| 2025 | EMNLP | GeoEdit: Geometric Knowledge Editing for Large Language Models. | Yujie Feng, Li-Ming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu |
| 2025 | ICCV | GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-Ray Diagnosis. | Bo Liu, Ke Zou, Li-Ming Zhan, Zexin Lu, Xiaoyu Dong, Yidi Chen, Chengqiang Xie, Jiannong Cao, Xiao-Ming Wu, Huazhu Fu |
| 2024 | ACL | 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 |
| 2024 | COLING | How Good Are LLMs at Out-of-Distribution Detection? | Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu |
| 2024 | COLING | VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection. | Li-Ming Zhan, Bo Liu, Xiao-Ming Wu |
| 2023 | ACL | 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 |
| 2022 | ACL | New Intent Discovery with Pre-training and Contrastive Learning. | Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2022 | COLING | 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 |
| 2022 | NAACL | 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 |
| 2021 | ACL | 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 |
| 2021 | EMNLP | 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 |
| 2021 | MICCAI | Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images. | Bo Liu, Li-Ming Zhan, Xiao-Ming Wu |
| 2020 | AAAI | Variational Metric Scaling for Metric-Based Meta-Learning. | Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung |