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 11–20 of 42 papers

TitleStatusHype
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent DiscoveryCode0
Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPTCode0
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine HesitancyCode0
Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent RecognitionCode0
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting FrameworkCode0
Towards Real-world Scenario: Imbalanced New Intent DiscoveryCode0
A Diffusion Weighted Graph Framework for New Intent DiscoveryCode0
LANID: LLM-assisted New Intent DiscoveryCode0
Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent DiscoveryCode0
Going beyond research datasets: Novel intent discovery in the industry setting—0
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Benchmark Results

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