3 citations · 3 across the 5 of their papers we have counts for
5 papers
From Tool Use to Technological Agency: LoopCAT as a Local-First, Open-Source Tool for Translation Technology Education
Gokhan Dogru, Adrià Martín Mor
Translation students need to learn both how to use translation technologies and how to judge the choices those technologies make available. This article presents LoopCAT, an Apache…
Evaluative Judgement in Teaching AI-based Translation: A Class-room Case Study of AI-Mediated Translation and Post-Editing
Gokhan Dogru
Drawing on 23 anonymized student pro-jects from a fourth-year Machine Transla-tion and Post-editing course in a BA-level translation programme, this paper exam-ines how structured…
AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains
Vicent Briva Iglesias, Gokhan Dogru
Large language models (LLMs) and multi-agent orchestration are touted as the next leap in machine translation (MT), but their benefits relative to conventional neural MT (NMT) rema…
Creating Domain-Specific Translation Memories for Machine Translation Fine-tuning: The TRENCARD Bilingual Cardiology Corpus
Gokhan Dogru
This article investigates how translation memories (TM) can be created by translators or other language professionals in order to compile domain-specific parallel corpora , which c…
Large Language Models "Ad Referendum": How Good Are They at Machine Translation in the Legal Domain?
Vicent Briva-Iglesias, Joao Lucas Cavalheiro Camargo, Gokhan Dogru
This study evaluates the machine translation (MT) quality of two state-of-the-art large language models (LLMs) against a tradition-al neural machine translation (NMT) system across…