MATK: The Meme Analytical Tool Kit

December 11, 2023 ยท Declared Dead ยท ๐Ÿ› ACM Multimedia

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Authors Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee arXiv ID 2312.06094 Category cs.CL: Computation & Language Cross-listed cs.CV, cs.MM Citations 3 Venue ACM Multimedia Repository https://github.com/Social-AI-Studio/MATK} Last Checked 1 month ago
Abstract
The rise of social media platforms has brought about a new digital culture called memes. Memes, which combine visuals and text, can strongly influence public opinions on social and cultural issues. As a result, people have become interested in categorizing memes, leading to the development of various datasets and multimodal models that show promising results in this field. However, there is currently a lack of a single library that allows for the reproduction, evaluation, and comparison of these models using fair benchmarks and settings. To fill this gap, we introduce the Meme Analytical Tool Kit (MATK), an open-source toolkit specifically designed to support existing memes datasets and cutting-edge multimodal models. MATK aims to assist researchers and engineers in training and reproducing these multimodal models for meme classification tasks, while also providing analysis techniques to gain insights into their strengths and weaknesses. To access MATK, please visit \url{https://github.com/Social-AI-Studio/MATK}.
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