A Large-Scale Benchmark for Vietnamese Sentence Paraphrases
Sang Quang Nguyen, Kiet Van Nguyen
Abstract
This paper presents ViSP, a high-quality Vietnamese dataset for sentence paraphrasing, consisting of 1.2M original–paraphrase pairs collected from various domains. The dataset was constructed using a hybrid approach that combines automatic paraphrase generation with manual evaluation to ensure high quality. We conducted experiments using methods such as back-translation, EDA, and baseline models like BART and T5, as well as large language models (LLMs), including GPT-4o, Gemini-1.5, Aya, Qwen-2.5, and Meta-Llama-3.1 variants. To the best of our knowledge, this is the first large-scale study on Vietnamese paraphrasing. We hope that our dataset and findings will serve as a valuable foundation for future research and applications in Vietnamese paraphrase tasks. The dataset is available for research purposes at https://github.com/ngwgsang/ViSP.
BibTeX
@inproceedings{nguyen-nguyen-2025-large,
title = "A Large-Scale Benchmark for {V}ietnamese Sentence Paraphrases",
author = "Nguyen, Sang Quang and
Nguyen, Kiet Van",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-naacl.59/",
pages = "1045--1060",
ISBN = "979-8-89176-195-7"
}