New Intent Discovery with Attracting and Dispersing Prototype

arXiv:2403.16913v1 Announce Type: new
Abstract: New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data. The task is addressed as a feature-clustering problem and recent studies augment instance representation. However, existing methods fail to capture cluster-friendly representations, since they show less capability to effectively control and coordinate within-cluster and between-cluster distances. Tailored to the NID problem, we propose a Robust and Adaptive Prototypical learning (RAP) framework for …

abstract arxiv cluster clustering cs.cl data discovery feature however instance representation scale studies type