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20232026
most citedFine-grained and Explainable Factuality Evaluation for Multimodal Summarization

2 citations · 13 across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CL2024★ 2 cited

Fine-grained and Explainable Factuality Evaluation for Multimodal Summarization

Yue Zhang, Jingxuan Zuo, Ke Su +1

Multimodal summarization aims to generate a concise summary based on the input text and image. However, the existing methods potentially suffer from unfactual output. To evaluate t…

cs.CL2024★ 1 cited

Sentiment-enhanced Graph-based Sarcasm Explanation in Dialogue

Kun Ouyang, Liqiang Jing, Xuemeng Song +3

Sarcasm Explanation in Dialogue (SED) is a new yet challenging task, which aims to generate a natural language explanation for the given sarcastic dialogue that involves multiple m…

cs.CL2023★ 1 cited

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…

cs.CL2023

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…

cs.CL2023★ 2 cited

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…

cs.CL2023

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…