86 citations · 107 across the 10 of their papers we have counts for
5 papers · 1 filter
ArGuard Shared Task: Harmful Content Detection in Arabic Memes and LLM Prompts
Firoj Alam, Md. Rafiul Biswas, Mohamed Bayan Kmainasi +5
ArGuard is a shared task on harmful content detection in Arabic memes and LLM prompts. It includes two tracks: Track A focuses on multimodal hate detection in Arabic memes, while T…
AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes
Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Abul Hasnat +3
Hateful memes are a growing form of multimodal online harm, where hostile intent is often conveyed through the joint interpretation of images, text, cultural references, and implic…
Adapting Reinforcement Learning with Chain-of-Thought Supervision for Explainable Detection of Hateful and Propagandistic Memes
Mohamed Bayan Kmainasi, Mucahid Kutlu, Ali Ezzat Shahroor +2
Hateful and propagandistic memes exploit the interplay between images and text to convey harmful intent that neither modality reveals alone. Although thinking-based multimodal larg…
Can Thinking Models Think to Detect Hateful Memes?
Mohamed Bayan Kmainasi, Mucahid Kutlu, Ali Ezzat Shahroor +2
Hateful memes often require compositional multimodal reasoning: the image and text may appear benign in isolation, yet their interaction conveys harmful intent. Although thinking-b…
MemeLens: Multilingual Multitask VLMs for Memes
Ali Ezzat Shahroor, Mohamed Bayan Kmainasi, Abul Hasnat +4
Memes are a dominant medium for online communication and manipulation because meaning emerges from interactions between embedded text, imagery, and cultural context. Existing meme…