Study: Shallow Early Exit Is More Robust Against Jailbreaks Than Deep Early Exit
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An arXiv paper released on October 11, 2026 examines the relationship between depth-based dynamic inference in large language models and jailbreak robustness. The study tests the vulnerability of each early-exit depth via adversarial suffix optimization, finding that shallow early exits are consistently more robust to jailbreak attacks than deep ones: early-exit depth affects the optimization difficulty of adversarial suffixes, with deeper early exits achieving lower attack loss; meanwhile, the impact of adversarial suffixes on model utility is consistent across early-exit depths. The authors state these observations can help design dynamic inference methods more robust to jailbreaks, and the code has been made public on GitHub.
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- Exploring Jailbreak Vulnerability Across Depth-Based Dynamic Inference in Large Language Models
arXiv · 2026-10-10 · Deep reading
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- arXiv: Adversarial Attacks, Backdoors & PoisoningInvestigating Jailbreak Vulnerability in Depth-Based Dynamic Reasoning of Large Language Models
The paper examines the relationship between depth-based dynamic reasoning and jailbreak robustness in large language models, finding that shallow early exits are consistently more resistant to jailbreak attacks than deeper ones. The study optimizes adversarial suffixes to test the vulnerability of each early exit depth, finding that early exit depth affects the optimization difficulty of adversarial suffixes, with deeper early exits achieving lower attack loss. The impact of adversarial suffixes on model utility is consistent across early exit depths. The authors state these observations can help design dynamic reasoning methods more resistant to jailbreaks, and code has been made public on GitHub.