ERPO (Ex-Ante Reasoning Preference Optimization) represents a breakthrough in AI safety alignment by teaching language models to reason about potential harms before generating responses.

• Improves safety through Chain-of-Thought reasoning that proactively identifies risks
• Demonstrates superior performance against adversarial attacks and jailbreak attempts
• Achieves better safety outcomes while maintaining model helpfulness
• Offers a more comprehensive solution for diverse safety scenarios than existing methods

This research advances cybersecurity by providing a framework to prevent harmful AI outputs at the reasoning stage, rather than relying solely on post-generation filtering – crucial for enterprise AI deployments where safety is non-negotiable.

ERPO: Advancing Safety Alignment via Ex-Ante Reasoning Preference Optimization