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 31–40 of 42 papers

TitleStatusHype
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering—0
New Intent Discovery with Pre-training and Contrastive LearningCode1
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine HesitancyCode0
Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive LearningCode1
UNICON: Unsupervised Intent Discovery via Semantic-level Contrastive Learning—0
Semi-supervised Intent Discovery with Contrastive Learning—0
TEXTOIR: An Integrated and Visualized Platform for Text Open Intent RecognitionCode0
Unknown Intent Detection Using Multi-Objective Optimization on Deep Learning Classifiers—0
Open Intent Discovery through Unsupervised Semantic Clustering and Dependency ParsingCode0
Intent Discovery With Or Without Labeled Data Using Dependency Parser—0
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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