UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian Memes
We introduce UkrMeme, a dataset of 200 organically produced Ukrainian wartime memes annotated for persuasion techniques, and PTM-UA, a Ukrainian translation of a subset of the Propaganda 950 benchmark that preserves original visual content while translating meme text.
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Key points
- Memes play a central role in modern online communication, especially in contexts of political conflict where visual and textual cues combine to convey persuasive messages.
- We study persuasive technique detection in Ukrainian memes using vision-language models (VLMs).
- We evaluate VLMs in a zero-shot prompting setup across image, text, and multimodal inputs using hierarchical F1 metrics.
- Finally, we compare Layer-wise Relevance Propagation (LRP) and model-generated token attributions and analyze the semantic categories of evidence emphasized by each explanation method.
Sources (1)
- [1]UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian MemesarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 9, 04:03 PM
We introduce UkrMeme, a dataset of 200 organically produced Ukrainian wartime memes annotated for persuasion techniques, and PTM-UA, a Ukrainian translation of a subset of the Propaganda 950 benchmark that preserves original visual content while translating meme text.
Memes play a central role in modern online communication, especially in contexts of political conflict where visual and textual cues combine to convey persuasive messages.
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