5 papers
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…
From Detection to Discovery: A Closed-Loop Approach for Simultaneous and Continuous Medical Knowledge Expansion and Depression Detection on Social Media
Shuang Geng, Wenli Zhang, Jiaheng Xie +2
Social media user-generated content (UGC) provides real-time, self-reported indicators of mental health conditions such as depression, offering a valuable source for predictive ana…
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…
Detecting Fake News on Social Media: A Novel Reliability Aware Machine-Crowd Hybrid Intelligence-Based Method
Yidong Chai, Kangwei Shi, Jiaheng Xie +3
Fake news on social media platforms poses a significant threat to societal systems, underscoring the urgent need for advanced detection methods. The existing detection methods can…