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Multimodal unlearning could revolutionize how we handle sensitive data in AI, enabling targeted removal without sacrificing model performance.
VLMs can now be certified for robustness against semantic variations without the burden of extra data, transforming how we assess model reliability in real-world applications.
Achieve significantly better code generation and mathematical problem solving from diffusion language models with a simple, training-free sampling tweak that encourages diversity.
