---
license: cc-by-nc-4.0
task_categories:
- image-text-to-text
tags:
- hateful-memes
- multimodal
- retrieval-augmented-generation
- lmm
---

# Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection Datasets

This repository contains the datasets used in the paper [Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection](https://huggingface.co/papers/2502.13061).

[Project Page](https://rgclmm.github.io/) | [Code](https://github.com/JingbiaoMei/RGCL)

## Abstract
Recent advances in Large Multimodal Models (LMMs) have shown promise in hateful meme detection, but face challenges like sub-optimal performance and limited out-of-domain generalization. This work proposes a robust adaptation framework for hateful meme detection that enhances in-domain accuracy and cross-domain generalization while preserving the general vision-language capabilities of LMMs. Our approach achieves improved robustness under adversarial attacks compared to supervised fine-tuning (SFT) models and state-of-the-art performance on six meme classification datasets, outperforming larger agentic systems. Additionally, our method generates higher-quality rationales for explaining hateful content, enhancing model interpretability.

## Dataset Preparation
The datasets consist of image data and corresponding annotation data.

### Image data
Copy images into `./data/image/dataset_name/All` folder.
For example: `./data/image/FB/All/12345.png`, `./data/image/HarMeme/All`, `./data/image/Propaganda/All`, etc..

### Annotation data
Copy `jsonl` annotation file into `./data/gt/dataset_name` folder.

## Sample Usage
To generate CLIP embeddings for the datasets prior to training, you can use the provided script as follows:

```shell
python3 src/utils/generate_CLIP_embedding_HF.py --dataset "FB"
python3 src/utils/generate_CLIP_embedding_HF.py --dataset "HarMeme"
```

Similarly, to generate ALIGN embeddings:

```shell
python3 src/utils/generate_ALIGN_embedding_HF.py --dataset "FB"
python3 src/utils/generate_ALIGN_embedding_HF.py --dataset "HarMeme"
```

## Citation
If our work helped your research, please kindly cite our papers:

```
@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 }
```