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 81–90 of 344 papers

TitleStatusHype
Adversarial Training for Multi-task and Multi-lingual Joint Modeling of Utterance Intent Classification—0
Data Augmentation for Intent Classification with Generic Large Language Models—0
Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain—0
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase—0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding—0
Data Collection for Dialogue System: A Startup Perspective—0
Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems—0
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data—0
Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling—0
DASB -- Discrete Audio and Speech Benchmark—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