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 31–40 of 344 papers

TitleStatusHype
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce—0
Exploring Description-Augmented Dataless Intent ClassificationCode0
Why do you cite? An investigation on citation intents and decision-making classification processes—0
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
Paraphrase and Aggregate with Large Language Models for Minimizing Intent Classification Errors—0
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks—0
DASB -- Discrete Audio and Speech Benchmark—0
Finding Task-specific Subnetworks in Multi-task Spoken Language Understanding Model—0
Self-Supervised Speech Representations are More Phonetic than SemanticCode0
Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-ClassificationCode0
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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