6 citations · 7 across the 5 of their papers we have counts for
5 papers
Omni-SILA: Towards Omni-scene Driven Visual Sentiment Identifying, Locating and Attributing in Videos
Jiamin Luo, Jingjing Wang, Junxiao Ma +3
Prior studies on Visual Sentiment Understanding (VSU) primarily rely on the explicit scene information (e.g., facial expression) to judge visual sentiments, which largely ignore im…
Comment-aided Video-Language Alignment via Contrastive Pre-training for Short-form Video Humor Detection
Yang Liu, Tongfei Shen, Dong Zhang +3
The growing importance of multi-modal humor detection within affective computing correlates with the expanding influence of short-form video sharing on social media platforms. In t…
Pre-trained Token-replaced Detection Model as Few-shot Learner
Zicheng Li, Shoushan Li, Guodong Zhou
Pre-trained masked language models have demonstrated remarkable ability as few-shot learners. In this paper, as an alternative, we propose a novel approach to few-shot learning wit…
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
Jingjing Wang, Changlong Sun, Shoushan Li +5
Recently, neural networks have shown promising results on Document-level Aspect Sentiment Classification (DASC). However, these approaches often offer little transparency w.r.t. th…
Emotion Detection with Neural Personal Discrimination
Xiabing Zhou, Zhongqing Wang, Shoushan Li +2
There have been a recent line of works to automatically predict the emotions of posts in social media. Existing approaches consider the posts individually and predict their emotion…