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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 251–260 of 344 papers

Title	Date	Tasks	Status	Hype
NUBOT: Embedded Knowledge Graph With RASA Framework for Generating Semantic Intents Responses in Roman Urdu	Feb 20, 2021	Chatbotintent-classification	—Unverified	0
Leveraging Acoustic and Linguistic Embeddings from Pretrained speech and language Models for Intent Classification	Feb 15, 2021	ClassificationGeneral Classification	—Unverified	0
Neural Data Augmentation via Example Extrapolation	Feb 2, 2021	Data AugmentationDiversity	CodeCode Available	0
ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification	Jan 28, 2021	ClassificationData Augmentation	—Unverified	0
A survey of joint intent detection and slot-filling models in natural language understanding	Jan 20, 2021	ClassificationGeneral Classification	—Unverified	0
A character representation enhanced on-device Intent Classification	Jan 12, 2021	ClassificationGeneral Classification	—Unverified	0
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection	Jan 11, 2021	intent-classificationIntent Classification	—Unverified	0
Exploring Fluent Query Reformulations with Text-to-Text Transformers and Reinforcement Learning	Dec 18, 2020	intent-classificationIntent Classification	—Unverified	0
Generation of complex database queries and API calls from natural language utterances	Dec 15, 2020	intent-classificationIntent Classification	—Unverified	0
Using multiple ASR hypotheses to boost i18n NLU performance	Dec 7, 2020	Abstractive Text SummarizationAutomatic Speech Recognition	—Unverified	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