62 citations · 80 across the 16 of their papers we have counts for
7 papers · 1 filter
Debiasing Multimodal Sarcasm Detection with Contrastive Learning
Mengzhao Jia, Can Xie, Liqiang Jing
Despite commendable achievements made by existing work, prevailing multimodal sarcasm detection studies rely more on textual content over visual information. It unavoidably induces…
VK-G2T: Vision and Context Knowledge enhanced Gloss2Text
Liqiang Jing, Xuemeng Song, Xinxing Zu +3
Existing sign language translation methods follow a two-stage pipeline: first converting the sign language video to a gloss sequence (i.e. Sign2Gloss) and then translating the gene…
FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models
Liqiang Jing, Ruosen Li, Yunmo Chen +1
We introduce FaithScore (Faithfulness to Atomic Image Facts Score), a reference-free and fine-grained evaluation metric that measures the faithfulness of the generated free-form an…
Knowledge-enhanced Memory Model for Emotional Support Conversation
Mengzhao Jia, Qianglong Chen, Liqiang Jing +2
The prevalence of mental disorders has become a significant issue, leading to the increased focus on Emotional Support Conversation as an effective supplement for mental health sup…
General Debiasing for Multimodal Sentiment Analysis
Teng Sun, Juntong Ni, Wenjie Wang +3
Existing work on Multimodal Sentiment Analysis (MSA) utilizes multimodal information for prediction yet unavoidably suffers from fitting the spurious correlations between multimoda…
Multi-source Semantic Graph-based Multimodal Sarcasm Explanation Generation
Liqiang Jing, Xuemeng Song, Kun Ouyang +2
Multimodal Sarcasm Explanation (MuSE) is a new yet challenging task, which aims to generate a natural language sentence for a multimodal social post (an image as well as its captio…
Stylized Data-to-Text Generation: A Case Study in the E-Commerce Domain
Liqiang Jing, Xuemeng Song, Xuming Lin +3
Existing data-to-text generation efforts mainly focus on generating a coherent text from non-linguistic input data, such as tables and attribute-value pairs, but overlook that diff…