39 citations · 64 across the 6 of their papers we have counts for
6 papers
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…
Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligence
Weixiang Zhao, Zhuojun Li, Shilong Wang +5
Emotional Intelligence (EI), consisting of emotion perception, emotion cognition and emotion expression, plays the critical roles in improving user interaction experience for the c…
SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models
Weixiang Zhao, Shilong Wang, Yulin Hu +6
The continual learning (CL) ability is vital for deploying large language models (LLMs) in the dynamic world. Existing methods devise the learning module to acquire task-specific k…
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…
TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition
Weixiang Zhao, Yanyan Zhao, Shilong Wang +1
Emotion Support Conversation (ESC) is an emerging and challenging task with the goal of reducing the emotional distress of people. Previous attempts fail to maintain smooth transit…
Is ChatGPT Equipped with Emotional Dialogue Capabilities?
Weixiang Zhao, Yanyan Zhao, Xin Lu +3
This report presents a study on the emotional dialogue capability of ChatGPT, an advanced language model developed by OpenAI. The study evaluates the performance of ChatGPT on emot…