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arXiv · 2403.18973

Conformal Intent Classification and Clarification for Fast and Accurate Intent Recognition

Floris den Hengst·Ralf Wolter·Patrick Altmeyer·Arda Kaygan
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Abstract

We present Conformal Intent Classification and Clarification (CICC), a framework for fast and accurate intent classification for task-oriented dialogue systems. The framework turns heuristic uncertainty scores of any intent classifier into a clarification question that is guaranteed to contain the true intent at a pre-defined confidence level. By disambiguating between a small number of likely intents, the user query can be resolved quickly and accurately. Additionally, we propose to augment the framework for out-of-scope detection. In a comparative evaluation using seven intent recognition datasets we find that CICC generates small clarification questions and is capable of out-of-scope detection. CICC can help practitioners and researchers substantially in improving the user experience of dialogue agents with specific clarification questions.

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Floris den Hengst, Ralf Wolter, Patrick Altmeyer, Arda Kaygan. 2024-03-27. Conformal Intent Classification and Clarification for Fast and Accurate Intent Recognition. https://arxiv.org/abs/2403.18973

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