pmovva/rebus-puzzles

Rebus Dataset

The Rebus Dataset is a collection of 221 rebus puzzle images, each annotated with corresponding textual solutions and metadata.
It was introduced as part of the paper:

Reasoning Riddles: How Explainability Reveals Cognitive Limits in Vision-Language Models
Prahitha Movva, 2025
arXiv:2510.02780

The dataset is designed to support research in visual reasoning, multimodal interpretability, and cognitive evaluation of vision–language models.

---

Dataset Structure

• Images: 221 rebus puzzles (0001.jpg-0221.jpg)
• Metadata: Provided in rebus_dataset.csv with the following fields:
  • filename: image filename (e.g., 0001.jpg)
  • solution: canonical textual solution to the rebus
  • alternate_solutions: list of acceptable alternate phrasings
  • category: one or more cognitive or linguistic transformation types (e.g., Spatial Encoding, Phonetic Transformation)
  • exact_spelling: whether the image spelling exactly matches the intended phrase
  • theme: high-level semantic group (e.g., idioms and expressions, food and cuisine, common phrases)

---

Example Entry

filename	solution	alternate_solutions	category	exact_spelling	theme
0001.jpg	You're on mute	["You are on mute"]	Spatial Encoding, Absence Reasoning	No	common_phrase

---

Usage

Load the dataset programmatically using the 🤗 Datasets library:

from datasets import load_dataset

dataset = load_dataset("pmovva/rebus-puzzles")
example = dataset["train"][0]
example["image"].show()
print(example)

If you use this dataset in your research or publications, please cite the accompanying paper:

@inproceedings{
movva2025reasoning,
title={Reasoning Riddles: How Explainability Reveals Cognitive Limits in Vision-Language Models},
author={Prahitha Movva},
booktitle={The First Workshop on the Application of LLM Explainability to Reasoning and Planning},
year={2025},
url={https://openreview.net/forum?id=c5FgKxcwMP}
}