An LLM-augmented Bayesian inverse planning model, LAIP, generates hypotheses and action likelihoods, then uses Bayes' rule to infer agent preferences, outperforming LLM-only baselines.
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Towards Machine Theory of Mind with Large Language Model-Augmented Inverse Planning
An LLM-augmented Bayesian inverse planning model, LAIP, generates hypotheses and action likelihoods, then uses Bayes' rule to infer agent preferences, outperforming LLM-only baselines.