Datasets › MMToM-QA

MMToM-QA (Multimodal Theory of Mind Question Answering)

Introduced by Chuanyang Jin et al. in MMToM-QA: Multimodal Theory of Mind Question Answering16 Jan 2024 archive 2025-07-28

MMToM-QA is the first multimodal benchmark to evaluate machine Theory of Mind (ToM), the ability to understand people's minds. MMToM-QA consists of 600 questions. Each question is paired with a clip of the full activity in a video (as RGB-D frames), as well as a text description of the scene and the actions taken by the person in that clip. All questions have two choices. The questions are categorized into seven types, evaluating belief inference and goal inference in rich and diverse situations. Each belief inference type has 100 questions, totaling 300 belief questions; each goal inference type has 75 questions, totaling 300 goal questions. The questions are paired with 134 videos of a person looking for daily objects in household environments.

Benchmarks archive 2025-07-28

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Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • MMToM-QA

1 variant name, as the archive lists them.

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