AHA-Memes: First Large-Scale Arabic Hateful Meme Benchmark with Fine-Grained Labels

Researchers released AHA-Memes, a new benchmark for detecting hate in Arabic memes. This dataset is the first of its kind to focus specifically on Arabic hateful memes, offering fine-grained, multi-label annotations. Hateful memes are a growing form of online harm, where hostile intent is conveyed through a combination of images, text, cultural references, and implicit targets. While progress has been made in detecting hateful memes in high-resource languages, Arabic has largely been overlooked, with existing resources focusing mainly on propaganda or broad harmful-content labels.

## Fine-Grained Multi-Label Annotations for Arabic Memes AHA-Memes provides a comprehensive dataset for training and evaluating AI models to detect hate in Arabic memes. The dataset includes detailed annotations that go beyond simple binary labels, capturing the nuances of hate speech in memes. This includes identifying specific types of hate, such as racism, sexism, or religious discrimination, as well as the targets of the hate. The dataset is designed to help researchers and developers create more accurate and nuanced models for detecting and mitigating hate speech in Arabic memes.

## First Large-Scale Arabic Hateful Meme Benchmark AHA-Memes is the first large-scale Arabic hateful meme benchmark with fine-grained, multi-label annotations. The dataset includes a diverse range of memes, covering various forms of hate speech and cultural contexts. This granularity allows for more precise detection and understanding of hateful content, which is crucial for developing effective countermeasures. The dataset is also designed to be scalable, allowing for future expansions and updates as new forms of hate speech emerge.

## Impact on Online Safety for Arabic-Speaking Communities Hateful memes can have a significant impact on individuals and communities, spreading harmful ideologies and inciting violence. By improving the detection of hate in Arabic memes, AHA-Memes can help platforms and moderators identify and remove harmful content more effectively. This is particularly important in regions where Arabic is widely spoken, as it can help protect vulnerable communities from online harassment and discrimination. For everyday users, this means a safer and more inclusive online environment, where hate speech is quickly identified and addressed.

## Accessing the AHA-Memes Dataset If you are a researcher or developer interested in combating hate speech, you can explore the AHA-Memes dataset and use it to train your models. The dataset is available on arXiv, and you can access it by visiting the source link provided. For everyday users, staying informed about the efforts to combat hate speech and supporting platforms that prioritize safety and inclusivity can make a significant difference.