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Toxicity identification in online multimodal environments remains a challenging task due to the complexity of contextual connections across modalities (e.g., textual and visual). In this paper, we propose a novel framework that integrates…

机器学习 · 计算机科学 2026-02-18 Rahul Garg , Trilok Padhi , Hemang Jain , Ugur Kursuncu , Ponnurangam Kumaraguru

Pre-trained language models (LMs) have been shown to memorize a substantial amount of knowledge from the pre-training corpora; however, they are still limited in recalling factually correct knowledge given a certain context. Hence, they…

As a multimodal medium combining images and text, memes frequently convey implicit harmful content through metaphors and humor, rendering the detection of harmful memes a complex and challenging task. Although recent studies have made…

计算与语言 · 计算机科学 2026-04-02 Hexiang Gu , Qifan Yu , Yuan Liu , Zikang Li , Saihui Hou , Jian Zhao , Zhaofeng He

The rapid expansion of memes on social media has highlighted the urgent need for effective approaches to detect harmful content. However, traditional data-driven approaches struggle to detect new memes due to their evolving nature and the…

计算与语言 · 计算机科学 2025-07-10 Ziyan Liu , Chunxiao Fan , Haoran Lou , Yuexin Wu , Kaiwei Deng

Memes have become a dominant form of communication in social media in recent years. Memes are typically humorous and harmless, however there are also memes that promote hate speech, being in this way harmful to individuals and groups based…

计算机视觉与模式识别 · 计算机科学 2025-04-15 Maria Tzelepi , Vasileios Mezaris

The age of social media is rife with memes. Understanding and detecting harmful memes pose a significant challenge due to their implicit meaning that is not explicitly conveyed through the surface text and image. However, existing harmful…

计算与语言 · 计算机科学 2023-12-12 Hongzhan Lin , Ziyang Luo , Jing Ma , Long Chen

In the current context where online platforms have been effectively weaponized in a variety of geo-political events and social issues, Internet memes make fair content moderation at scale even more difficult. Existing work on meme…

The prevalence of memes on social media has created the need to sentiment analyze their underlying meanings for censoring harmful content. Meme censoring systems by machine learning raise the need for a semi-supervised learning solution to…

机器学习 · 计算机科学 2023-05-17 Pham Thai Hoang Tung , Nguyen Tan Viet , Ngo Tien Anh , Phan Duy Hung

Deepfake detection technologies become vital because current generative AI models can generate realistic deepfakes, which may be utilized in malicious purposes. Existing deepfake detection methods either rely on developing classification…

计算机视觉与模式识别 · 计算机科学 2025-03-05 Tonghui Li , Yuanfang Guo , Zeming Liu , Heqi Peng , Yunhong Wang

Incorrect information poses significant challenges by disrupting content veracity and integrity, yet most detection approaches struggle to jointly balance textual content verification with external knowledge modification under collapsed…

计算与语言 · 计算机科学 2026-05-06 Zhongxing Zhang , Emily K. Vraga , Jisu Huh , Jaideep Srivastava

Internet memes have emerged as a popular multimodal medium, yet they are increasingly weaponized to convey harmful opinions through subtle rhetorical devices like irony and metaphor. Existing detection approaches, including Multimodal Large…

机器学习 · 计算机科学 2026-04-17 Wenshuo Wang , Ziyou Jiang , Junjie Wang , Mingyang Li , Jie Huang , Yuekai Huang , Zhiyuan Chang , Feiyan Duan , Qing Wang

The age of social media is flooded with Internet memes, necessitating a clear grasp and effective identification of harmful ones. This task presents a significant challenge due to the implicit meaning embedded in memes, which is not…

计算与语言 · 计算机科学 2024-01-25 Hongzhan Lin , Ziyang Luo , Wei Gao , Jing Ma , Bo Wang , Ruichao Yang

In the digital world, memes present a unique challenge for content moderation due to their potential to spread harmful content. Although detection methods have improved, proactive solutions such as intervention are still limited, with…

计算与语言 · 计算机科学 2024-06-11 Prince Jha , Raghav Jain , Konika Mandal , Aman Chadha , Sriparna Saha , Pushpak Bhattacharyya

Hateful meme detection presents a significant challenge as a multimodal task due to the complexity of interpreting implicit hate messages and contextual cues within memes. Previous approaches have fine-tuned pre-trained vision-language…

计算与语言 · 计算机科学 2025-02-18 Ming Shan Hee , Roy Ka-Wei Lee

The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audio content, but typically in isolation. Yet, harmful content…

Memes act as cryptic tools for sharing sensitive ideas, often requiring contextual knowledge to interpret. This makes moderating multimodal memes challenging, as existing works either lack high-quality datasets on nuanced hate categories or…

计算与语言 · 计算机科学 2024-12-31 Palash Nandi , Shivam Sharma , Tanmoy Chakraborty

Memes are widely used for humor and cultural commentary, but they are increasingly exploited to spread hateful content. Due to their multimodal nature, hateful memes often evade traditional text-only or image-only detection systems,…

计算机视觉与模式识别 · 计算机科学 2025-04-24 Ali Anaissi , Junaid Akram , Kunal Chaturvedi , Ali Braytee

Among the various modes of communication in social media, the use of Internet memes has emerged as a powerful means to convey political, psychological, and socio-cultural opinions. Although memes are typically humorous in nature, recent…

Memes are used for spreading ideas through social networks. Although most memes are created for humor, some memes become hateful under the combination of pictures and text. Automatically detecting the hateful memes can help reduce their…

计算机视觉与模式识别 · 计算机科学 2020-12-08 Yi Zhou , Zhenhao Chen

Memes are one of the most popular types of content used in an online disinformation campaign. They are primarily effective on social media platforms since they can easily reach many users. Memes in a disinformation campaign achieve their…

计算与语言 · 计算机科学 2024-04-09 Shreenaga Chikoti , Shrey Mehta , Ashutosh Modi
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