Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning. - Shuzhen Rao; Jun Huang 009; Zengming Tang (CoRR, 2023)

Leveraging enhanced task embeddings for generalization in multimodal meta-learning. - Shuzhen Rao; Jun Huang 009 (Neural Comput. Appl., 2023)

Adaptive Regularized Warped Gradient Descent Enhances Model Generalization and Meta-learning for Few-shot Learning. - Shuzhen Rao; Jun Huang 009; Zengming Tang (Neurocomputing, 2023)

RDProtoFusion: Refined discriminative prototype-based multi-task fusion for cross-domain few-shot learning. - Shuzhen Rao; Jun Huang 009; Zengming Tang (Neurocomputing, 2024)

Hierarchical global to local calibration for query-focused few-shot node classification. - Shuzhen Rao; Jun Huang 009; Zengming Tang (Inf. Fusion, 2025)

Heterogeneous graph multi-level semantics extraction for node classification. - Haochang Hao; Jun Huang 009; Shuzhen Rao (Neural Comput. Appl., 2025)