Author

Carlos Hinojosa

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Preprint Aug 2026

DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization

DiSCO is proposed, a zero-shot, strictly black-box defense that operates entirely at the prompt level as a plug-and-play module, requiring no model retraining, fine-tuning, or access to model internals, and can be readily applied to any text-to-image system without necessitating any changes to the model itself.

Tong Zhang, M. Alfarra, Carlos Hinojosa et al. · 0 citations

Preprint Jul 2026

HyperSafe: Inference-Time Safety Recovery for Fine-Tuned Language Models

This work proposes HyperSafe, a framework that restores safety behavior by generating a model-specific Safe Side Network (SSN) for each fine-tuned checkpoint by using layer-wise activation fingerprints to capture how fine-tuning changes the model's inner representations.

Aznaur Aliev, Carlos Hinojosa, A. Eldesokey et al. · 0 citations