Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations

Kyo Gerrits, Rik van Noord, Ana Guerberof Arenas


Abstract
This article investigates the performance of automatic evaluation metrics (AEMs) and LLM-as-a-judge evaluation on literary translation across multiple languages, genres, and translation modalities. The aim is to assess how well these tools align with professionals when evaluating translation, creativity (creative shifts & errors), and see if they can substitute laborious manual annotations. A dataset of literary translations across three modalities (human translation, machine translation, and post-editing), three genres and three language pairs was created and annotated in detail for creativity by experienced professional literary translators. The results show that both AEMs and LLM-as-a-judge evaluations correlate poorly with professional evaluations on creativity, with LLM-as-a-judge showing a systematic bias in favour of machine-translated texts and penalising creative and culturally appropriate solutions. Moreover, performance is consistently worse for more literary genres such as poetry. This highlights fundamental limitations of current automatic evaluation tools for literary translation and the need to create new tools that do not frequently consider out of routine translations as errors.
Anthology ID:
2026.eamt-1.43
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:
682–704
Language:
URL:
https://aclanthology.org/2026.eamt-1.43/
DOI:
Bibkey:
Cite (ACL):
Kyo Gerrits, Rik van Noord, and Ana Guerberof Arenas. 2026. Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations. In Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1), pages 682–704, Tilburg, The Netherlands. European Association for Machine Translation.
Cite (Informal):
Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations (Gerrits et al., EAMT 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.eamt-1.43.pdf