An Open-Source, Domain‑Adaptive and Interpretable NLP Pipeline for Precise Summarization of Complex Cross‑Jurisdictional Legal Documents

Syeda Sadia Fatima, G. Visalaxi, Keerthana G., Allam Balaram, Sejal Dhanaji Zimal

2025

Abstract

In this work, we introduce an open‑source natural language processing pipeline designed to automatically generate concise and accurate summaries of lengthy, complex legal documents spanning multiple jurisdictions. Our approach employs a domain‑adaptive pretraining strategy that fine‑tunes transformer models on diverse legal corpora, enabling robust handling of varied legal language and structure. A hybrid extractive‑abstractive framework leverages legal discourse markers and attention‑based interpretability modules, providing both precise summary generation and transparent justification of content selection. We validate our pipeline on benchmark datasets drawn from common law and civil law systems, demonstrating significant improvements in summary coherence, factual accuracy, and cross‑jurisdictional generalization compared to existing baseline methods. Finally, we release our entire implementation under an open‑source license to foster community adoption and further research in legal AI.

Paper Citation

in Harvard Style

Fatima S., Visalaxi G., G. K., Balaram A. and Zimal S. (2025). An Open-Source, Domain‑Adaptive and Interpretable NLP Pipeline for Precise Summarization of Complex Cross‑Jurisdictional Legal Documents. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 449-455. DOI: 10.5220/0013931200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Syeda Fatima and G. Visalaxi and Keerthana G. and Allam Balaram and Sejal Zimal},
title={An Open-Source, Domain‑Adaptive and Interpretable NLP Pipeline for Precise Summarization of Complex Cross‑Jurisdictional Legal Documents},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={449-455},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013931200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - An Open-Source, Domain‑Adaptive and Interpretable NLP Pipeline for Precise Summarization of Complex Cross‑Jurisdictional Legal Documents
SN - 978-989-758-777-1
AU - Fatima S.
AU - Visalaxi G.
AU - G. K.
AU - Balaram A.
AU - Zimal S.
PY - 2025
SP - 449
EP - 455
DO - 10.5220/0013931200004919
PB - SciTePress