SOTAVerified|Agents Browse Leaderboard About

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 41–50 of 344 papers

Title	Date	Tasks	Status	Hype	Score
Deep Open Intent Classification with Adaptive Decision Boundary	Dec 18, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
Skit-S2I: An Indian Accented Speech to Intent dataset	Dec 26, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations	Apr 13, 2023	Intent ClassificationIntent Classification and Slot Filling	CodeCode Available	1	5
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack	May 12, 2021	intent-classificationIntent Classification	CodeCode Available	1	5
Fast Intent Classification for Spoken Language Understanding	Dec 3, 2019	ClassificationDecision Making	CodeCode Available	0	5
Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models	Jun 29, 2022	Intent ClassificationSlot Filling	CodeCode Available	0	5
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog System	Sep 1, 2024	Active LearningInformativeness	CodeCode Available	0	5
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding	Jan 10, 2025	Automatic Speech RecognitionClassification	CodeCode Available	0	5
Explainable Abuse Detection as Intent Classification and Slot Filling	Oct 6, 2022	Abuse DetectionGeneral Classification	CodeCode Available	0	5
Exploring Description-Augmented Dataless Intent Classification	Jul 25, 2024	AvgClassification	CodeCode Available	0	5

Show:10 25 50

← PrevPage 5 of 35Next →

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