File size: 2,382 Bytes
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license: mit
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: image
dtype: image
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': sarcastic
- name: explanation
dtype: string
- name: is_ocr
dtype: bool
splits:
- name: train
num_bytes: 333867120
num_examples: 2983
- name: validation
num_bytes: 19589769
num_examples: 175
- name: test
num_bytes: 38841746
num_examples: 352
download_size: 390979603
dataset_size: 392298635
language:
- en
tags:
- Sarcasm
- Multimodal
- Multimodal-sarcasm
- sarcasm-explanation
---
# MuSe: Multimodal Sarcasm Explanation (Reformatted)
This repository provides a Hugging Face-compatible version of the **MuSe (MORE)** dataset.
## Dataset Description
- **Original Authors:** LCS2-IIITD (Shweta Desai, et al.)
- **Original Source:** [GitHub Repository](https://github.com/LCS2-IIITD/Multimodal-Sarcasm-Explanation-MuSE)
- **Paper:** [Nice perfume. How long did you marinate in it? Multimodal Sarcasm Explanation (AAAI 2022)](https://ojs.aaai.org/index.php/AAAI/article/view/21311)
## Modifications in this version
To make the dataset easier to use with the `datasets` library, the following changes were made:
1. **Unified Schema:** Merged separate OCR and Non-OCR files into a single `test` split.
2. **Metadata Flags:** Added an `is_ocr` (boolean) column to distinguish between image types.
3. **Image Integration:** Converted image paths into a native Hugging Face `Image` feature for direct loading.
4. **Labeling:** Explicitly labeled all samples as "sarcastic" to match standard classification formats.
## Citation
If you use this dataset in your research, please cite the original work:
@inproceedings{desai2022nice,
title={Nice perfume. How long did you marinate in it? Multimodal Sarcasm Explanation},
author={Desai, Shweta and Pawar, Tanmay and Shah, Parth and Mittal, Akshat and Das, Amitava and Shah, Rajiv Ratn and others},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
year={2022}
}
## License
This dataset is distributed under the **MIT License**, as per the original source repository. |