othello_shuffle / README.md
jaagli's picture
Update README.md
551be40 verified
---
dataset_info:
features:
- name: step
dtype: string
- name: num_black
dtype: int64
- name: num_white
dtype: int64
- name: game_id
dtype: string
- name: curr_player
dtype: string
- name: image
dtype: image
splits:
- name: train
num_bytes: 30131459110.176
num_examples: 1247852
- name: test
num_bytes: 5614904764.9
num_examples: 233975
- name: val
num_bytes: 1889083268.197
num_examples: 78141
download_size: 34783102465
dataset_size: 37635447143.272995
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: val
path: data/val-*
license: apache-2.0
task_categories:
- text-generation
- image-classification
- image-to-text
tags:
- game
size_categories:
- 1M<n<10M
---
# Dataset Card
## Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
The dataset is derived from real Othello game records collected from [EOTHELLO](https://www.eothello.com/). It combines textual move sequences with corresponding visual board states, enabling joint modeling of language and vision in a structured, rule-based environment.
Each game consists of a sequence of 60 ± 2 moves on average, with one board image generated after every move. This results in a total of approximately 25,000 games and 1.56 million board images.
It provides two synchronized modalities:
- Text modality – move tokens representing board positions (e.g., “C4”, “E6”).
- Visual modality – RGB images depicting the full Othello board state after each move.
## Repository:
[multimodal-othello](https://github.com/shin-ee-chen/multimodal-othello)
## Statistics
| Split | Number of Games | Number of Images | Avg. Images per Game |
| ---------- | --------------- | ---------------- | -------------------- |
| Training | 20,525 | 1,247,852 | ~ 60.8 |
| Validation | 1,282 | 78,141 | ~ 60.9 |
| Test | 3,850 | 233,975 | ~ 60.8 |
| **Total** | 25,657 | 1,559,968 | ~ 60.8 |
## Intended Usage
The dataset is intended for academic research for training and/or evaluating language models.
## Citation
**Paper:** [What if Othello-Playing Language Models Could See?](https://arxiv.org/abs/2507.14520)
**BibTeX:**
```
@article{chen2025if,
title={What if Othello-Playing Language Models Could See?},
author={Chen, Xinyi and Yuan, Yifei and Li, Jiaang and Belongie, Serge and de Rijke, Maarten and S{\o}gaard, Anders},
journal={arXiv preprint arXiv:2507.14520},
year={2025}
}
```