Author

Qinghua Hu

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#machine learning Preprint Aug 2026

Fusion Anything: A Generalized Multimodal Foundation Model

Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefined modalities (e.g., vision, text and audio) and single task, making it difficult to quickly adapt to new downstream applications. Therefore, a natural yet aggressive que...

Hui-Zi Cui, Zong-Bo Han, Chen Ding et al. · 0 citations

Jul 2026

LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation

This paper uses a vision-language model (VLM) to compute similarities between target samples and text labels, including those for unknown classes generated by prompting a large language model, and proposes a framework that leverages foundation models (LFM) for SF-UniDA.

Jing Li, Pan Liu, Meng Zhao et al. · IEEE transactions on multime... · 0 citations