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Learning to Attack and Defend: Adaptive Red Teaming of Language Models via GRPO
Language model safety must continually adapt to evolving attacks. Recent works have demonstrated that reinforcement learning can be used to train stronger attacker and defender models in tandem by applying PPO-style self-play and DPO-style online preference optimization. In this work, we explore the
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