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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 161–170 of 344 papers

Title	Date	Tasks	Status	Hype	Score
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling	Oct 26, 2021	Contrastive Learningintent-classification	—Unverified	0	0
A Financial Service Chatbot based on Deep Bidirectional Transformers	Feb 17, 2020	Chatbotintent-classification	—Unverified	0	0
Data Collection for Dialogue System: A Startup Perspective	Jun 1, 2018	General Classificationintent-classification	—Unverified	0	0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding	Aug 6, 2020	intent-classificationIntent Classification	—Unverified	0	0
ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling	Nov 27, 2022	intent-classificationIntent Classification	—Unverified	0	0
InFoBERT: Zero-Shot Approach to Natural Language Understanding Using Contextualized Word Embedding	Sep 1, 2021	intent-classificationIntent Classification	—Unverified	0	0
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase	Apr 16, 2021	Data Augmentationintent-classification	—Unverified	0	0
Industry Scale Semi-Supervised Learning for Natural Language Understanding	Mar 29, 2021	intent-classificationIntent Classification	—Unverified	0	0
RNN based Incremental Online Spoken Language Understanding	Oct 23, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0	0
Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain	Sep 1, 2022	Data Augmentationintent-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