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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 251–260 of 344 papers

Title	Date	Tasks	Status	Hype	Score
arXivEdits: Understanding the Human Revision Process in Scientific Writing	Oct 26, 2022	intent-classificationIntent Classification	—Unverified	0	0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism	Jun 5, 2022	Classificationintent-classification	—Unverified	0	0
A Single Example Can Improve Zero-Shot Data Generation	Aug 16, 2021	intent-classificationIntent Classification	—Unverified	0	0
A Study on the Influence of Architecture Complexity of RNNs for Intent Classification in E-Commerce Chats in Bahasa Indonesia	Jul 1, 2020	intent-classificationIntent Classification	—Unverified	0	0
A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog	Jul 26, 2022	Classificationintent-classification	—Unverified	0	0
A survey of joint intent detection and slot-filling models in natural language understanding	Jan 20, 2021	ClassificationGeneral Classification	—Unverified	0	0
A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification	Nov 1, 2017	General ClassificationInformation Retrieval	—Unverified	0	0
A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features	Nov 22, 2019	Activity Recognitionintent-classification	—Unverified	0	0
Audio-to-Intent Using Acoustic-Textual Subword Representations from End-to-End ASR	Oct 21, 2022	intent-classificationIntent Classification	—Unverified	0	0
Augmented Natural Language for Generative Sequence Labeling	Sep 15, 2020	intent-classificationIntent Classification	—Unverified	0	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