Preprint
Aug 2026
LLaVAFlow: Preserving Latent Alignment Flow for Parameter-Efficient Multimodal Fine-Tuning
This work argues that cross-modal alignment is implicitly captured in the information-compression trajectory, and proposes LLaVAFlow, an information-theoretic distillation framework that preserves alignment flow and enhances both downstream performance and generalization.
Mu-Yao Yuan, Mu-Yan Jiao, Jiang-Yong Ying et al.
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