Papers with Augmented objectives

1 papers
Augmented Adversarial Trigger Learning (2025.findings-naacl)

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Challenge: Gradient optimization-based adversarial attack methods can generate jailbreak prompts or leak system prompts.
Approach: They propose an algorithm that enhances negative log-likelihood loss and augments it with auxiliary loss.
Outcome: The proposed approach outperforms current state-of-the-art techniques in nearly 100% of attacks while requiring 80% fewer queries.

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