Papers with Multimodal Aspect-based Sentiment Analysis

2 papers
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis (2023.emnlp-main)

Copied to clipboard

Challenge: Existing work mainly utilizes image information to improve the performance of MABSA task.
Approach: They propose a multimodal Aspect-based Sentiment Analysis task that uses image information to improve model performance.
Outcome: The proposed framework outperforms state-of-the-art work on three sub-tasks of MABSA.
Vanessa: Visual Connotation and Aesthetic Attributes Understanding Network for Multimodal Aspect-based Sentiment Analysis (2024.findings-emnlp)

Copied to clipboard

Challenge: Existing methods to analyze images focus on superficial features or descriptions, omitting subtle contextual information.
Approach: They propose a Visual Connotation and Aesthetic Attributes Understanding Network (Vanessa) for Multimodal Aspect-based Sentiment Analysis.
Outcome: The proposed network captures both implicit and explicit sentimental cues and can be used to enrich textual sentiment analysis.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations