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Queen Mary University of London
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Tailoring evaluation taxonomies for each vision-language model reveals a 32% improvement in performance and uncovers unique model blind spots that global assessments miss.
Achieving competitive video super-resolution quality with just 11.25% of the usual trainable parameters, LiteVSR redefines efficiency in adapting frozen diffusion models.
