# JParaCrawl v3.0: A Large-scale English-Japanese Parallel Corpus

arXiv: https://arxiv.org/abs/2202.12607 · HTML: https://mlsanity.com/paper/2202.12607/

## Key facts

- Cited by 17 papers in the map (data through 7 Oct 2026).
- Builds on 17 of its 36 references that are in the map.
- First posted on arXiv 25 Feb 2022.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Sequence to Sequence Learning with Neural Networks](https://mlsanity.com/paper/1409.3215/) (2014)
- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://mlsanity.com/paper/1904.01038/) (2019)
- [Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation](https://mlsanity.com/paper/1609.08144/) (2016)
- [Effective Approaches to Attention-based Neural Machine Translation](https://mlsanity.com/paper/1508.04025/) (2015)
- [WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia](https://mlsanity.com/paper/1907.05791/) (2019)
- [Scaling Neural Machine Translation](https://mlsanity.com/paper/1806.00187/) (2018)
- [CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB](https://mlsanity.com/paper/1911.04944/) (2019)
- [JParaCrawl: A Large Scale Web-Based English-Japanese Parallel Corpus](https://mlsanity.com/paper/1911.10668/) (2019)
- [Findings of the First Shared Task on Machine Translation Robustness](https://mlsanity.com/paper/1906.11943/) (2019)
- [JESC: Japanese-English Subtitle Corpus](https://mlsanity.com/paper/1710.10639/) (2017)
- [Designing the Business Conversation Corpus](https://mlsanity.com/paper/2008.01940/) (2020)

## Built on by (most cited first, 17 of 17)

- [Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities](https://mlsanity.com/paper/2404.17790/) (2024)
- [Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters](https://mlsanity.com/paper/2406.16758/) (2024)
- [KIT's Multilingual Speech Translation System for IWSLT 2023](https://mlsanity.com/paper/2306.05320/) (2023)
- [Enhancing Translation Accuracy of Large Language Models through Continual Pre-Training on Parallel Data](https://mlsanity.com/paper/2407.03145/) (2024)
- [The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data](https://mlsanity.com/paper/2603.16177/) (2026)
- [Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMs](https://mlsanity.com/paper/2408.04217/) (2024)
- [Simultaneous Interpretation Corpus Construction by Large Language Models in Distant Language Pair](https://mlsanity.com/paper/2404.12299/) (2024)
- [Multi-Drafter Speculative Decoding with Alignment Feedback](https://mlsanity.com/paper/2604.05417/) (2026)
- [Generating Diverse Translation with Perturbed kNN-MT](https://mlsanity.com/paper/2402.09344/) (2024)
- [Domain adapted machine translation: What does catastrophic forgetting forget and why?](https://mlsanity.com/paper/2412.17537/) (2024)
- [BiMax: Bidirectional MaxSim Score for Document-Level Alignment](https://mlsanity.com/paper/2510.15577/) (2025)
- [Static Word Embeddings for Sentence Semantic Representation](https://mlsanity.com/paper/2506.04624/) (2025)
- [JaParaPat: A Large-Scale Japanese-English Parallel Patent Application Corpus](https://mlsanity.com/paper/2508.16303/) (2025)
- [Hacking Neural Evaluation Metrics with Single Hub Text](https://mlsanity.com/paper/2512.16323/) (2025)
- [A Japanese-Chinese Parallel Corpus Using Crowdsourcing for Web Mining](https://mlsanity.com/paper/2405.09017/) (2024)
- [Tracing Multilingual Knowledge Acquisition Dynamics in Domain Adaptation: A Case Study of English-Japanese Biomedical Adaptation](https://mlsanity.com/paper/2510.12115/) (2025)
- [CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation](https://mlsanity.com/paper/2606.21413/) (2026)

## Abstract (arXiv)

Most current machine translation models are mainly trained with parallel corpora, and their translation accuracy largely depends on the quality and quantity of the corpora. Although there are billions of parallel sentences for a few language pairs, effectively dealing with most language pairs is difficult due to a lack of publicly available parallel corpora. This paper creates a large parallel corpus for English-Japanese, a language pair for which only limited resources are available, compared to such resource-rich languages as English-German. It introduces a new web-based English-Japanese parallel corpus named JParaCrawl v3.0. Our new corpus contains more than 21 million unique parallel sentence pairs, which is more than twice as many as the previous JParaCrawl v2.0 corpus. Through experiments, we empirically show how our new corpus boosts the accuracy of machine translation models on various domains. The JParaCrawl v3.0 corpus will eventually be publicly available online for research purposes.