Papers with proactive safety alignment

1 papers
Be Your Own Red Teamer: Safety Alignment via Self-Play and Reflective Experience Replay (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have remarkable capabilities but are vulnerable to adversarial “jailbreak” attacks designed to bypass safety guardrails.
Approach: They propose to empower a large language model to be its own red teamer . safety self-play allows the model to act as both the Attacker and Defender .
Outcome: The proposed approach outperforms baselines trained on static adversarial datasets and establishes a new benchmark for proactive safety alignment.

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