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 201225 of 344 papers

TitleStatusHype
CAPE: Context-Aware Private Embeddings for Private Language LearningCode0
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain DetectionCode0
A Single Example Can Improve Zero-Shot Data Generation0
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
Exploring the Role of Context in Utterance-level Emotion, Act and Intent Classification in Conversations: An Empirical StudyCode1
Single Example Can Improve Zero-Shot Data Generation0
Semi-supervised Meta-learning for Cross-domain Few-shot Intent Classification0
Improved Text Classification via Contrastive Adversarial Training0
End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents0
Word-Free Spoken Language Understanding for Mandarin-Chinese0
Representation based meta-learning for few-shot spoken intent recognitionCode0
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU0
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection0
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent DetectionCode1
Optimizing NLU Reranking Using Entity Resolution Signals in Multi-domain Dialog Systems0
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language UnderstandingCode0
Meta-Inductive Node Classification across Graphs0
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language AttackCode1
Joint Text and Label Generation for Spoken Language Understanding0
Out-of-Scope Domain and Intent Classification through Hierarchical Joint ModelingCode0
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and SystemCode1
Fuzzy Classification of Multi-intent Utterances0
Adapting Long Context NLM for ASR Rescoring in Conversational Agents0
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase0
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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