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 1–42 of 42 papers

TitleStatusHype
IDAS: Intent Discovery with Abstractive SummarizationCode1
A Hybrid Architecture for Out of Domain Intent Detection and Intent DiscoveryCode1
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detectionCode1
New Intent Discovery with Pre-training and Contrastive LearningCode1
Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive LearningCode1
Intent Mining from past conversations for conversational agentCode1
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting FrameworkCode0
From Intent Discovery to Recognition with Topic Modeling and Synthetic Data—0
LANID: LLM-assisted New Intent DiscoveryCode0
Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialogues—0
IntentGPT: Few-shot Intent Discovery with Large Language Models—0
KULCQ: An Unsupervised Keyword-based Utterance Level Clustering Quality Metric—0
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents—0
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent DiscoveryCode0
Assured Automatic Programming via Large Language Models—0
A Survey of Ontology Expansion for Conversational Understanding—0
Controllable Discovery of Intents: Incremental Deep Clustering Using Semi-Supervised Contrastive Learning—0
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
Towards Real-world Scenario: Imbalanced New Intent DiscoveryCode0
RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations—0
New Intent Discovery with Attracting and Dispersing Prototype—0
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery—0
A Diffusion Weighted Graph Framework for New Intent DiscoveryCode0
Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent RecognitionCode0
Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPTCode0
Utilisation of open intent recognition models for customer support intent detection—0
Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent DiscoveryCode0
Going beyond research datasets: Novel intent discovery in the industry setting—0
A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery—0
Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent DiscoveryCode0
Generalized Intent Discovery: Learning from Open World Dialogue SystemCode0
Multimodal Intent Discovery from Livestream Videos—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
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine HesitancyCode0
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 Recognition—0
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
Towards Open Intent Discovery for Conversational Text—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