April 06, 2023 preprint Open access Large language models effectively leverage document-level context for literary translation, but critical errors persist arXiv (Cornell University) DOI: 10.48550/arxiv.2304.03245 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 1 stored of 8 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Document-Level Language Models for Machine Translation 2023 Conference on Machine Translation (WMT) conference-paper Computer Science Natural Language Processing Techniques Open access 4 citations 1 result References 0