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Gabriel Bretschner

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#natural language process... Preprint Sep 2026

LocQE: Principled Domain Adaptation for Localisation Quality Estimation by Leveraging Post-Edits

This work creates a QE model which proves markedly better at distinguishing preferred post-edits from rejected initial translations in a localisation context, and argues that to calibrate metrics both in terms of their absolute scores and comparisons between translation of the same source, both types of signal are need...

Kathy Hämmerl, Gabriel Bretschner, Joern Wuebker · 0 citations
#artificial intelligence Preprint Aug 2026

Terminal-Bench-LILT: Multilingual Agentic Coding Benchmark Grounded in Language, Region, and Culture

Evaluation of six frontier models reveals that even the strongest model reaches only 63.1\% pass rate, with many tasks unsolved by any model, highlighting that multilingual coding competence is a distinct and underexplored capability axis.

Yunsu Kim, Kaden Uhlig, Ashwin Purohit et al. · 0 citations

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