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Mohamed bin Zayed University of Artificial Intelligence
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A simple training framework boosts pixel-level tampering detection performance in VLMs by over 26%, showcasing the power of balanced sampling and late-injection strategies.
LLMs can be surprisingly effective vision models, even without full fine-tuning, thanks to inherent foundational properties in specific layers that transfer via a simple "random label bridge training" technique.
