Papers with generation of guardrail models

1 papers
On Guardrail Models’ Robustness to Mutations and Adversarial Attacks (2025.findings-emnlp)

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Challenge: generative AI systems providing unsafe information has raised significant concerns, emphasizing the need for safety guardrails.
Approach: They propose to evaluate 15 state-of-the-art guardrail models to assess their robustness to input mutations and adversarial attacks designed to bypass models’ safety alignment.
Outcome: The proposed models are robust to input mutations and adversarial attacks that bypass models’ safety alignment.

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