46 citations · 192 across the 56 of their papers we have counts for
9 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…
Learning to Evaluate the Artness of AI-generated Images
Junyu Chen, Jie An, Hanjia Lyu +2
Assessing the artness of AI-generated images continues to be a challenge within the realm of image generation. Most existing metrics cannot be used to perform instance-level and re…
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…