Prompting LLMs: Length Control for Isometric Machine Translation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10511591" target="_blank" >RIV/00216208:11320/25:10511591 - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2025.iwslt-1.11/" target="_blank" >https://aclanthology.org/2025.iwslt-1.11/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2025.iwslt-1.11" target="_blank" >10.18653/v1/2025.iwslt-1.11</a>

Result language

angličtina

Original language name

Prompting LLMs: Length Control for Isometric Machine Translation

Original language description

In this study, we explore the effectiveness of isometric machine translation across multiple language pairs (En-De, En-Fr, and En-Es) under the conditions of the IWSLT Isometric Shared Task 2022. Using eight open-source large language models (LLMs) of varying sizes, we investigate how different prompting strategies, varying numbers of few-shot examples, and demonstration selection influence translation quality and length control. We discover that the phrasing of instructions, when aligned with the properties of the provided demonstrations, plays a crucial role in controlling the output length. Our experiments show that LLMs tend to produce shorter translations only when presented with extreme examples, while isometric demonstrations often lead to the models disregarding length constraints. While few-shot prompting generally enhances translation quality, further improvements are marginal across 5, 10, and 20-shot settings. Finally, considering multiple outputs allows to notably improve overall tradeoff

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EH23_020%2F0008518" target="_blank" >EH23_020/0008518: Linguistics, Artificial Intelligence and Language and Speech Technologies: from Research to Applications</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025)

ISBN

979-8-89176-272-5

ISSN

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e-ISSN

—

Number of pages

19

Pages from-to

119-137

Publisher name

Association for Computational Linguistics

Place of publication

Kerrville, TX, USA

Event location

Wien, Austria

Event date

Jul 31, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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