arXiv cs.CL· Nazar Andrushko, Vera Schmitt, Veronika Solopova·· 6 天前AI 评分15
UkrMeme：乌克兰语模因中的多模态可解释说服检测
UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian Memes
AI 导读
研究团队构建了 UkrMeme 数据集，包含 200 条乌克兰战时模因并标注说服技巧，同时发布 PTM-UA——Propaganda 950 基准子集的乌克兰语翻译版，保留原始图像内容仅翻译文本。研究在零样本提示下用视觉语言模型（VLM）评测图像、文本和多模态输入，采用分层 F1 指标，并对比 LRP 与模型生成 token 归因两种解释方法所强调的证据语义类别。
正文 · 原文
Abstract: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 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. 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.
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2610.13783 [cs.AI] |
| (or arXiv:2610.13783v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.13783 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Veronika Solopova [view email]
[v1]
Fri, 9 Oct 2026 16:03:27 UTC (1,714 KB)
来源：arXiv cs.CL · arxiv.org