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Bias of AI-Generated Content: An Examination of News Produced by Large Language Models
We then apply each examined LLM to generate news content with headlines of these news articles as prompts, and evaluate the gender and racial biases of the AIGC produced by the LLM by comparing the AIGC and the original news articles.
Proactive Resource Request for Disaster Response: A Deep Learning-based Optimization Model
Prior resource management research for disaster response overlooks the problem of deciding optimal quantities of resources requested by a local agency.
Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoT
To connect human expertise in the decision-making, safeguard trust for this high-stake prediction, and ensure algorithm transparency, we develop an interpretable deep learning model: Temporal Prototype Network (TempPNet).
Exploiting Expert Knowledge for Assigning Firms to Industries: A Novel Deep Learning Method
To address the limitations of existing methods, we propose a novel deep learning-based method that not only seamlessly integrates the three types of knowledge for industry assignment but also takes the time-specificity of assignment-based knowledge into account.
