First Advisor
Ameeta Agrawal
Date of Award
Winter 3-22-2025
Document Type
Thesis
Degree Name
Bachelor of Science (B.S.) in Computer Science and University Honors
Department
Computer Science
Language
English
Subjects
Computer Science, Large Language Models, Artificial Intelligence, Natural Language Processing, Machine Learning
Abstract
This research delves into the realm of "protective scenes" within Large Language Models (LLMs), exploring their impact on bias mitigation, deception, and context preservation. The study investigates the use of roleplay prompting human-like behavior and reasoning in LLMs, focusing on the Character-LLM framework's concept of protective scenes with graduated levels of protection. By combining insights from psychology, cognitive science, and computational analysis, this research aims to develop a framework for understanding how protective scenes influence roleplay performance in LLMs, ultimately contributing to the development of more reliable and ethical AI systems.
Persistent Identifier
https://archives.pdx.edu/ds/psu/43136
Recommended Citation
Weisman, Eben M., "Investigating Key Structures in Protective Scenes for LLMs" (2025). University Honors Theses. Paper 1583.
