Papers with context-aware MT models

2 papers
Analysing concatenation approaches to document-level NMT in two different domains (D19-65)

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Challenge: a recent study has shown that discourse-related biases affect neural MT performance.
Approach: They propose a comparative evaluation scheme that contrasts coherent context with artificially scrambled documents and absent context.
Outcome: The proposed evaluation scheme contrasts coherent context with artificially scrambled documents and absent context on two popular datasets.
When Does Translation Require Context? A Data-driven, Multilingual Exploration (2023.acl-long)

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Challenge: Recent studies in context-aware MT attempt to target a small set of discourse phenomena during evaluation, however not in a fully systematic way.
Approach: They develop a multilingual discourse-aware benchmark to evaluate model performance on discourse phenomena in a given dataset.
Outcome: The proposed model improves on previously studied phenomena while uncovering others which were not addressed.

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