Papers with intent clustering methods

1 papers
Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialogues (2025.emnlp-main)

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Challenge: Existing intent clustering methods rely on embedding distance metrics and neglect of underlying semantic structures.
Approach: They propose an LLM-in-the-loop framework that integrates language understanding capabilities into conventional clustering algorithms.
Outcome: The proposed framework outperforms baselines in Chinese and improves quality, cost efficiency and downstream applications.

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