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BAITBENCH: Measuring Agent Reward Hacking with Optional Shortcuts Planted in ML Tasks
LLM agents are increasingly used to run autonomous ML experiments, iterating on target metrics with little human oversight. Prior work has documented reward hacking in these environments, bringing into question the validity of produced research and the broader safety case for AI R&D. Existing benchm
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