OSCToM uses RL-guided generation with an extended DSL and surrogate models to create nested belief conflict tasks, raising FANToM accuracy from 0.2% to 76% while being 6x more efficient.
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OSCToM: RL-Guided Adversarial Generation for High-Order Theory of Mind
OSCToM uses RL-guided generation with an extended DSL and surrogate models to create nested belief conflict tasks, raising FANToM accuracy from 0.2% to 76% while being 6x more efficient.