Papers with zero-shot persona customization

1 papers
Towards Zero-Shot Persona Dialogue Generation with In-Context Learning (2023.findings-acl)

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Challenge: Existing methods to improve persona consistency on high-quality human-labeled persona datasets face high cost and poor scalability.
Approach: They propose a method to improve zero-shot persona consistency via in-context learning by pre-training a persona-augmented dialogue generation model and then using in-constant prompting mechanism to realize zero- shot persona customization.
Outcome: The proposed method improves persona consistency without compromising coherence and informativeness in zero-shot settings.

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