VNJPTranslate: A comprehensive pipeline for Vietnamese-Japanese translation

• URL: http://arxiv.org/abs/2504.00339v1
• Date: Tue, 01 Apr 2025 01:38:25 GMT
• Title: VNJPTranslate: A comprehensive pipeline for Vietnamese-Japanese translation
• Authors: Hoang Hai Phan, Nguyen Duc Minh Vu, Nam Dang Phuong,
• Abstract summary: VNJPTranslate is a pipeline designed to systematically address the Vi-Ja translation task.<n>It features a targeted data augmentation strategy using advanced LLMs with Chain-of-specifically prompting for challenging segments identified via corpus analysis.<n>We employ efficient fine-tuning techniques to create a practical and high-performing translation system.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Neural Machine Translation (NMT) driven by Transformer architectures has advanced significantly, yet faces challenges with low-resource language pairs like Vietnamese-Japanese (Vi-Ja). Issues include sparse parallel data and handling linguistic/cultural nuances. Recent progress in Large Language Models (LLMs) with strong reasoning, often refined via Reinforcement Learning (RL), enables high-quality synthetic data generation. We introduce VNJPTranslate, a pipeline designed to systematically address the Vi-Ja translation task. It features a targeted data augmentation strategy using advanced LLMs with Chain-of-Thought prompting for challenging segments identified via corpus analysis. Subsequently, we employ efficient fine-tuning techniques (Unsloth with QLoRA) on a capable, low-parameter autoregressive model (specifically, a fine-tuned version of the 1.8B parameter Sailor model, which is based on the Qwen architecture) to create a practical and high-performing translation system. This integrated approach aims to improve Vi-Ja translation quality significantly over existing baselines.

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