HERMeS: Human Evaluation & Ranking of MultiplE Systems

Rex Vanhorn


Abstract
Human evaluation remains essential for reliable machine translation (MT) assessment, yet practical evaluation workflows are often difficult to reproduce and scale. Here we introduce HERMeS, a lightweight human evaluation platform designed to streamline systematic human evaluation and comparison of multiple MT systems across large translation sets. Unlike existing evaluation tools, HERMeS focuses specifically on scalable comparison of many anonymized systems through a hybrid ranking and direct assessment workflow, using a novel approach that reduces evaluator cognitive load while maintaining data quality, security, and integrity.
Anthology ID:
2026.eamt-2.8
Volume:
Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2)
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:
17–18
Language:
URL:
https://aclanthology.org/2026.eamt-2.8/
DOI:
Bibkey:
Cite (ACL):
Rex Vanhorn. 2026. HERMeS: Human Evaluation & Ranking of MultiplE Systems. In Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2), pages 17–18, Tilburg, The Netherlands. European Association for Machine Translation.
Cite (Informal):
HERMeS: Human Evaluation & Ranking of MultiplE Systems (Vanhorn, EAMT 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.eamt-2.8.pdf