SOTAVerified

Intent Discovery

Given a set of labelled and unlabelled utterances, the idea is to identify existing (known) intents and potential (new intents) intents. This method can be utilised in conversational system setting.

Papers

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Showing 21–30 of 42 papers

TitleStatusHype
New Intent Discovery with Attracting and Dispersing Prototype—0
RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations—0
Semi-supervised Intent Discovery with Contrastive Learning—0
Towards Open Intent Discovery for Conversational Text—0
From Intent Discovery to Recognition with Topic Modeling and Synthetic Data—0
Unknown Intent Detection Using Multi-Objective Optimization on Deep Learning Classifiers—0
Utilisation of open intent recognition models for customer support intent detection—0
Generalized Intent Discovery: Learning from Open World Dialogue SystemCode0
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine HesitancyCode0
Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent DiscoveryCode0
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All datasetsATISPersian-ATISSNIPS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1k-PCA + HDBSCANARI74.94—Unverified
#ModelMetricClaimedVerifiedStatus
1k-PCA + HDBSCANARI11.97—Unverified
#ModelMetricClaimedVerifiedStatus
1k-PCA + HDBSCANARI59.23—Unverified