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Lass Najmuldeen

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#artificial intelligence Preprint Oct 2026

Exploring Jailbreak Vulnerability Across Depth-Based Dynamic Inference in Large Language Models

This paper makes the following key observations: Shallow exits are consistently more robust to jailbreak attacks than deeper ones; Exit depth affects how easily the adversarial suffix can be optimized, with deeper exits reaching lower attack loss; and adversarial suffixes affect utility uniformly across exit depths.

Lass Najmuldeen, Seyedhamidreza Mousavi · 0 citations

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