English

Abstractive Text Summarization for Contemporary Sanskrit Prose: Issues and Challenges

Computation and Language 2025-01-06 v1 Artificial Intelligence

Abstract

This thesis presents Abstractive Text Summarization models for contemporary Sanskrit prose. The first chapter, titled Introduction, presents the motivation behind this work, the research questions, and the conceptual framework. Sanskrit is a low-resource inflectional language. The key research question that this thesis investigates is what the challenges in developing an abstractive TS for Sanskrit. To answer the key research questions, sub-questions based on four different themes have been posed in this work. The second chapter, Literature Review, surveys the previous works done. The third chapter, data preparation, answers the remaining three questions from the third theme. It reports the data collection and preprocessing challenges for both language model and summarization model trainings. The fourth chapter reports the training and inference of models and the results obtained therein. This research has initiated a pipeline for Sanskrit abstractive text summarization and has reported the challenges faced at every stage of the development. The research questions based on every theme have been answered to answer the key research question.

Keywords

Cite

@article{arxiv.2501.01933,
  title  = {Abstractive Text Summarization for Contemporary Sanskrit Prose: Issues and Challenges},
  author = {Shagun Sinha},
  journal= {arXiv preprint arXiv:2501.01933},
  year   = {2025}
}

Comments

PhD Thesis

R2 v1 2026-06-28T20:55:38.807Z