This repository contains the code necessary to create the collective neuro-symbolic benchmark suite described in the paper: Visual Sudoku Puzzle Classification: A Suite of Collective Neuro-Symbolic Tasks.
Pre-generated data is made available with 4x4 and 9x9 puzzles. 11 splits are provided for each configuration. The first 10 splits (01 - 10) are to be scored, while the final split (11) is free to be used as the experimenter sees fit. For convenience, the data has been split up by size, task, and datasets.
All the data is available in this directory: https://linqs-data.soe.ucsc.edu/public/datasets/ViSudo-PC/v01/
Shortcuts to the basic task datasets are provided here:
Data Source | 4x4 | 9x9 |
---|---|---|
MNIST | Basic 4x4 MNIST | Basic 9x9 MNIST |
EMNIST | Basic 4x4 EMNIST | Basic 9x9 EMNIST |
FMNIST | Basic 4x4 FMNIST | Basic 9x9 FMNIST |
KMNIST | Basic 4x4 KMNIST | Basic 9x9 KMNIST |
We also provide some sample datasets that only cover one specific setting and split:
Has Overlap? | 4x4 | 9x9 |
---|---|---|
Without Overlap | Sample 4x4 No Overlap | Sample 9x9 No Overlap |
With Overlap | Sample 4x4 Overlap | Sample 9x9 Overlap |
The ./scripts/generate-split.py
script can be used to generate a split of puzzles.
All available options can be viewed using --help
:
./scripts/generate-split.py --help
To reference this work, please cite:
@inproceedings{augustine:nesy22,
title = {Visual Sudoku Puzzle Classification: A Suite of Collective Neuro-Symbolic Tasks},
author = {Eriq Augustine and Connor Pryor and Charles Dickens and Jay Pujara and William Yang Wang and Lise Getoor},
booktitle = {International Workshop on Neural-Symbolic Learning and Reasoning (NeSy)},
year = {2022},
_publisher = {CEUR},
address = {Windsor, United Kingdom},
}