Papers with safety alignment of Large language models

1 papers
Enhancing the Transferability of Jailbreak Attacks on Large Language Models via Exploiting Reparameterization Invariance (2026.acl-long)

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Challenge: Existing token-level attacks have shown efficacy on open-source models but suffer from poor cross-model transferability.
Approach: They propose a framework to improve cross-model transferability by modifying model parameters and generating update directions according to differences in output distributions rather than parameter-space distances.
Outcome: The proposed framework improves cross-model transferability and success rates on open-source models.

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