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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 61–70 of 344 papers

Title	Date	Tasks	Status	Hype	Score
Leveraging GANs for citation intent classification and its impact on citation network analysis	May 27, 2025	Citation Intent Classificationintent-classification	CodeCode Available	0	5
Bengali Intent Classification with Generative Adversarial BERT	Dec 17, 2023	ClassificationGenerative Adversarial Network	CodeCode Available	0	5
Fast Intent Classification for Spoken Language Understanding	Dec 3, 2019	ClassificationDecision Making	CodeCode Available	0	5
Benchmarking Language-agnostic Intent Classification for Virtual Assistant Platforms	Jul 1, 2022	BenchmarkingClassification	CodeCode Available	0	5
Exploring Robustness of Multilingual LLMs on Real-World Noisy Data	Jan 14, 2025	intent-classificationIntent Classification	CodeCode Available	0	5
Evaluating N-best Calibration of Natural Language Understanding for Dialogue Systems	Sep 1, 2022	Classificationintent-classification	CodeCode Available	0	5
Explainable Abuse Detection as Intent Classification and Slot Filling	Oct 6, 2022	Abuse DetectionGeneral Classification	CodeCode Available	0	5
Augmenting Automation: Intent-Based User Instruction Classification with Machine Learning	Mar 2, 2024	intent-classificationIntent Classification	CodeCode Available	0	5
A new approach for fine-tuning sentence transformers for intent classification and out-of-scope detection tasks	Oct 17, 2024	Classificationintent-classification	CodeCode Available	0	5
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble	Oct 20, 2022	Contrastive Learningintent-classification	CodeCode Available	0	5

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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