MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition. - Naichuan Zheng; Hailun Xia; Zeyu Liang 001 (CoRR, 2024)

Topological Symmetry Enhanced Graph Convolution for Skeleton-Based Action Recognition. - Zeyu Liang 001; Hailun Xia; Naichuan Zheng; Huan Xu (CoRR, 2024)

Scaling Under-Resourced TTS: A Data-Optimized Framework with Advanced Acoustic Modeling for Thai. - Yizhong Geng; Jizhuo Xu; Zeyu Liang 001; Jinghan Yang; Xiaoyi Shi; Xiaoyu Shen 001 (ACL (6), 2025)

Signal-SGN: A Spiking Graph Convolutional Network for Skeleton Action Recognition via Learning Temporal-Frequency Dynamics. - Naichuan Zheng; Yuchen Du; Hailun Xia; Zeyu Liang 001 (ACM Multimedia, 2025)

Empowering Global Voices: A Data-Efficient, Phoneme-Tone Adaptive Approach to High-Fidelity Speech Synthesis. - Yizhong Geng; Jizhuo Xu; Zeyu Liang 001; Jinghan Yang; Xiaoyi Shi; Xiaoyu Shen 001 (CoRR, 2025)

Patch as Node: Human-Centric Graph Representation Learning for Multimodal Action Recognition. - Zeyu Liang 001; Hailun Xia; Naichuan Zheng (CoRR, 2025)

MK-SGN: A spiking graph convolutional network with multimodal fusion and knowledge distillation for skeleton-based action recognition. - Naichuan Zheng; Hailun Xia; Zeyu Liang 001; Yuchen Du (Neurocomputing, 2026)

Leveraging Spatial High-Order Modeling for Skeleton-Based Action Recognition. - Zeyu Liang 001; Hailun Xia; Naichuan Zheng; Huan Xu (IEEE Signal Process. Lett., 2026)