Diversity and Homogenisation in Generative AI Translation: A Comparative Study of English-Dutch Translation Across Domains

Dimitar Shterionov, Noa van Helleman, Eva Vanmassenhove


Abstract
Generative AI tools, such as ChatGPT, are applied to a wide range of languagerelated tasks, including translation. Despite their current popularity among users and researchers and the impressive results obtained on several benchmarks (Kocmi et al., 2024a; Deutsch et al., 2025), their potential side-effects on languages and translations are still understudied (Vanmassenhove, 2025). The paradigm shift from Machine Translation (MT) to Generative AI Translation (GAIT) likely calls for a reconsideration of our assessment and evaluation metrics and practices. In this work, we focus on GAIT by analyzing translations from four multilingual large language models (MLLMs), mBART, Jamba-1.5-large, GPT 4o and DeepSeek R1 applied to three different domains (news, literature and poetry) for the English-Dutch language pair. Focusing on metrics related to lexical and textual diversity, we find that while GAIT text for literature if of significantly high lexical and grammatical richness, that is not the case for news and poetry. We also assess the homogeneity of AI-generated text through a set of clustering and classification experiments. In addition to a clear separation between human- and AI-generated content, our results indicate that GAIT output is more homogeneous among MLLMs.
Anthology ID:
2026.eamt-1.6
Volume:
Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)
Month:
June
Year:
2026
Address:
Tilburg, The Netherlands
Editors:
Dimitar Shterionov, Eva Vanmassenhove, Mirella De Sisto, Fred Blain, Javad Pourmostafa Roshan Sharami, Lisa Lepp, Chiara Manna, Argentina Anna Rescigno, Alina Karakanta, Ayla Rigouts Terryn, Manuel Lardelli, Natalia Resende, Elena Murgolo, Janiça Hackenbuchner, Anna Zaretskaya, Miquel Esplà-Gomis, Thierry Etchegoyhen, Dagmar Gromann, Rachel Bawden, Barry Haddow, Sara Szoc, Mikel Forcada, Helena Moniz
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
61–75
Language:
URL:
https://aclanthology.org/2026.eamt-1.6/
DOI:
Bibkey:
Cite (ACL):
Dimitar Shterionov, Noa van Helleman, and Eva Vanmassenhove. 2026. Diversity and Homogenisation in Generative AI Translation: A Comparative Study of English-Dutch Translation Across Domains. In Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1), pages 61–75, Tilburg, The Netherlands. European Association for Machine Translation.
Cite (Informal):
Diversity and Homogenisation in Generative AI Translation: A Comparative Study of English-Dutch Translation Across Domains (Shterionov et al., EAMT 2026)
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PDF:
https://aclanthology.org/2026.eamt-1.6.pdf