3 citations · 3 across the 7 of their papers we have counts for
7 papers
AI for Computational Design Science: A Responsible Human-AI Framework and Case Study on Short-Form Video Safety Surveillance
Wenli Zhang, Jiaheng Xie, Zhihe Pan +3
Artificial intelligence (AI) is transforming not only what information systems researchers design, but also how design research is conducted. Yet existing literature offers limited…
Measuring Investor Learning in Private Markets: A Sequential LLM-Bayesian Analysis of Expert Network Calls
Yidong Chai, Yanguang Liu, Xuan Tian +2
We study investor learning and information acquisition in private markets using a large dataset of expert network calls. We develop a sequential Large Language Model (LLM)-Bayesian…
Collaborative Management for Chronic Diseases and Depression: A Double Heterogeneity-based Multi-Task Learning Method
Yidong Chai, Haoxin Liu, Jiaheng Xie +2
Wearable sensor technologies and deep learning are transforming healthcare management. Yet, most health sensing studies focus narrowly on physical chronic diseases. This overlooks…
A Bayesian Hybrid Parameter-Efficient Fine-Tuning Method for Large Language Models
Yidong Chai, Yang Liu, Yonghang Zhou +2
Large Language Models (LLMs) have demonstrated transformative potential in reshaping the world. As these models are pretrained on general corpora, they often require domain-specifi…
Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model
Jiaheng Xie, Ruicheng Liang, Yidong Chai +2
Along with the rise of short-form videos, their mental impacts on viewers have led to widespread consequences, prompting platforms to predict videos' impact on viewers' mental heal…
Few-Shot Learning for Mental Disorder Detection: A Continuous Multi-Prompt Engineering Approach with Medical Knowledge Injection
Haoxin Liu, Wenli Zhang, Jiaheng Xie +4
This study harnesses state-of-the-art AI technology for detecting mental disorders through user-generated textual content. Existing studies typically rely on fully supervised machi…
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning
Jiaheng Xie, Xiao Liu
Predicting video viewership is a top priority for content creators and video-sharing sites. Content creators live on such predictions to maximize influences and minimize budgets. V…