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Modeling Human Beliefs about AI Behavior for Scalable Oversight
We explain how modeling human evaluator beliefs about AI behavior can help to better interpret their feedback.
Leon Lang, Patrick Forré
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Modeling Human Beliefs about AI Behavior for Scalable Oversight
Factored space models: Towards causality between levels of abstraction
We develop a new foundation for a theory of causality, based on factored space models
Scott Garrabrant, Matthias Georg Mayer, Magdalena Wache, Leon Lang, Sam Eisenstat, Holger Dell
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Factored space models: Towards causality between levels of abstraction
The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret
We theoretically analyze to what extent an error in a learned reward function translates into regret of resulting policies
Lukas Fluri, Leon Lang, Allesandro Abate, Patrick Forré, David Krueger, Joar Skalse
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The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret
Abstract Markov Random Fields
We use the recently generalized Hu Theorem to develop a theory of purely abstract Markov random fields.
Leon Lang, Clélia de Mulatier, Rick Quax, Patrick Forré
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Abstract Markov Random Fields