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20232026
most citedLarge Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey

12 citations · 24 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

InCarEmo: A Multimodal Dataset for In-Cabin Emotion Recognition and Driver State Monitoring

Hao Yang, Yanyan Zhao, Kewei Zhao +11

Understanding driver emotion and state is critical for the next generation of intelligent in-cabin systems that ensure safety and enhance human-vehicle interaction. However, existi…

cs.CV2026

DeepSight: Bridging Depth Maps and Language with a Depth-Driven Multimodal Model

Hao Yang, Hongbo Zhang, Yanyan Zhao +1

Multimodal large language models (MLLMs) have achieved impressive performance across various tasks such as image captioning and visual question answer(VQA); however, they often str…

cs.CV2026

Text-Driven Emotionally Continuous Talking Face Generation

Hao Yang, Yanyan Zhao, Tian Zheng +7

Talking Face Generation (TFG) strives to create realistic and emotionally expressive digital faces. While previous TFG works have mastered the creation of naturalistic facial movem…

cs.CL2024★ 12 cited

Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey

Hao Yang, Yanyan Zhao, Yang Wu +6

Compared to traditional sentiment analysis, which only considers text, multimodal sentiment analysis needs to consider emotional signals from multimodal sources simultaneously and…

cs.CL2023★ 12 cited

An Early Evaluation of GPT-4V(ision)

Yang Wu, Shilong Wang, Hao Yang +4

In this paper, we evaluate different abilities of GPT-4V including visual understanding, language understanding, visual puzzle solving, and understanding of other modalities such a…