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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 111–120 of 344 papers

Title	Date	Tasks	Status	Hype	Score
Evaluating N-best Calibration of Natural Language Understanding for Dialogue Systems	Sep 1, 2022	Classificationintent-classification	CodeCode Available	0	5
Exploring Robustness of Multilingual LLMs on Real-World Noisy Data	Jan 14, 2025	intent-classificationIntent Classification	CodeCode Available	0	5
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding	May 15, 2021	intent-classificationIntent Classification	CodeCode Available	0	5
End-to-end Spoken Language Understanding with Tree-constrained Pointer Generator	Oct 29, 2022	intent-classificationIntent Classification	CodeCode Available	0	5
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems	Sep 10, 2021	dialog state trackingFew-Shot Learning	—Unverified	0	0
A Single Example Can Improve Zero-Shot Data Generation	Aug 16, 2021	intent-classificationIntent Classification	—Unverified	0	0
CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training	May 27, 2023	intent-classificationIntent Classification	—Unverified	0	0
Ericson: An Interactive Open-Domain Conversational Search Agent	Apr 5, 2023	Conversational SearchDialogue Management	—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 Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval	Mar 28, 2023	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