{
 "id": "QCRI/MemeReason",
 "owner": "QCRI",
 "name": "MemeReason",
 "downloads": 80,
 "likes": 0,
 "last_modified": "2026-09-21T06:30:46.000Z",
 "stated_licence": "cc-by-nc-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-classification",
  "visual-question-answering",
  "text-generation"
 ],
 "citation": "@inproceedings{kmainasi2026can,\n  title     = {Can Thinking Models Think to Detect Hateful Memes?},\n  author    = {Kmainasi, Mohamed Bayan and Kutlu, Mucahid and Ezzat Shahroor, Ali\n               and Hasnat, Abul and Alam, Firoj},\n  booktitle = {Companion Proceedings of the ACM Web Conference 2026},\n  pages     = {935--944},\n  year      = {2026}\n}\n\n@article{kmainasi2026adapting,\n  title = {Adapting reinforcement learning with chain-of-thought supervision for explainable detection of hateful and propagandistic memes},\n  journal = {Machine Learning with Applications},\n  pages = {101003},\n  year = {2026},\n  issn = {2666-8270},\n  doi = {https://doi.org/10.1016/j.mlwa.2026.101003},\n  url = {https://www.sciencedirect.com/science/article/pii/S2666827026001684},\n  author = {Kmainasi, Mohamed Bayan and Kutlu, Mucahid and Shahroor, Ali Ezzat and Hasnat, Abul and Alam, Firoj},\n  keywords = {Hateful meme detection, Propaganda detection, Multimodal large language models, Reinforcement learning, Chain-of-thought reasoning},\n}",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.",
 "revision": "55b5b7f51a7236012fc79e02e3c20bd4a254e2b2",
 "stated_evidence": "https://huggingface.co/datasets/QCRI/MemeReason/blob/55b5b7f51a7236012fc79e02e3c20bd4a254e2b2/README.md",
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}