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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
Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models	Dec 13, 2023	Class Incremental LearningIncremental Learning	CodeCode Available	1
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings	Dec 11, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution	Dec 10, 2023	Efficient Neural Networkintent-classification	—Unverified	0
Generalized zero-shot audio-to-intent classification	Nov 4, 2023	ClassificationGoal-Oriented Dialog	—Unverified	0
Dense Retrieval as Indirect Supervision for Large-space Decision Making	Oct 28, 2023	Decision MakingEntity Typing	CodeCode Available	0
Privacy-preserving Representation Learning for Speech Understanding	Oct 26, 2023	ClassificationEmotion Recognition	—Unverified	0
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery	Oct 25, 2023	Contrastive Learningintent-classification	—Unverified	0
TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification	Oct 17, 2023	intent-classificationIntent Classification	CodeCode Available	0
InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems	Oct 13, 2023	Dialogue State TrackingInformativeness	CodeCode Available	1
SNOiC: Soft Labeling and Noisy Mixup based Open Intent Classification Model	Oct 11, 2023	intent-classificationIntent Classification	—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