Li-Ming Zhan

According to our database, Li-Ming Zhan authored at least 17 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

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