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Linguistically Motivated Evaluation of the 2023 State-of-the-art Machine Translation: Can ChatGPT Outperform NMT?

, , , , , and . WMT, page 224-245. Association for Computational Linguistics, (2023)

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Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination., and . BMC systems biology, (Mar 24, 2017)Linguistic Evaluation of German-English Machine Translation Using a Test Suite., , , and . WMT (2), page 445-454. Association for Computational Linguistics, (2019)Evaluating the translation of speech to virtually-performed sign language on AR glasses., , , and . QoMEX, page 141-144. IEEE, (2021)Sentence-level quality estimation by predicting HTER as a multi-component metric.. WMT, page 534-539. Association for Computational Linguistics, (2017)Efforts on Machine Learning over Human-mediated Translation Edit Rate.. WMT@ACL, page 302-306. The Association for Computer Linguistics, (2014)Observing the Learning Curve of NMT Systems With Regard to Linguistic Phenomena., , and . ACL (student), page 186-196. Association for Computational Linguistics, (2021)DGS-Fabeln-1: A Multi-Angle Parallel Corpus of Fairy Tales between German Sign Language and German Text., , , , , and . LREC/COLING, page 4847-4857. ELRA and ICCL, (2024)DFKI's SC and MT submissions to IWSLT 2011., , , and . IWSLT, page 98-105. ISCA, (2011)The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation., , , , , and . LREC, page 3430-3435. European Language Resources Association (ELRA), (2012)Results of WMT22 Metrics Shared Task: Stop Using BLEU - Neural Metrics Are Better and More Robust., , , , , , , , , and . WMT, page 46-68. Association for Computational Linguistics, (2022)