Results 11 to 20 of about 4,505,015 (366)
Gender Bias in Machine Translation [PDF]
Transactions of the Association for Computational Linguistics, 2021 AbstractMachine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, processing, and communicating information. However, it can suffer from biases that harm users and society at large. As a relatively new field of inquiry, studies of gender bias in MT still lack cohesion.
Savoldi B. +4 more
openaire +8 more sources
No Language Left Behind: Scaling Human-Centered Machine Translation [PDF]
arXiv.org, 2022 Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today.
Nllb team +38 more
semanticscholar +1 more source
How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation [PDF]
arXiv.org, 2023 Generative Pre-trained Transformer (GPT) models have shown remarkable capabilities for natural language generation, but their performance for machine translation has not been thoroughly investigated.
Amr Hendy +8 more
semanticscholar +1 more source
Prompting Large Language Model for Machine Translation: A Case Study [PDF]
International Conference on Machine Learning, 2023 Research on prompting has shown excellent performance with little or even no supervised training across many tasks. However, prompting for machine translation is still under-explored in the literature.
Biao Zhang, B. Haddow, Alexandra Birch
semanticscholar +1 more source
Automatic evaluation of the quality of machine translation of a scientific text: the results of a five-year-long experiment [PDF]
E3S Web of Conferences, 2021 We report on various approaches to automatic evaluation of machine translation quality and describe three widely used methods. These methods, i.e. methods based on string matching and n-gram models, make it possible to compare the quality of machine ...
Ulitkin Ilya +3 more
doaj +1 more source
Towards Making the Most of ChatGPT for Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 ChatGPT shows remarkable capabilities for machine translation (MT). Several prior studies have shown that it achieves comparable results to commercial systems for high-resource languages, but lags behind in complex tasks, e.g., low-resource and distant ...
Keqin Peng +7 more
semanticscholar +1 more source
Survey of Mongolian-Chinese Neural Machine Translation [PDF]
Jisuanji kexue, 2022 Machine translation is the process of using a computer to convert one language into another language.With the deep understanding of semantics,neural machine translation has become the most mainstream machine translation method at present,and it has made ...
HOU Hong-xu, SUN Shuo, WU Nier
doaj +1 more source
Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis [PDF]
NAACL-HLT, 2023 Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions: 1) How well do ...
Wenhao Zhu +7 more
semanticscholar +1 more source
Document-Level Machine Translation with Large Language Models [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks.
Longyue Wang +6 more
semanticscholar +1 more source
Adaptive Machine Translation with Large Language Models [PDF]
European Association for Machine Translation Conferences/Workshops, 2023 Consistency is a key requirement of high-quality translation. It is especially important to adhere to pre-approved terminology and adapt to corrected translations in domain-specific projects.
Yasmin Moslem, Rejwanul Haque, Andy Way
semanticscholar +1 more source