85 citations · 86 across the 6 of their papers we have counts for
6 papers
Modularized Networks for Few-shot Hateful Meme Detection
Rui Cao, Roy Ka-Wei Lee, Jing Jiang
In this paper, we address the challenge of detecting hateful memes in the low-resource setting where only a few labeled examples are available. Our approach leverages the compositi…
Knowledge Generation for Zero-shot Knowledge-based VQA
Rui Cao, Jing Jiang
Previous solutions to knowledge-based visual question answering~(K-VQA) retrieve knowledge from external knowledge bases and use supervised learning to train the K-VQA model. Recen…
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…
Modularized Zero-shot VQA with Pre-trained Models
Rui Cao, Jing Jiang
Large-scale pre-trained models (PTMs) show great zero-shot capabilities. In this paper, we study how to leverage them for zero-shot visual question answering (VQA). Our approach is…
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…
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…