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cs.LG2026
Golden Handcuffs make safer AI agents
Aram Ebtekar, Michael K. Cohen
Reinforcement learners can attain high reward through novel unintended strategies. We study a Bayesian mitigation for general environments: we expand the agent's subjective reward…
cs.LG2025
Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Nevan Wichers, Aram Ebtekar, Ariana Azarbal +8
Large language models are sometimes trained with imperfect oversight signals, leading to undesired behaviors such as reward hacking and sycophancy. Improving oversight quality can…
cs.LG2025★ 1 cited
Toward Universal Laws of Outlier Propagation
Aram Ebtekar, Yuhao Wang, Dominik Janzing
When a variety of anomalous features motivate flagging different samples as outliers, Algorithmic Information Theory (AIT) offers a principled way to unify them in terms of a sampl…