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 71–80 of 344 papers

Title	Date	Tasks	Status	Hype	Score
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
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding	Jan 10, 2025	Automatic Speech RecognitionClassification	CodeCode Available	0	5
Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modeling	Apr 30, 2021	ClassificationGeneral Classification	CodeCode Available	0	5
DarijaBanking: A New Resource for Overcoming Language Barriers in Banking Intent Detection for Moroccan Arabic Speakers	May 26, 2024	intent-classificationIntent Classification	CodeCode Available	0	5
Attentively Embracing Noise for Robust Latent Representation in BERT	Dec 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	0	5
Exploring Robustness of Multilingual LLMs on Real-World Noisy Data	Jan 14, 2025	intent-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
Exploring Description-Augmented Dataless Intent Classification	Jul 25, 2024	AvgClassification	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
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling	Sep 6, 2016	Decoderintent-classification	CodeCode Available	0	5

Show:10 25 50

← PrevPage 8 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