arXiv AI
Jev-ToM: Evaluating Theory of Mind in Typed Decision Models
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Jev-ToM: Evaluating Theory of Mind in Typed Decision Models
Jev-ToM evaluates Theory of Mind (ToM) in typed decision models, comparing five such models and seven generative baselines on 11,117 English text questions from nine ToM benchmarks across six capability groups. The TypeSafe Jev model achieves 73.2% source‑balanced accuracy, ranking first or second in all six capabilities, including leading beliefs, goals/desires/intentions, and emotions. Other typed models show distinct strengths, and resource comparisons suggest Jev could reduce cost and waiting time for repeated ToM selection, while confidence‑based selection and candidate expansion reveal task‑dependent challenges and opportunities for improvement.
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