SubmissionNumber#=%=#14
FinalPaperTitle#=%=#AI-Tutor: Interactive Learning of Ancient Knowledge from Low-Resource Languages
ShortPaperTitle#=%=#
NumberOfPages#=%=#11
CopyrightSigned#=%=#Siddhartha Dalal
JobTitle#==#
Organization#==#Columbia University, NY, NY 10027
Abstract#==#Many low-resource languages, such as Prakrit, present significant linguistic complexities and have limited modern-day resources. These languages often have multiple derivatives; for example, Prakrit, a language in use by masses around 2500 years ago for 500 years, includes Pali and  Gandhari, which encompass a vast body of Buddhist literature, as well as Ardhamagadhi, rich in Jain literature. Despite these challenges, these languages are invaluable for their historical, religious, and cultural insights needed by non-language experts and others.

To explore and understand the deep knowledge within these ancient texts for non-language experts,  we propose a novel approach: translating multiple dialects of the parent language into a contemporary language and then enabling them to interact with the system in their native language, including English, Hindi, French and German, through a question-and-answer interface built on Large Language Models. We demonstrate the effectiveness of this novel AI-Tutor system by focusing on Ardhamagadhi and Pali.
Author{1}{Firstname}#=%=#Siddhartha R.
Author{1}{Lastname}#=%=#Dalal
Author{1}{Username}#=%=#sid
Author{1}{Email}#=%=#sd2803@columbia.edu
Author{1}{Affiliation}#=%=#Columbia University
Author{2}{Firstname}#=%=#Rahul
Author{2}{Lastname}#=%=#Aditya
Author{2}{Email}#=%=#ra3261@columbia.edu
Author{2}{Affiliation}#=%=#Columbia University
Author{3}{Firstname}#=%=#Vethavikashini
Author{3}{Lastname}#=%=#Chithrra Raghuram
Author{3}{Email}#=%=#vc2652@columbia.edu
Author{3}{Affiliation}#=%=#Columbia University
Author{4}{Firstname}#=%=#Prahlad
Author{4}{Lastname}#=%=#Koratamaddi
Author{4}{Email}#=%=#k.prahlad@columbia.edu
Author{4}{Affiliation}#=%=#Columbia University

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