%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Scat Marian Small Target Ctx4 Cwd0 En Fr
This model is based on Helsinki-NLP/opus-mt-en-fr, further trained for English-French translation with context tag format on the IWSLT17 dataset, and fine-tuned on the SCAT+ training set.
Downloads 39
Release Time : 6/28/2023
Model Overview
This model is designed for English-French context-aware and non-context translation tasks, supports document-level machine translation, and is used for research on quantifying the rationality of context dependencies in neural machine translation.
Model Features
Context-aware translation
Supports input and output of contextual information, enhancing translation coherence and accuracy.
Document-level translation
Capable of handling document-level translation tasks, maintaining overall semantic consistency of documents.
Multi-dataset fine-tuning
Fine-tuned on IWSLT17 and SCAT+ datasets, adaptable to various translation scenarios.
Model Capabilities
English to French translation
Context-aware translation
Document-level translation
Use Cases
Academic research
Context dependency research
Used for research quantifying the rationality of context dependencies in neural machine translation.
Related findings were published in the ICLR 2024 paper 'Quantifying the Rationality of Context Dependencies in Neural Machine Translation'.
Commercial applications
Document translation
Suitable for translation tasks requiring preservation of overall document semantic consistency.
Featured Recommended AI Models
Š 2025AIbase