SOTAVerified

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

Showing 2650 of 344 papers

TitleStatusHype
Stacked DeBERT: All Attention in Incomplete Data for Text ClassificationCode1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent DetectionCode1
ViMQ: A Vietnamese Medical Question Dataset for Healthcare Dialogue System DevelopmentCode1
Skit-S2I: An Indian Accented Speech to Intent datasetCode1
Reconstructing Capsule Networks for Zero-shot Intent ClassificationCode1
InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue SystemsCode1
Search4Code: Code Search Intent Classification Using Weak SupervisionCode1
Data Augmentation for Intent Classification with Off-the-shelf Large Language ModelsCode1
Deep Open Intent Classification with Adaptive Decision BoundaryCode1
Example-Driven Intent Prediction with ObserversCode1
Exploring the Role of Context in Utterance-level Emotion, Act and Intent Classification in Conversations: An Empirical StudyCode1
An Evaluation Dataset for Intent Classification and Out-of-Scope PredictionCode1
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot FillerCode1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Intent Classification and Slot Filling for Privacy PoliciesCode1
ITALIC: An Italian Intent Classification DatasetCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTCode1
Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent ClassificationCode1
A Single Example Can Improve Zero-Shot Data Generation0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval0
arXivEdits: Understanding the Human Revision Process in Scientific Writing0
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems0
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TDT 0-8Accuracy (%)90.07Unverified
2Partially Fine-tuned HuBERTAccuracy (%)87.51Unverified
3Multi-SLURPAccuracy (%)78.33Unverified
4Finstreder (Conformer)Accuracy (%)53.11Unverified
5Finstreder (Quartznet)Accuracy (%)43.15Unverified
#ModelMetricClaimedVerifiedStatus
1mT5 Base (encoder-only)Intent Accuracy86.1Unverified
2mT5 Base (text-to-text)Intent Accuracy85.3Unverified
3XLM-R BaseIntent Accuracy85.1Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-wwm-ext-baseAccuracy85.5Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (query + URL)F1-score0.77Unverified