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cs.LG2026
BAITBENCH: Measuring Agent Reward Hacking with Optional Shortcuts Planted in ML Tasks
Pradyumna Shyama Prasad, Meiri Anto, Leon Eshuijs +3
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 enviro…
cs.LG2026
Safety Training Modulates Harmful Misalignment Under On-Policy RL, But Direction Depends on Environment Design
Leon Eshuijs, Shihan Wang, Antske Fokkens
Specification gaming under Reinforcement Learning (RL) is known to cause LLMs to develop sycophantic, manipulative, or deceptive behavior, yet the conditions under which this occur…