Backtranslation Invariance Boosts Effectiveness of Non-English Prompts
We present an approach to improving non-English prompts based on backtranslation invariance (the semantics of the prompt should not change after automatic translation to English and back).It improves prompts in non-English languages for a variety of Large Language Models (LLMs), including GPT-4-o, Llama-3.1, and Mixtral8x7B.We evaluate the approach for Russian and Finnish languages.In the benchmark of removing commas from a sentence, the proposed approach achieved an accuracy increase of 42% for Russian and 54% for Finnish compared to noninvariant prompts (LLaMA).In the benchmark of counting commas, accuracy increase of 19% for Russian and 11% for Finnish (GPT).
Authors
- Anna Kurtukova (ORCID: https://orcid.org/0000-0001-5619-1836)
- Aleksander Kozachenko
Publication Details
- Journal
- Computational Linguistics and Intellectual Technologies
- Published
- 2025-01-01
- DOI
- https://doi.org/10.28995/2075-7182-2025-23-1055-1065
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00