Papers with sentence-level systems

2 papers
On Search Strategies for Document-Level Neural Machine Translation (2023.findings-acl)

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Challenge: Document-level neural machine translation models produce a more consistent output across a document . however, the exact decoding strategy is often not described and not mentioned at all.
Approach: They propose to use standard automatic metrics and specific linguistic phenomena to compare different decoding schemes.
Outcome: The proposed decoding strategies perform similar to each other on three standard document-level translation benchmarks.
Challenges in Context-Aware Neural Machine Translation (2023.emnlp-main)

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Challenge: despite well-reasoned intuitions, most context-aware neural machine translation models show only modest improvements over sentence-level systems.
Approach: They propose a more realistic setting for document-level translation called paragraph-to-paragraph (PARA2PARA) they collect a dataset of Chinese-English novels to promote future research .
Outcome: The proposed model improves translation quality across document-level metrics and discourse phenomena.

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