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

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Showing 331–340 of 344 papers

TitleStatusHype
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
Diverse Few-Shot Text Classification with Multiple MetricsCode0
Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa—0
Forewords—0
A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification—0
Open-Domain Neural Dialogue Systems—0
Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks—0
Robust Task Clustering for Deep Many-Task Learning—0
Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders—0
User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario—0
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All datasetsSLURPMASSIVEKUAKE-QICORCAS-I

Benchmark Results

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