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 101125 of 344 papers

TitleStatusHype
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
Effective Open Intent Classification with K-center Contrastive Learning and Adjustable Decision BoundaryCode0
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language UnderstandingCode0
Contrastive and Consistency Learning for Neural Noisy-Channel Model in Spoken Language UnderstandingCode0
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language UnderstandingCode0
Out-of-Scope Domain and Intent Classification through Hierarchical Joint ModelingCode0
Fast Intent Classification for Spoken Language UnderstandingCode0
STIL -- Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++Code0
Emu: Enhancing Multilingual Sentence Embeddings with Semantic SpecializationCode0
Structural Scaffolds for Citation Intent Classification in Scientific PublicationsCode0
Exploring Robustness of Multilingual LLMs on Real-World Noisy DataCode0
Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text modelsCode0
CAPE: Context-Aware Private Embeddings for Private Language LearningCode0
End-to-end Spoken Language Understanding with Tree-constrained Pointer GeneratorCode0
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue systemCode0
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems0
A Single Example Can Improve Zero-Shot Data Generation0
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification0
CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training0
Ericson: An Interactive Open-Domain Conversational Search Agent0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval0
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU0
Enhancing Pipeline-Based Conversational Agents with Large Language Models0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques0
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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