A Multimodal Framework for the Detection of Hateful Memes

Understand

An increasingly common expression of online hate speech is multimodal in nature and comes in the form of memes.

• Designing systems to automatically detect hateful content is of paramount importance if we are to mitigate its undesirable effects on the society at large.
• The detection of multimodal hate speech is an intrinsically difficult and open problem: memes convey a message using both images and text and, hence, require multimodal reasoning and joint visual and language understanding.
• In this work, we seek to advance this line of research and develop a multimodal framework for the detection of hateful memes.