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 151175 of 344 papers

TitleStatusHype
ORCAS-I: Queries Annotated with Intent using Weak SupervisionCode0
KNN-Contrastive Learning for Out-of-Domain Intent Classification0
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification0
Knowledge Distillation Meets Few-Shot Learning: An Approach for Few-Shot Intent Classification Within and Across Domains0
Label Errors in BANKING770
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection0
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse LanguagesCode2
Learning to Classify Open Intent via Soft Labeling and Manifold MixupCode0
Redwood: Using Collision Detection to Grow a Large-Scale Intent Classification DatasetCode0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data0
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model0
Quick Starting Dialog Systems with Paraphrase Generation0
Data Augmentation for Intent Classification with Off-the-shelf Large Language ModelsCode1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTCode1
A Speech Representation Anonymization Framework via Selective Noise PerturbationCode0
Towards Textual Out-of-Domain Detection without In-Domain Labels0
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling0
A new data augmentation method for intent classification enhancement and its application on spoken conversation datasets0
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing0
pNLP-Mixer: an Efficient all-MLP Architecture for LanguageCode1
mSLAM: Massively multilingual joint pre-training for speech and text0
A Deep Learning Approach to Integrate Human-Level Understanding in a Chatbot0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF0
Training data reduction for multilingual Spoken Language Understanding systems0
Multi-task pre-finetuning for zero-shot cross lingual transfer0
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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