3 accepted papers
Multimodal sarcasm detection aims to uncover the sarcasm emotions expressed through various modalities such as text and image. Previous work has made enlightening exploration in detecting sarcastic sentiments with given domains. However, there remains a gap in utilizing deeper contextual information…
Sentiment analysis is rapidly advancing by utilizing various data modalities (e.g., text, video, and audio). However, most existing techniques only learn the atomic-level features that reflect strong correlations, while ignoring more complex compositions in multimodal data. Moreover, they also negle…
Multimodal sarcasm detection, aiming to detect the ironic sentiment within multimodal social data, has gained substantial popularity in both the natural language processing and computer vision communities. Recently, graph-based studies by drawing sentimental relations to detect multimodal sarcasm ha…