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cs.CL2026
Can Large Language Models Reliably Correct Errors in Low-Resource ASR? A Contamination-Aware Case Study on West Frisian
Yun Hao, Reihaneh Amooie, Wietse de Vries +2
Automatic speech recognition (ASR) has improved substantially in recent years, yet performance remains limited for low-resource languages. Large language models (LLMs) have shown p…
cs.CL2026
Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations
Kyo Gerrits, Rik van Noord, Ana Guerberof Arenas
This article investigates the performance of automatic evaluation metrics (AEMs) and LLM-as-a-judge evaluation on literary translation across multiple languages, genres, and transl…