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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 11–20 of 344 papers

Title	Date	Tasks	Status	Hype
End-to-End Slot Alignment and Recognition for Cross-Lingual NLU	Apr 29, 2020	Cross-Lingual TransferGoal-Oriented Dialog	CodeCode Available	1
Example-Driven Intent Prediction with Observers	Oct 17, 2020	Attributeintent-classification	CodeCode Available	1
Induction Networks for Few-Shot Text Classification	Feb 27, 2019	Few-Shot Text ClassificationGeneral Classification	CodeCode Available	1
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler	Mar 26, 2024	In-Context Learningintent-classification	CodeCode Available	1
A Multi-Task BERT Model for Schema-Guided Dialogue State Tracking	Jul 2, 2022	Dialogue State TrackingIntent Classification	CodeCode Available	1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection	Jun 8, 2021	intent-classificationIntent Classification	CodeCode Available	1
Benchmarking Natural Language Understanding Services for building Conversational Agents	Mar 13, 2019	BenchmarkingGeneral Classification	CodeCode Available	1
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction	Sep 4, 2019	BenchmarkingGeneral Classification	CodeCode Available	1
Search4Code: Code Search Intent Classification Using Weak Supervision	Nov 24, 2020	ClassificationCode Search	CodeCode Available	1
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark	Jun 15, 2021	Intent ClassificationMedical Concept Normalization	CodeCode Available	1

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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