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
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
A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery—0
Utilisation of open intent recognition models for customer support intent detection—0
Going beyond research datasets: Novel intent discovery in the industry setting—0
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery—0
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering—0
Intent Discovery for Enterprise Virtual Assistants: Applications of Utterance Embedding and Clustering to Intent Mining—0
Generalized Intent Discovery: Learning from Open World Dialogue SystemCode0
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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