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ACL Findings2024

A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism

Brian Thompson, Mehak Preet Dhaliwal, Peter Frisch, Tobias Domhan, Marcello Federico

摘要

We show that content on the web is often translated into many languages, and the low quality of these multi-way translations indicates they were likely created using Machine Translation (MT). Multi-way parallel, machine generated content not only dominates the translations in lower resource languages; it also constitutes a large fraction of the total web content in those languages. We also find evidence of a selection bias in the type of content which is translated into many languages, consistent with low quality English content being translated en masse into many lower resource languages, via MT. Our work raises serious concerns about training models such as multilingual large language models on both monolingual and bilingual data scraped from the web.

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引用它的顶会 Paper8

  1. Assessing Large Language Models on Climate InformationJannis Bulian, Mike S. Schäfer, Afra Amini, Heidi Lam 等ICML 2024 · 39 次引用
  2. Scaling Low-Resource MT via Synthetic Data Generation with LLMsOna de Gibert, Joseph Attieh, Teemu Vahtola, Mikko Aulamo 等EMNLP 2025 · 2 次引用
  3. Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMsEva VanmassenhoveACL 2026 · 1 次引用
  4. Mitigating GenAI-Powered Evidence Pollution for Out-Of-Context Misinformation DetectionZehong Yan, Peng Qi, Wynne Hsu, Mong-Li LeeICDE 2026 · 1 次引用
  5. Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?HyoJung Han, Akiko Eriguchi, Haoran Xu, Hieu Hoang 等ICLR 2025

它引用的 Paper6

  1. ParaCrawl: Web-Scale Acquisition of Parallel CorporaMarta Bañón, Pinzhen Chen, Barry Haddow, Kenneth Heafield 等ACL 2020 · 132 次引用
  2. What Language Model to Train if You Have One Million GPU Hours?Teven Le Scao, Thomas Wang, Daniel Hesslow, Lucile Saulnier 等EMNLP Findings 2022 · 33 次引用
  3. Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled CorpusJesse Dodge, Maarten Sap, Ana Marasovic, William Agnew 等EMNLP 2021 · 18 次引用
  4. Automatic Machine Translation Evaluation in Many Languages via Zero-Shot ParaphrasingBrian Thompson, Matt PostEMNLP 2020 · 7 次引用
  5. Language-agnostic BERT Sentence EmbeddingFangxiaoyu Feng, Yinfei Yang, Daniel Cer, Naveen Arivazhagan 等ACL 2022

相关 Paper

  1. An Extensive Exploration of Back-Translation in 60 LanguagesPaul McNamee, Kevin DuhACL Findings 2023 · 3 次引用
  2. Small Data, Big Impact: Leveraging Minimal Data for Effective Machine TranslationJean Maillard, Cynthia Gao, Elahe Kalbassi, Kaushik Ram Sadagopan 等ACL 2023 · 3 次引用
  3. Multilingual Data Filtering using Synthetic Data from Large Language ModelsJonas Waldendorf, Barry Haddow, Alexandra Birch, Mateusz KlimaszewskiEMNLP Findings 2025
  4. Understanding Translationese in Cross-Lingual SummarizationJiaan Wang, Fandong Meng, Yunlong Liang, Tingyi Zhang 等EMNLP Findings 2023 · 5 次引用
  5. Statistical Power and Translationese in Machine Translation EvaluationYvette Graham, Barry Haddow, Philipp KoehnEMNLP 2020 · 82 次引用
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