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Jingbiao/rgcl-sparse-retrieval

RGCL Dataset Resources This repository contains the dataset for the paper Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning. The linked HF paper is Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning 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 Code (GitHub):… See the full description on the dataset page: https://huggingface.co/datasets/Jingbiao/rgcl-sparse-retrieval.

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RGCL Dataset Resources

This repository contains the dataset for the paper Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning.

The linked HF paper is Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning

This provides the sparse retrieval dataset for the RGCL paper.

For more details and related resources:

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
}