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Go to ACL ARR 2024 February homepage (/group?idaclweb.org/ACL/ARR/2024/February)Fewshot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning (/pdf?idPTLoZZ_rRFm)Anonymous16
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What is few-shot dialogue strategy learning?
Few-shot dialogue strategy learning is a machine learning approach that enables a system to learn how to engage in dialogue with minimal training examples, typically by leveraging prior knowledge and contextual information.
Who is required to file few-shot dialogue strategy learning?
Typically, researchers and developers who are implementing few-shot learning techniques in dialogue systems may be required to document and file their methodologies and findings as part of academic or regulatory standards.
How to fill out few-shot dialogue strategy learning?
To fill out few-shot dialogue strategy learning, one must define the dialogue context, provide examples of interactions, outline the learning algorithms used, and report the outcomes of the learning process.
What is the purpose of few-shot dialogue strategy learning?
The purpose of few-shot dialogue strategy learning is to enable conversational agents to effectively understand and respond to user inputs with limited data, thus improving their adaptability and efficiency across various dialogue scenarios.
What information must be reported on few-shot dialogue strategy learning?
Information that must be reported includes the methodology used, the types of data employed, performance metrics, and insights gained from the learning process.
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