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Research Training data can be reconstructed from foundation model weights with significantly higher accuracy than previously reported, with implications for GDPR compliance and IP protection.
Academic and industry research shaping the future of AI security, attack, and defence.
Training data can be reconstructed from foundation model weights with significantly higher accuracy than previously reported, with implications for GDPR compliance and IP protection.
Vision-language models are highly susceptible to adversarial image perturbations, with attacks transferring across models (GPT-4V, Gemini Pro, LLaVA) at 43-74% success rates.
Query-efficient model extraction attacks against commercial LLM APIs: how adversaries reconstruct a functional shadow model using only input-output pairs, and how to defend.