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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 344 papers

TitleStatusHype
Uddessho: An Extensive Benchmark Dataset for Multimodal Author Intent Classification in Low-Resource Bangla LanguageCode0
LLM-based Weak Supervision Framework for Query Intent Classification in Video Search—0
LLMs Will Always Hallucinate, and We Need to Live With This—0
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog SystemCode0
Practical token pruning for foundation models in few-shot conversational virtual assistant systems—0
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
DarijaBanking: A New Resource for Overcoming Language Barriers in Banking Intent Detection for Moroccan Arabic SpeakersCode0
Contrastive and Consistency Learning for Neural Noisy-Channel Model in Spoken Language UnderstandingCode0
Luganda Speech Intent Recognition for IoT Applications—0
OmniActions: Predicting Digital Actions in Response to Real-World Multimodal Sensory Inputs with LLMs—0
CourseAssist: Pedagogically Appropriate AI Tutor for Computer Science Education—0
Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language ModelsCode1
New Semantic Task for the French Spoken Language Understanding MEDIA BenchmarkCode0
Conformal Intent Classification and Clarification for Fast and Accurate Intent Recognition—0
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot FillerCode1
LARA: Linguistic-Adaptive Retrieval-Augmentation for Multi-Turn Intent Classification—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