RoMemes: A multimodal meme corpus for the Romanian language
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Abstract (arXiv)
Memes are becoming increasingly more popular in online media, especially in social networks. They usually combine graphical representations (images, drawings, animations or video) with text to convey powerful messages. In order to extract, process and understand the messages, AI applications need to employ multimodal algorithms. In this paper, we introduce a curated dataset of real memes in the Romanian language, with multiple annotation levels. Baseline algorithms were employed to demonstrate the usability of the dataset. Results indicate that further research is needed to improve the processing capabilities of AI tools when faced with Internet memes.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 26 references that are in the map. First posted on arXiv 20 Oct 2024.
Builds on
6 of 26 references.
References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2016Bag of Tricks for Efficient Text Classificationcited by 876
- 2020The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memescited by 490
- 2023MemeCap: A Dataset for Captioning and Interpreting Memescited by 46
- 2021Distilling the Knowledge of Romanian BERTs Using Multiple Teacherscited by 13
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2026"Inctelegi Romanecste?'' A Recipe for Romanian Vision-Language Models29 May 2026
- 2026MemeLens: Multilingual Multitask VLMs for Memes18 Jan 2026
- 2025Large Multimodal Models for Low-Resource Languages: A Survey8 Feb 2025