Shupan Li — accepted AI-conference papers

2026

Balancing Multimodal Domain Generalization via Gradient Modulation and Projection

Hongzhao Li, Guohao Shen, Shupan Li, Mingliang Xu, Muhammad Haris Khan

AAAI 2026technical

Multimodal Domain Generalization (MMDG) leverages the complementary strengths of multiple modalities to enhance model generalization on unseen domains. A central challenge in multimodal learning is optimization imbalance, where modalities converge at different speeds during training. This imbalance

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2026

Towards Multimodal Domain Generalization with Few Labels

Hongzhao Li, Hao Dong, Hualei Wan, Shupan Li, Mingliang Xu, Muhammad Haris Khan

CVPR 2026

Multimodal models ideally should generalize to unseen domains while remaining data-efficient to reduce annotation costs. To this end, we introduce and study a new problem, Semi-Supervised Multimodal Domain Generalization (SSMDG), which aims to learn robust multimodal models from multi-source data wi

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