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New Intent Discovery with Attracting and Dispersing Prototype
March 26, 2024, 4:51 a.m. | Shun Zhang, Jian Yang, Jiaqi Bai, Chaoran Yan, Tongliang Li, Zhao Yan, Zhoujun Li
cs.CL updates on arXiv.org arxiv.org
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
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