3 citations · 6 across the 9 of their papers we have counts for
4 papers · 1 filter
Dynamic Fusion-Aware Graph Convolutional Neural Network for Multimodal Emotion Recognition in Conversations
Tao Meng, Weilun Tang, Yuntao Shou +4
Multimodal emotion recognition in conversations (MERC) aims to identify and understand the emotions expressed by speakers during utterance interaction from multiple modalities (e.g…
The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection
Wei Ai, Yilong Tan, Yuntao Shou +4
In recent years, the rapid evolution of large vision-language models (LVLMs) has driven a paradigm shift in multimodal fake news detection (MFND), transforming it from traditional…
A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning
Yuntao Shou, Tao Meng, Wei Ai +3
Multi-modal conversation emotion recognition (MCER) aims to recognize and track the speaker's emotional state using text, speech, and visual information in the conversation scene.…
MCSFF: Multi-modal Consistency and Specificity Fusion Framework for Entity Alignment
Wei Ai, Wen Deng, Hongyi Chen +3
Multi-modal entity alignment (MMEA) is essential for enhancing knowledge graphs and improving information retrieval and question-answering systems. Existing methods often focus on…