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 301–325 of 344 papers

TitleStatusHype
Explainable Abuse Detection as Intent Classification and Slot FillingCode0
CitePrompt: Using Prompts to Identify Citation Intent in Scientific PapersCode0
ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model RobustnessCode0
The Open-World Lottery Ticket Hypothesis for OOD Intent ClassificationCode0
Bengali Intent Classification with Generative Adversarial BERTCode0
Predicting User Intents and Musical Attributes from Music Discovery ConversationsCode0
Dense Retrieval as Indirect Supervision for Large-space Decision MakingCode0
CAPE: Context-Aware Private Embeddings for Private Language LearningCode0
A new approach for fine-tuning sentence transformers for intent classification and out-of-scope detection tasksCode0
Evaluating N-best Calibration of Natural Language Understanding for Dialogue SystemsCode0
Metric Learning for Dynamic Text ClassificationCode0
Benchmarking Language-agnostic Intent Classification for Virtual Assistant PlatformsCode0
Augmenting Automation: Intent-Based User Instruction Classification with Machine LearningCode0
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleCode0
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech TranslationCode0
DarijaBanking: A New Resource for Overcoming Language Barriers in Banking Intent Detection for Moroccan Arabic SpeakersCode0
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision BoundaryCode0
A Speech Representation Anonymization Framework via Selective Noise PerturbationCode0
End-to-end Spoken Language Understanding with Tree-constrained Pointer GeneratorCode0
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain DetectionCode0
Intent Classification in Question-Answering Using LSTM ArchitecturesCode0
Attentively Embracing Noise for Robust Latent Representation in BERTCode0
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue systemCode0
Unsupervised Speech Representation Pooling Using Vector QuantizationCode0
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot FillingCode0
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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