10 citations · 68 across the 39 of their papers we have counts for
8 papers · 1 filter
Personalized Multimodal Large Language Models: A Survey
Junda Wu, Hanjia Lyu, Yu Xia +24
Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…
INS-MMBench: A Comprehensive Benchmark for Evaluating LVLMs' Performance in Insurance
Chenwei Lin, Hanjia Lyu, Xian Xu +1
Large Vision-Language Models (LVLMs) and Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance in various general multimodal applications and have show…
Harnessing GPT-4V(ision) for Insurance: A Preliminary Exploration
Chenwei Lin, Hanjia Lyu, Jiebo Luo +1
The emergence of Large Multimodal Models (LMMs) marks a significant milestone in the development of artificial intelligence. Insurance, as a vast and complex discipline, involves a…
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
Daoan Zhang, Junming Yang, Hanjia Lyu +4
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image input…
Human vs. LMMs: Exploring the Discrepancy in Emoji Interpretation and Usage in Digital Communication
Hanjia Lyu, Weihong Qi, Zhongyu Wei +1
Leveraging Large Multimodal Models (LMMs) to simulate human behaviors when processing multimodal information, especially in the context of social media, has garnered immense intere…
GPT-4V(ision) as A Social Media Analysis Engine
Hanjia Lyu, Jinfa Huang, Daoan Zhang +6
Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest i…
Holistic Visual-Textual Sentiment Analysis with Prior Models
Junyu Chen, Jie An, Hanjia Lyu +2
Visual-textual sentiment analysis aims to predict sentiment with the input of a pair of image and text, which poses a challenge in learning effective features for diverse input ima…
Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis
Wei Zhu, Zihe Zheng, Haitian Zheng +2
Visual sentiment analysis has received increasing attention in recent years. However, the dataset's quality is a concern because the sentiment labels are crowd-sourcing, subjective…