2d ago

New Paper Shows Reward Models Learn 9x Faster Than Dynamics Simulators in RLHF

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Ravid Shwartz ZivRS#612@ZIV_RAVIDOPGrigory SapunovGSGrigory Sapunov|@CHE_SHR_CAT

1/ RLHF practitioners are wasting budget. If you treat dynamics and rewards as a monolithic world model, your data allocation is wrong. Reward models learn ~9x faster than dynamics simulators. 🧵

12:55 PM · May 17, 2026 View on X

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Users see the new paper showing reward models learn 9x faster than dynamics simulators in RLHF as a big deal because it supports scaling world models by grounding empirical laws without heuristic hyperparameter tuning.

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