Brief

Researchers have developed a novel method for detecting reward hacking in AI systems using a small transformer encoder. This encoder maps trajectories to a space where distance approximates signal differences, achieving high accuracy in identifying reward hacking. The approach is significantly more cost-effective than using large language models as judges and demonstrates that the encoder relies on more than just natural language reasoning. AI