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 1–50 of 344 papers

TitleStatusHype
The First Evaluation of Chinese Human-Computer Dialogue TechnologyCode2
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse LanguagesCode2
Benchmarking Natural Language Understanding Services for building Conversational AgentsCode1
pNLP-Mixer: an Efficient all-MLP Architecture for LanguageCode1
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent ClassificationCode1
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue SystemCode1
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and SystemCode1
Efficient Sequence Transduction by Jointly Predicting Tokens and DurationsCode1
Learn or Recall? Revisiting Incremental Learning with Pre-trained Language ModelsCode1
Phoneme-BERT: Joint Language Modelling of Phoneme Sequence and ASR TranscriptCode1
Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible InputsCode1
Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document RevisionsCode1
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detectionCode1
BERT for Joint Intent Classification and Slot FillingCode1
A Multi-Task BERT Model for Schema-Guided Dialogue State TrackingCode1
ConveRT: Efficient and Accurate Conversational Representations from TransformersCode1
Induction Networks for Few-Shot Text ClassificationCode1
Improving End-to-End SLU performance with Prosodic Attention and DistillationCode1
Interactive Classification by Asking Informative QuestionsCode1
Learning Dialogue Representations from Consecutive UtterancesCode1
MTSI-BERT: A Session-aware Knowledge-based Conversational AgentCode1
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language AttackCode1
Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language ModelsCode1
SLURP: A Spoken Language Understanding Resource PackageCode1
End-to-End Slot Alignment and Recognition for Cross-Lingual NLUCode1
Stacked DeBERT: All Attention in Incomplete Data for Text ClassificationCode1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent DetectionCode1
ViMQ: A Vietnamese Medical Question Dataset for Healthcare Dialogue System DevelopmentCode1
Skit-S2I: An Indian Accented Speech to Intent datasetCode1
Reconstructing Capsule Networks for Zero-shot Intent ClassificationCode1
InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue SystemsCode1
Search4Code: Code Search Intent Classification Using Weak SupervisionCode1
Data Augmentation for Intent Classification with Off-the-shelf Large Language ModelsCode1
Deep Open Intent Classification with Adaptive Decision BoundaryCode1
Example-Driven Intent Prediction with ObserversCode1
Exploring the Role of Context in Utterance-level Emotion, Act and Intent Classification in Conversations: An Empirical StudyCode1
An Evaluation Dataset for Intent Classification and Out-of-Scope PredictionCode1
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot FillerCode1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Intent Classification and Slot Filling for Privacy PoliciesCode1
ITALIC: An Italian Intent Classification DatasetCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTCode1
Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent ClassificationCode1
A Single Example Can Improve Zero-Shot Data Generation—0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism—0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval—0
arXivEdits: Understanding the Human Revision Process in Scientific Writing—0
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems—0
A Closer Look At Feature Space Data Augmentation For Few-Shot 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