mlsanityData to 14 Oct 2026

Creative and Context-Aware Translation of East Asian Idioms with GPT-4

arXiv 2410.00988 ↗First posted 1 Oct 2024cs.CLcited by 10

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Abstract (arXiv)

As a type of figurative language, an East Asian idiom condenses rich cultural background into only a few characters. Translating such idioms is challenging for human translators, who often resort to choosing a context-aware translation from an existing list of candidates. However, compiling a dictionary of candidate translations demands much time and creativity even for expert translators. To alleviate such burden, we evaluate if GPT-4 can help generate high-quality translations. Based on automatic evaluations of faithfulness and creativity, we first identify Pareto-optimal prompting strategies that can outperform translation engines from Google and DeepL. Then, at a low cost, our context-aware translations can achieve far more high-quality translations per idiom than the human baseline. We open-source all code and data to facilitate further research.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 25 of its 42 references that are in the map. First posted on arXiv 1 Oct 2024.

Builds on

25 of 42 references.

References · 25

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
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  8. 2021Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translationcited by 338
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  10. 2023GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4cited by 146
  11. 2023The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluationcited by 95
  12. 2023Large language models effectively leverage document-level context for literary translation, but critical errors persistcited by 80
13 more
  1. 2021BlonDe: An Automatic Evaluation Metric for Document-level Machine Translationcited by 58
  2. 2023Leveraging GPT-4 for Automatic Translation Post-Editingcited by 56
  3. 2022Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literaturecited by 45
  4. 2021It's not Rocket Science : Interpreting Figurative Language in Narrativescited by 39
  5. 2024Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Textscited by 31
  6. 2023Do GPTs Produce Less Literal Translations?cited by 30
  7. 2023Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMscited by 25
  8. 2023Translate Meanings, Not Just Words: IdiomKB's Role in Optimizing Idiomatic Translation with Language Modelscited by 24
  9. 2023Augmenting Large Language Model Translators via Translation Memoriescited by 21
  10. 2022PETCI: A Parallel English Translation Dataset of Chinese Idiomscited by 10
  11. 2024CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfercited by 10
  12. 2024Improving Language Model Reasoning with Self-motivated Learningcited by 4
  13. 2024Thinker-DDM: Modeling Deliberation for Machine Translation with a Drift-Diffusion Processcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 5.

10 papers.