Papers with Multilingual generation

1 papers
Multilingual AMR-to-Text Generation (2020.emnlp-main)

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Challenge: Existing work on generating text from structured data into English has focused on bridging the gap between structure and natural language (NL) and semantically underspecified input and fully specified output.
Approach: They propose a multilingual approach that can decode into 21 different languages . they leverage advances in cross-lingual embeddings and pretraining to generate multilingual models .
Outcome: The proposed model surpasses baselines that generate into one language in eighteen languages.

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