Datasets:
File size: 2,149 Bytes
b9aef89 608b32f b9aef89 608b32f b9aef89 d914574 608b32f b9aef89 608b32f b9aef89 608b32f b9aef89 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
---
license: cc-by-nc-4.0
task_categories:
- image-text-to-text
language:
- en
tags:
- hateful-memes
- multimodal
- retrieval-augmented-generation
- vision-language
---
# RGCL Dataset Resources
This repository contains the dataset for the paper [Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning](https://aclanthology.org/2024.acl-long.291).
The linked HF paper is [Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning](https://huggingface.co/papers/2311.08110)
This provides the sparse retrieval dataset for the RGCL paper.
For more details and related resources:
- **Paper**: [Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning](https://aclanthology.org/2024.acl-long.291)
- **Code (GitHub)**: https://github.com/JingbiaoMei/RGCL
- **Project Page**: https://rgclmm.github.io/
### Citation
If you use this dataset in your research, please kindly cite the corresponding paper:
```bibtex
@inproceedings{RGCL2024Mei,
title = "Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning",
author = "Mei, Jingbiao and
Chen, Jinghong and
Lin, Weizhe and
Byrne, Bill and
Tomalin, Marcus",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-long.291",
doi = "10.18653/v1/2024.acl-long.291",
pages = "5333--5347"
}
@article{RAHMD2025Mei,
title={Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection},
url={http://arxiv.org/abs/2502.13061},
DOI={10.48550/arXiv.2502.13061},
note={arXiv:2502.13061 [cs]},
number={arXiv:2502.13061},
publisher={arXiv},
author={Mei, Jingbiao and Chen, Jinghong and Yang, Guangyu and Lin, Weizhe and Byrne, Bill},
year={2025},
month=may
}
``` |