Findings), 2021)

Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering. - Bo Liu 049; Li-Ming Zhan; Li Xu; Lin Ma; Yan Yang; Xiao-Ming Wu 003 (ISBI, 2021)

Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images. - Bo Liu 049; Li-Ming Zhan; Xiao-Ming Wu 003 (MICCAI (2), 2021)

Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. - Guangyuan Shi; Jiaxin Chen; Wenlong Zhang; Li-Ming Zhan; Xiao-Ming Wu 003 (NeurIPS, 2021)

Adaptation-Agnostic Meta-Training. - Jiaxin Chen; Li-Ming Zhan; Xiao-Ming Wu 003; Fu-Lai Chung (CoRR, 2021)

New Intent Discovery with Pre-training and Contrastive Learning. - Yuwei Zhang 001; Haode Zhang; Li-Ming Zhan; Xiao-Ming Wu 003; Albert Y. S. Lam (ACL (1), 2022)

A Closer Look at Few-Shot Out-of-Distribution Intent Detection. - Li-Ming Zhan; Haowen Liang; Lu Fan; Xiao-Ming Wu 003; Albert Y. S. Lam (COLING, 2022)

Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. - Haode Zhang; Haowen Liang; Yuwei Zhang 001; Li-Ming Zhan; Xiao-Ming Wu 003; Xiaolei Lu; Albert Y. S. Lam (NAACL-HLT, 2022)

Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. - Haode Zhang; Haowen Liang; Li-Ming Zhan; Xiao-Ming Wu 003; Albert Y. S. Lam (ACL (Findings), 2023)

Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning. - Bo Liu 049; Li-Ming Zhan; Li Xu; Xiao-Ming Wu 003 (IEEE Trans. Medical Imaging, 2023)

Continual Dialogue State Tracking via Reason-of-Select Distillation. - Yujie Feng; Bo Liu 049; Xiaoyu Dong; Zexin Lu; Li-Ming Zhan; Xiao-Ming Wu 003; Albert Y. S. Lam (ACL (Findings), 2024)

How Good Are LLMs at Out-of-Distribution Detection? - Bo Liu 049; Li-Ming Zhan; Zexin Lu; Yujie Feng; Lei Xue 001; Xiao-Ming Wu 003 (LREC/COLING, 2024)

VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection. - Li-Ming Zhan; Bo Liu; Xiao-Ming Wu (LREC/COLING, 2024)

VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection. - Li-Ming Zhan; Bo Liu; Xiao-Ming Wu (CoRR, 2024)

DEAL: Disentangling Transformer Head Activations for LLM Steering. - Li-Ming Zhan; Bo Liu 049; Zexin Lu; Chengqiang Xie; Jiannong Cao 001; Xiao-Ming Wu 003 (CoRR, 2025)