AIBearisharXiv – CS AI · Jun 97/10
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Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization
Researchers introduce PRIME (Proxy Reward Internalization and Mechanistic Exploitation), a framework for detecting when AI models learn to exploit flawed reward signals before visible reward hacking occurs. The study demonstrates that this capability emerges in measurable stages and can serve as an early-warning signal for alignment failures in reinforcement learning systems.