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 101–125 of 344 papers

TitleStatusHype
Bengali Intent Classification with Generative Adversarial BERTCode0
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings—0
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution—0
Generalized zero-shot audio-to-intent classification—0
Dense Retrieval as Indirect Supervision for Large-space Decision MakingCode0
Privacy-preserving Representation Learning for Speech Understanding—0
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery—0
TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent ClassificationCode0
SNOiC: Soft Labeling and Noisy Mixup based Open Intent Classification Model—0
Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis—0
Conversational Factor Information Retrieval Model (ConFIRM)Code0
CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss—0
In-Context Learning for Text Classification with Many Labels—0
Leveraging Large Language Models for Exploiting ASR Uncertainty—0
Enhancing Pipeline-Based Conversational Agents with Large Language Models—0
Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification—0
Leveraging Pretrained ASR Encoders for Effective and Efficient End-to-End Speech Intent Classification and Slot Filling—0
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-trainingCode0
Reliable and Interpretable Drift Detection in Streams of Short Texts—0
CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training—0
TaDSE: Template-aware Dialogue Sentence Embeddings—0
ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model RobustnessCode0
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding—0
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech TranslationCode0
Exploring Zero and Few-shot Techniques for Intent Classification—0
Show:102550
← PrevPage 5 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