---
# Template:
# https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1
size_categories:
- 10K<n<100K
task_categories:
- multiple-choice
configs:
- config_name: tom-in-amc
  default: true
  data_files:
  - split: train
    path: data/train.parquet
  - split: dev
    path: data/dev.parquet
  - split: test
    path: data/test.parquet
  - split: dev_human_subset
    path: data/dev_human_subset.parquet
  - split: test_human_subset
    path: data/test_human_subset.parquet
license: apache-2.0
language:
- en
tags:
- theory-of-mind
---

# Dataset Card for <span style="font-variant: small-caps;">ToM-in-AMC</span>

The dataset consists of ∼1,000 parsed movie scripts from [IMSDb](https://imsdb.com), each corresponding to a character understanding task.

![icml-2024-poster](https://icml.cc/media/PosterPDFs/ICML%202024/33732.png)

## Dataset Description

- **Homepage:** https://shunchizhang.github.io/tom-in-amc/
- **Repository:** https://github.com/ShunchiZhang/ToM-in-AMC
- **Paper:** https://huggingface.co/papers/2211.04684
- **Point of Contact:** moyumyu@global.tencent.com

## Citation

**BibTeX:**

```bibtex
@inproceedings{yu2024few,
  title = {Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind},
  author = {Yu, Mo and Wang, Qiujing and Zhang, Shunchi and Sang, Yisi and Pu, Kangsheng and Wei, Zekai and Wang, Han and Xu, Liyan and Li, Jing and Yu, Yue and Zhou, Jie},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning},
  year = {2024}
}
```

## Dataset Card Authors

[Mo Yu](https://sites.google.com/site/moyunlp/)\*, [Qiujing Wang](https://qiujing.wang/)\*, [Shunchi Zhang](https://shunchizhang.github.io/)\*, [Yisi Sang](https://yisisang.github.io/), [Kangsheng Pu](https://www.linkedin.com/in/kspu/), [Zekai Wei](https://www.linkedin.com/in/zekai-wei-a053031a3/), [Han Wang](https://hannight.github.io/), [Liyan Xu](https://lxucs.github.io/), [Jing Li](https://web.njit.edu/~jingli/), [Yue Yu](https://www.lehigh.edu/~yuy214/), and [Jie Zhou](https://openreview.net/profile?id=~Jie_Zhou8).