Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Vamvas, Jannis, Prat, Ignacio Pérez, Heldstab, Angela, Fischer, Dominic P., Ahmadi, Sina, Sennrich, Rico
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866914425151160320
author Vamvas, Jannis
Prat, Ignacio Pérez
Heldstab, Angela
Fischer, Dominic P.
Ahmadi, Sina
Sennrich, Rico
author_facet Vamvas, Jannis
Prat, Ignacio Pérez
Heldstab, Angela
Fischer, Dominic P.
Ahmadi, Sina
Sennrich, Rico
contents Recent strategies for low-resource machine translation rely on LLMs to generate synthetic data from higher-resource languages. We find that this method fails for Romansh, because LLMs tend to confuse its 6 distinct language varieties. Our experiments show that instead, the direction of data augmentation should be aligned with the resource gradient between source and target language. This approach surpasses Gemini 3 Pro in the lowest-resource variety of Romansh by 23 BLEU. A human evaluation confirms that our experiments yield the first model that generates fluent translations in the individual Romansh varieties.
format Preprint
id arxiv_https___arxiv_org_abs_2603_25489
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties
Vamvas, Jannis
Prat, Ignacio Pérez
Heldstab, Angela
Fischer, Dominic P.
Ahmadi, Sina
Sennrich, Rico
Computation and Language
Recent strategies for low-resource machine translation rely on LLMs to generate synthetic data from higher-resource languages. We find that this method fails for Romansh, because LLMs tend to confuse its 6 distinct language varieties. Our experiments show that instead, the direction of data augmentation should be aligned with the resource gradient between source and target language. This approach surpasses Gemini 3 Pro in the lowest-resource variety of Romansh by 23 BLEU. A human evaluation confirms that our experiments yield the first model that generates fluent translations in the individual Romansh varieties.
title Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties
topic Computation and Language
url https://arxiv.org/abs/2603.25489