A cognitive lab study by Jinah Choi, Sonya Powers, Farzan Karimi-Malekabadi, and Michelle Barrett examined how students in Grades 7-12 interacted with an AI-enabled chatbot while completing online cou…
A feasibility study by Marcus Leong, Jennifer Rose, Lisa Dierker, and Antonio Laverghetta Jr., published in the Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME…
Xiaolan Xu, Sara Mendes, and Yu-Yin Hsu built a 495-sentence Chinese challenge set covering 45 occupations to measure gender bias in Chinese-to-Portuguese automated translation, testing two commercial…
Alina Karakanta presented a project-based translation technology module for MA Translation students that integrates large language models as translation engines, prompting and domain adaptation tools,…
Antonio Castaldo, Johanna Monti, and Sheila Castilho published "Emotion Profiling in LLM-Based Literary Translation: Systematic Shifts Across MT and Post-Editing" in the Proceedings of the First Works…
A study of 23 student projects in a fourth-year Machine Translation and Post-editing course found that students did not treat automatic metrics as final authority when selecting machine translation ou…
The European Association for Machine Translation published the Proceedings of the 1st International Workshop on Teaching AI-Based Translation and Technologies (TAITT 2026), held in June 2026 in Tilbur…
A study by Manuel Lardelli, published in the Proceedings of the 4th Workshop on Gender-Inclusive Translation Technologies (GITT 2026), found that neural machine translation (NMT) systems default to bi…
Reasoning LLMs outperform standard inference at shifting Italian-to-German machine translation from binary to non-binary formulations, according to a paper by Paolo Di Natale, Laura Schlutter, Elena C…
A qualitative study by Koen Kerremans, published in the Proceedings of the 1st International Workshop on Teaching AI-Based Translation and Technologies (TAITT 2026), found that a Simulated Translation…
A study by Chiara Manna, Argentina Anna Rescigno, and Eva Vanmassenhove compared the automated WinoMT annotation pipeline with the instruction-tuned LLM Qwen3-8B for annotating grammatical gender in E…
Vincent Vandeghinste presented a paper at the 1st International Workshop on Teaching AI-Based Translation and Technologies (TAITT 2026) describing a teaching method that replicates the historical deve…
Researchers Ivory Yang, Weicheng Ma, and Soroush Vosoughi presented NüshuRescue, an AI-driven framework for training large language models on endangered languages with minimal data, at COLING 2025 in …
A study presented at the 17th Conference of the Association for Machine Translation in the Americas (AMTA 2026) benchmarked eight large language models on game localization quality assurance tasks, fi…
Researchers from the University of Vermont introduced Translation-CoT, a chain-of-thought prompting framework that breaks translation into lexical retrieval, grammatical analysis, and topic identifica…
A study by Rebecca Knowles and Cyril Goutte, presented at the 17th Conference of the Association for Machine Translation in the Americas (AMTA) in Québec City, Canada, in August 2026, found that large…
Researchers at the Association for Machine Translation in the Americas found that document-level summaries improve AI-based post-editing quality only when they are specific and actionable, with gemini…
Researchers Ming Qian and Luyi Yang found that GPT5, guided by MQM-like prompts, aligned with human evaluators on 77.8% of negative flags and 88.9% of positive flags, with an F1 score of 0.875 for det…
A study presented at the 17th Conference of the Association for Machine Translation in the Americas (AMTA 2026) finds that large language models with 70B parameters or more consistently improve downst…
A study by researchers including Jeniffer Leal-Wyss, Gabriel Bernier-Colborne, Delaney Lothian, Michel Simard, and Rebecca Knowles, presented at the 17th Conference of the Association for Machine Tran…