85 citations · 91 across the 6 of their papers we have counts for
6 papers
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection
Kairui Hu, Ming Yan, Joey Tianyi Zhou +3
Stance detection aims to identify the attitude expressed in a document towards a given target. Techniques such as Chain-of-Thought (CoT) prompting have advanced this task, enhancin…
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
Rui Cao, Ming Shan Hee, Adriel Kuek +3
Hateful meme detection is a challenging multimodal task that requires comprehension of both vision and language, as well as cross-modal interactions. Recent studies have tried to f…
Decoding the Underlying Meaning of Multimodal Hateful Memes
Ming Shan Hee, Wen-Haw Chong, Roy Ka-Wei Lee
Recent studies have proposed models that yielded promising performance for the hateful meme classification task. Nevertheless, these proposed models do not generate interpretable e…
Prompting for Multimodal Hateful Meme Classification
Rui Cao, Roy Ka-Wei Lee, Wen-Haw Chong +1
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external kn…
On Explaining Multimodal Hateful Meme Detection Models
Ming Shan Hee, Roy Ka-Wei Lee, Wen-Haw Chong
Hateful meme detection is a new multimodal task that has gained significant traction in academic and industry research communities. Recently, researchers have applied pre-trained v…
Disentangling Hate in Online Memes
Rui Cao, Ziqing Fan, Roy Ka-Wei Lee +2
Hateful and offensive content detection has been extensively explored in a single modality such as text. However, such toxic information could also be communicated via multimodal c…