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cs.LG2026
UniFed-VLM: Federated Instruction Tuning for Vision-Language Models with Multiple Heterogeneity
Pengyu Wang, Baochen Xiong, Xiaoshan Yang +4
Vision-Language Models (VLMs) have demonstrated strong performance in multimodal understanding and generation. However, fine-tuning of VLMs typically relies on centralized data, wh…
cs.LG2026
A Step Toward Federated Pretraining of Multimodal Large Language Models
Baochen Xiong, Yifan Xu, Xiaoshan Yang +3
The rapid evolution of Multimodal Large Language Models (MLLMs) is bottlenecked by the saturation of high-quality public data, while vast amounts of diverse multimodal data remain…