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
New Intent Discovery with Pre-training and Contrastive LearningCode1
Intent Mining from past conversations for conversational agentCode1
A Hybrid Architecture for Out of Domain Intent Detection and Intent DiscoveryCode1
IDAS: Intent Discovery with Abstractive SummarizationCode1
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detectionCode1
Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive LearningCode1
UNICON: Unsupervised Intent Discovery via Semantic-level Contrastive Learning—0
Assured Automatic Programming via Large Language Models—0
A Survey of Ontology Expansion for Conversational Understanding—0
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents—0
Controllable Discovery of Intents: Incremental Deep Clustering Using Semi-Supervised Contrastive Learning—0
Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialogues—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
Intent Discovery With Or Without Labeled Data Using Dependency Parser—0
IntentGPT: Few-shot Intent Discovery with Large Language Models—0
KULCQ: An Unsupervised Keyword-based Utterance Level Clustering Quality Metric—0
Multimodal Intent Discovery from Livestream Videos—0
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
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting FrameworkCode0
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
Open Intent Discovery through Unsupervised Semantic Clustering and Dependency ParsingCode0
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent DiscoveryCode0
A Diffusion Weighted Graph Framework for New Intent DiscoveryCode0
Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent DiscoveryCode0
Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent RecognitionCode0
TEXTOIR: An Integrated and Visualized Platform for Text Open Intent RecognitionCode0
LANID: LLM-assisted New Intent DiscoveryCode0
Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPTCode0
A Clustering Framework for Unsupervised and Semi-supervised New Intent DiscoveryCode0
Towards Real-world Scenario: Imbalanced New Intent DiscoveryCode0
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Benchmark Results

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