Papers by Pavel Serdyukov

1 papers
Context-Aware Neural Machine Translation Learns Anaphora Resolution (P18-1)

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Challenge: Standard machine translation systems process sentences in isolation and ignore extra-sentential information.
Approach: They propose a context-aware neural machine translation model that controls flow of information from extended context to the translation model.
Outcome: The proposed model improves on an English-Russian subtitles dataset over its context-agnostic version (+0.7) and over simple concatenation of context and source sentences (+0.6).

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