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 126–150 of 344 papers

TitleStatusHype
An Exploration into the Performance of Unsupervised Cross-Task Speech Representations for "In the Wild'' Edge Applications—0
ReMask: A Robust Information-Masking Approach for Domain Counterfactual GenerationCode0
CitePrompt: Using Prompts to Identify Citation Intent in Scientific PapersCode0
Effective Open Intent Classification with K-center Contrastive Learning and Adjustable Decision BoundaryCode0
Unsupervised Speech Representation Pooling Using Vector QuantizationCode0
Ericson: An Interactive Open-Domain Conversational Search Agent—0
Efficiently Aligned Cross-Lingual Transfer Learning for Conversational Tasks using Prompt-TuningCode0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval—0
Improving the Intent Classification accuracy in Noisy Environment—0
Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information—0
Conversation Style Transfer using Few-Shot Learning—0
Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction—0
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
The Massively Multilingual Natural Language Understanding 2022 (MMNLU-22) Workshop and Competition—0
Zero-Shot Learning for Joint Intent and Slot Labeling—0
ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling—0
Multitask Learning for Low Resource Spoken Language Understanding—0
Introducing Semantics into Speech Encoders—0
Prompt Learning for Domain Adaptation in Task-Oriented Dialogue—0
Multilingual Name Entity Recognition and Intent Classification Employing Deep Learning Architectures—0
token2vec: A Joint Self-Supervised Pre-training Framework Using Unpaired Speech and Text—0
End-to-end Spoken Language Understanding with Tree-constrained Pointer GeneratorCode0
End-to-End Speech to Intent Prediction to improve E-commerce Customer Support Voicebot in Hindi and English—0
arXivEdits: Understanding the Human Revision Process in Scientific Writing—0
Learning Better Intent Representations for Financial Open Intent Classification—0
Show:102550
← PrevPage 6 of 14Next →
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