Li-Ming Zhan

According to our database, Li-Ming Zhan authored at least 18 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection.

Li-Ming Zhan, Bo Liu, Xiao-Ming Wu

CoRR, 2024

VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection.

Li-Ming Zhan, Bo Liu, Xiao-Ming Wu

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

How Good Are LLMs at Out-of-Distribution Detection?

Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Continual Dialogue State Tracking via Reason-of-Select Distillation.

Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning.

Bo Liu, Li-Ming Zhan, Li Xu, Xiao-Ming Wu

IEEE Trans. Medical Imaging, May, 2023

Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training.

Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization.

Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

A Closer Look at Few-Shot Out-of-Distribution Intent Detection.

Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the 29th International Conference on Computational Linguistics, 2022

New Intent Discovery with Pre-training and Contrastive Learning.

Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Adaptation-Agnostic Meta-Training.

Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images.

Bo Liu, Li-Ming Zhan, Xiao-Ming Wu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering.

Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Effectiveness of Pre-training for Few-shot Intent Classification.

Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training.

Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

A Closer Look at the Training Strategy for Modern Meta-Learning.

Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Medical Visual Question Answering via Conditional Reasoning.

Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Variational Metric Scaling for Metric-Based Meta-Learning.

Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020