MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models

Suramya Jadhav, Abhay Shanbhag, Amogh Thakurdesai, Ridhima Sinare, Ananya Joshi +1 more
8/24/2025
cs.CLcs.LG

Official code: l3cube-pune/MarathiNLP (160 stars, last commit 2025-09-14).

Abstract

Paraphrases are a vital tool to assist language understanding tasks such as question answering, style transfer, semantic parsing, and data augmentation tasks. Indic languages are complex in natural language processing (NLP) due to their rich morphological and syntactic variations, diverse scripts, and limited availability of annotated data. In this work, we present the L3Cube-MahaParaphrase Dataset, a high-quality paraphrase corpus for Marathi, a low resource Indic language, consisting of 8,000 sentence pairs, each annotated by human experts as either Paraphrase (P) or Non-paraphrase (NP). We also present the results of standard transformer-based BERT models on these datasets. The dataset and model are publicly shared at https://github.com/l3cube-pune/MarathiNLP

View on arXivView PDF

Code Implementations(1)

l3cube-pune/MarathiNLPOfficial100%

Marathi NLP - is a repository dedicated to development of tools and resources for Marathi language.

16019Python, Jupyter NotebookJan 8, 20211 years ago
bertdatasetmachine-learningmarathimarathi-language+5 more

Similar Papers

mahaNLP: A Marathi Natural Language Processing Library

85% match1 repo1602023

L3Cube-MahaNews: News-based Short Text and Long Document Classification Datasets in Marathi

84% match1 repo1602024

L3Cube-MahaSum: A Comprehensive Dataset and BART Models for Abstractive Text Summarization in Marathi

84% match1 repo1602024

L3Cube-MahaSTS: A Marathi Sentence Similarity Dataset and Models

83% match1 repo1602025

Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A Case Study in Marathi

82% match2024

My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks

82% match1 repo1602023

Cite this paper

@article{jadhav2025mahaparaphrase,
  title  = {MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models},
  author = {Suramya Jadhav and Abhay Shanbhag and Amogh Thakurdesai and Ridhima Sinare and Ananya Joshi and Raviraj Joshi},
  year   = {2025},
  eprint = {2508.17444},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.17444v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2508.17444.svg)](https://codeofpaper.com/paper/2508.17444)

Discussion