Papers with generation of fluent sentences

1 papers
GRACE: Gradient-guided Controllable Retrieval for Augmenting Attribute-based Text Generation (2023.findings-acl)

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Challenge: Existing methods for controlling the generation of pre-trained language models infuse domain bias into the generation process, making it difficult to generate out-of-domain texts.
Approach: They propose a retrieval-augmented generation framework that uses retrieval to generate fluent sentences with high attribute relevance.
Outcome: The proposed method can generate fluent sentences with high attribute relevance while keeping domain bias out of the model.

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