Papers with abstract meaning representation back-translation

1 papers
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation (2023.acl-long)

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Challenge: Paraphrase generation is a long-standing task in natural language processing (NLP).
Approach: They propose to generate large-scale syntactically diverse paraphrase datasets by abstract meaning representation back-translation.
Outcome: The proposed dataset is syntactically more diverse than existing datasets while maintaining good semantic similarity.

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