Li-Ming Zhan

29 papers A* 5B 1Journal 13Unranked 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
DEAL: Disentangling Transformer Head Activations for LLM Steering.
CoRR
Li-Ming Zhan, Bo Liu, Zexin Lu, Chengqiang Xie, Jiannong Cao, Xiao-Ming Wu
2025 A* conf
GeoEdit: Geometric Knowledge Editing for Large Language Models.
EMNLP
Yujie Feng, Li-Ming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu
2024 — conf
Continual Dialogue State Tracking via Reason-of-Select Distillation.
ACL (Findings)
Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2024 J jnl
Continual Dialogue State Tracking via Reason-of-Select Distillation.
CoRR
Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2024 — conf
How Good Are LLMs at Out-of-Distribution Detection?
LREC/COLING
Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu
2024 — conf
VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection.
LREC/COLING
Li-Ming Zhan, Bo Liu, Xiao-Ming Wu
2024 J jnl
VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection.
CoRR
Li-Ming Zhan, Bo Liu, Xiao-Ming Wu
2023 J jnl
Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning.
IEEE Trans. Medical Imaging
Bo Liu, Li-Ming Zhan, Li Xu, Xiao-Ming Wu
2023 — conf
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training.
ACL (Findings)
Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2023 J jnl
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training.
CoRR
Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2022 B conf
A Closer Look at Few-Shot Out-of-Distribution Intent Detection.
COLING
Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2022 — conf
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization.
NAACL-HLT
Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam
2022 J jnl
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization.
CoRR
Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam
2022 — conf
New Intent Discovery with Pre-training and Contrastive Learning.
ACL (1)
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2022 J jnl
New Intent Discovery with Pre-training and Contrastive Learning.
CoRR
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2021 J jnl
Adaptation-Agnostic Meta-Training.
CoRR
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
2021 — conf
Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images.
MICCAI (2)
Bo Liu, Li-Ming Zhan, Xiao-Ming Wu
2021 — conf
Effectiveness of Pre-training for Few-shot Intent Classification.
EMNLP (Findings)
Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam
2021 J jnl
Effectiveness of Pre-training for Few-shot Intent Classification.
CoRR
Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam
2021 — conf
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training.
ACL/IJCNLP (1)
Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2021 J jnl
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training.
CoRR
Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2021 A* conf
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima.
NeurIPS
Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu
2021 J jnl
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima.
CoRR
Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu
2021 J jnl
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering.
CoRR
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
2021 — conf
Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering.
ISBI
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
2020 A* conf
A Closer Look at the Training Strategy for Modern Meta-Learning.
NeurIPS
Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung
2020 A* conf
Medical Visual Question Answering via Conditional Reasoning.
ACM Multimedia
Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu
2020 A* conf
Variational Metric Scaling for Metric-Based Meta-Learning.
AAAI
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
2019 J jnl
Variational Metric Scaling for Metric-Based Meta-Learning.
CoRR
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung