Proposed novel method achieves significant token reduction in vision-language models, suggesting efficiency gains.
AbstractIn this paper it is proposed a novel method that aims to achieve human-like vision (interms of efficiency) for VLMs. In doing so, an almost x10 token input reduction is achieved,and the training time is only 2-5 minutes on low end gpu hardware. Though, additionally,limitations of this method are presented.
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L. Monaco (2026) studied this question.
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