Browsing by Author "Shin, Daniel"
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- PromptLibraryWang, Ziyan; Hoang, Brandon; Shin, Gabriel; Shin, Daniel (2024-05-06)The rapid advancement and integration of Large Language Models (LLMs) in academic research underscores the critical need for specialized, context-rich training datasets. The PromptLibrary project is designed to address this gap by establishing a comprehensive library of prompts tailored for academic libraries. This initiative aims to amass a wide array of instructional prompts, thereby forming an essential instruction dataset to enhance the utility and relevance of LLMs within scholarly domains. By encapsulating real-world, academic-specific inquiries and scenarios, this dataset is poised to significantly improve LLMs' learning capabilities and adaptability. The project features a web-based, searchable repository that allows for the submission and retrieval of high-quality prompts, ensuring a robust quality assurance mechanism for prompt validation. This repository not only serves as a critical resource for prompt tuning LLMs but also fosters a collaborative environment for librarians, educators, and researchers, thereby advancing the narrative and utility of LLMs in academic settings.