Datasets › ToM-in-AMC

ToM-in-AMC

Introduced by Mo Yu et al. in Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind9 Nov 2022 archive 2025-07-28

ToM-in-AMC is a novel NLP benchmark, Short for Theory-of-Mind meta-learning Assessment with Movie Characters. The benchmark consists of 1,000 parsed movie scripts for this purpose, each corresponding to a few-shot character understanding task.

Source: Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind

Image Source: https://arxiv.org/pdf/2211.04684v1.pdf

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Apache-2.0 license

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • ToM-in-AMC

1 variant name, as the archive lists them.

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