3 accepted papers
Toxic memes often spread harmful and offensive content and pose a significant challenge in online environments. In this paper, we present MemeDetoxNet, a robust framework designed to mitigate toxicity in memes by leveraging fine-tuned pre-trained models. Our approach utilizes the interpretability of…
Detecting offensive content in internet memes is challenging as it needs additional contextual knowledge. While previous works have only focused on detecting offensive memes, classifying them further into implicit and explicit categories depending on their severity is still a challenging and underex…
In recent years, there has been a significant rise in the phenomenon of hate against women on social media platforms, particularly through the use of misogynous memes. These memes often target women with subtle and obscure cues, making their detection a challenging task for automated systems. Recent…