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

Showing 150 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
Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language ModelsCode1
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detectionCode1
pNLP-Mixer: an Efficient all-MLP Architecture for LanguageCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
Improving End-to-End SLU performance with Prosodic Attention and DistillationCode1
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue SystemCode1
Reconstructing Capsule Networks for Zero-shot Intent ClassificationCode1
SLURP: A Spoken Language Understanding Resource PackageCode1
ViMQ: A Vietnamese Medical Question Dataset for Healthcare Dialogue System DevelopmentCode1
Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible InputsCode1
Example-Driven Intent Prediction with ObserversCode1
A Multi-Task BERT Model for Schema-Guided Dialogue State TrackingCode1
End-to-End Slot Alignment and Recognition for Cross-Lingual NLUCode1
Intent Classification and Slot Filling for Privacy PoliciesCode1
ITALIC: An Italian Intent Classification DatasetCode1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTCode1
MTSI-BERT: A Session-aware Knowledge-based Conversational AgentCode1
Phoneme-BERT: Joint Language Modelling of Phoneme Sequence and ASR TranscriptCode1
Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent ClassificationCode1
BERT for Joint Intent Classification and Slot FillingCode1
Stacked DeBERT: All Attention in Incomplete Data for Text ClassificationCode1
Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document RevisionsCode1
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent ClassificationCode1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent DetectionCode1
Exploring the Role of Context in Utterance-level Emotion, Act and Intent Classification in Conversations: An Empirical StudyCode1
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and SystemCode1
Induction Networks for Few-Shot Text ClassificationCode1
Learning Dialogue Representations from Consecutive UtterancesCode1
Search4Code: Code Search Intent Classification Using Weak SupervisionCode1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot FillerCode1
ConveRT: Efficient and Accurate Conversational Representations from TransformersCode1
InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue SystemsCode1
An Evaluation Dataset for Intent Classification and Out-of-Scope PredictionCode1
Interactive Classification by Asking Informative QuestionsCode1
Data Augmentation for Intent Classification with Off-the-shelf Large Language ModelsCode1
Learn or Recall? Revisiting Incremental Learning with Pre-trained Language ModelsCode1
Deep Open Intent Classification with Adaptive Decision BoundaryCode1
Skit-S2I: An Indian Accented Speech to Intent datasetCode1
Efficient Sequence Transduction by Jointly Predicting Tokens and DurationsCode1
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language AttackCode1
Fast Intent Classification for Spoken Language UnderstandingCode0
Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text modelsCode0
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog SystemCode0
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language UnderstandingCode0
Explainable Abuse Detection as Intent Classification and Slot FillingCode0
Exploring Description-Augmented Dataless Intent ClassificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TDT 0-8Accuracy (%)90.07Unverified
2Partially Fine-tuned HuBERTAccuracy (%)87.51Unverified
3Multi-SLURPAccuracy (%)78.33Unverified
4Finstreder (Conformer)Accuracy (%)53.11Unverified
5Finstreder (Quartznet)Accuracy (%)43.15Unverified
#ModelMetricClaimedVerifiedStatus
1mT5 Base (encoder-only)Intent Accuracy86.1Unverified
2mT5 Base (text-to-text)Intent Accuracy85.3Unverified
3XLM-R BaseIntent Accuracy85.1Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-wwm-ext-baseAccuracy85.5Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (query + URL)F1-score0.77Unverified