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Large vision-language models (LVLMs) exhibit strong multimodal in-context learning (ICL) capabilities, yet this ability degrades substantially as model size decreases. Knowledge distillation offers a natural way to bridge this gap, but existing methods primarily align output distributions or hidden representations dire...
This work introduces TempFinRAG, a point-in-time evaluation protocol built from public filings and XBRL facts, and introduces TempFinQA, a point-in-time evaluation protocol built from public filings and XBRL facts, and evaluates the framework on complementary evidence-grounded, numerical, conversational, and multi-tabl...
This work injects two complementary semantic priors into Visual prompt tuning, a cascaded scheme that integrates both priors throughout ViT adaptation, and proposes a cascaded scheme that integrates both priors throughout ViT adaptation.
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