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Intent Classification

Intent Classification is the task of correctly labeling a natural language utterance from a predetermined set of intents

Source: Multi-Layer Ensembling Techniques for Multilingual Intent Classification

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 51–60 of 344 papers

Title	Date	Tasks	Status	Hype
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification	Oct 9, 2019	Data AugmentationGeneral Classification	—Unverified	0
Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders	Mar 7, 2024	Clusteringintent-classification	—Unverified	0
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding	May 22, 2023	GPUIn-Context Learning	—Unverified	0
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection	May 1, 2022	intent-classificationIntent Classification	—Unverified	0
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch	Oct 24, 2024	Cross-Lingual TransferDecoder	—Unverified	0
A Joint Learning Framework With BERT for Spoken Language Understanding	Nov 20, 2019	Decoderintent-classification	—Unverified	0
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce	Aug 4, 2024	intent-classificationIntent Classification	—Unverified	0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network	Jun 19, 2020	ChatbotInformation Retrieval	—Unverified	0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism	Jun 5, 2022	Classificationintent-classification	—Unverified	0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque	May 1, 2020	ClassificationGeneral Classification	—Unverified	0

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All datasets SLURP MASSIVE KUAKE-QIC ORCAS-I

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TDT 0-8	Accuracy (%)	90.07	—	Unverified
2	Partially Fine-tuned HuBERT	Accuracy (%)	87.51	—	Unverified
3	Multi-SLURP	Accuracy (%)	78.33	—	Unverified
4	Finstreder (Conformer)	Accuracy (%)	53.11	—	Unverified
5	Finstreder (Quartznet)	Accuracy (%)	43.15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	mT5 Base (encoder-only)	Intent Accuracy	86.1	—	Unverified
2	mT5 Base (text-to-text)	Intent Accuracy	85.3	—	Unverified
3	XLM-R Base	Intent Accuracy	85.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-wwm-ext-base	Accuracy	85.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT (query + URL)	F1-score	0.77	—	Unverified