Our project, "Enhancing Historical Understanding with Retrieval Augmented Generation," addresses the significant challenge of accessing and understanding the vast trove of historical information available online. In an age where the internet is saturated with data, traditional search engines often provide either an overwhelming flood of data or overly simplistic summaries that lack depth and context. Our approach revolutionizes the retrieval of historical data by combining advanced search algorithms with the power of Large Language Models (LLMs). This unique blend allows our system not only to locate historical data but to understand and synthesize this information in a meaningful and contextually rich manner. The primary objective of this project is to transform how historical information is accessed, making it reliable, contextual, and easy to access for a broad audience. Our tool ensures the accuracy and credibility of the historical data provided by sourcing from reputable historical texts and databases. It also offers a deeper understanding of the historical contexts surrounding the facts, enriching users' appreciation and comprehension of historical events. This system features a retrieval augmented generation technology that leverages both advanced search algorithms and LLMs. This method overcomes the limitations of traditional search engines by offering nuanced insights and synthesized responses to complex historical queries. The result is a tool that not only enhances the accessibility of detailed historical information but also improves the accuracy of the data retrieved, making it an invaluable educational tool. We invite you to experience the capabilities of our innovative system by visiting our website or accessing the tool directly through the provided links. For more information or to provide feedback, please contact Srianusha Nandula at snandula@ucsd.edu, Saachi Shenoy at svshenoy@ucsd.edu, or Colin Jemmott at cjemmott@ucsd.edu. This tool is ideally suited for educational research and professional settings where reliable historical information is crucial, simplifying the process of finding and understanding historical data and reducing the risk of misinformation.
Utilizes both search algorithms and LLMs to produce accurate answers to user queries
Answers are derived from a curated selection of historical newspapers, ensuring the reliability and relevance of the information
Designed to be intuitive for all users, from students to researchers