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)

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)

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)

Asymmetric feature interaction for interpreting model predictions. - Xiaolei Lu; Jianghong Ma; Haode Zhang (ACL (Findings), 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 003; Albert Y. S. Lam (ACL (Findings), 2023)

Minimizing PLM-Based Few-Shot Intent Detectors. - Haode Zhang; Xiao-Ming Wu; Albert Y. S. Lam (CoRR, 2024)

Robust Reward Alignment via Hypothesis Space Batch Cutting. - Zhixian Xie; Haode Zhang; Yizhe Feng; Wanxin Jin (CoRR, 2025)