马拉地语跨语言生成式摘要研究
Cross Lingual Abstractive Summarization for Marathi
AI 导读
该arXiv论文基于马拉地语MahaSum单语语料构建跨语言训练数据，结合较小的PMIndiaSum数据集微调IndicTrans2神经机器翻译模型，实现马拉地语到英语的生成式摘要。使用ROUGE、chrF和chrF++指标评测，结果显示利用预训练翻译模型的摘要性能显著优于此前基于IndicBART和mBART-50基线的跨语言摘要工作。
正文 · 原文
Abstract:Text summarization is an important task for advancing natural language processing (NLP) research and applications in Indic languages. Despite progress in extractive and abstractive summarization, both monolingual summarization (MS) and cross-lingual summarization (CLS) remain relatively underexplored for these languages. Recent advances in Transformer architectures, pretrained language models (PLMs), and dataset availability offer new opportunities to address this gap. In this work, we construct cross-lingual training data from the monolingual Marathi MahaSum corpus and combine it with the smaller cross-lingual PMIndiaSum dataset to fine-tune IndicTrans2, an Indic neural machine translation model. We evaluate the resulting models using ROUGE, chrF and chrF++ metrics, focusing primarily on Marathi-to-English summarization due to computational constraints. We also discuss the applicability of our approach to the English-to-Marathi direction. Our experiments demonstrate that leveraging a pretrained translation model yields substantially better summarization performance than the IndicBART and mBART-50 based baselines reported in previous work on cross-lingual summarization.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| ACM classes: | I.2.7 |
| Cite as: | arXiv:2610.38267 [cs.CL] |
| (or arXiv:2610.38267v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.38267 arXiv-issued DOI via DataCite |
Submission history
From: Asang Dani [view email]
[v1]
Wed, 28 Oct 2026 04:34:32 UTC (705 KB)
来源：arXiv cs.AI · arxiv.org