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 181–190 of 344 papers

TitleStatusHype
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model—0
token2vec: A Joint Self-Supervised Pre-training Framework Using Unpaired Speech and Text—0
Towards ASR Robust Spoken Language Understanding Through In-Context Learning With Word Confusion Networks—0
Towards Better Citation Intent Classification—0
Towards Explainable Dialogue System: Explaining Intent Classification using Saliency Techniques—0
Towards Textual Out-of-Domain Detection without In-Domain Labels—0
Training data reduction for multilingual Spoken Language Understanding systems—0
Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information—0
User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario—0
User Intent Inference for Web Search and Conversational Agents—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