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RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations
To address the aforementioned challenges, we propose a Robust New Intent Discovery (RoNID) framework optimized by an EM-style method, which focuses on constructing reliable pseudo-labels and obtaining cluster-friendly discriminative representations.
New Intent Discovery with Attracting and Dispersing Prototype
New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data.
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