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News/Mitigating Reward Hacking in Realistic Scenarios Through Representation Engineering
arxiv
PublishedOctober 22, 2026 at 4:00 AM

Mitigating Reward Hacking in Realistic Scenarios Through Representation Engineering

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arXiv:2610.29129v1 Announce Type: new Abstract: Reward hacking is a major problem in current production machine learning systems, resulting in costly and dangerous failures. Here we study how to monitor for and mitigate reward hacking in realistic settings, including tool calls and long contexts. We

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