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

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Showing 101–150 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
Leveraging GANs for citation intent classification and its impact on citation network analysisCode0
Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text modelsCode0
Efficiently Aligned Cross-Lingual Transfer Learning for Conversational Tasks using Prompt-TuningCode0
Joint Automatic Speech Recognition And Structure Learning For Better Speech UnderstandingCode0
Learning to Classify Open Intent via Soft Labeling and Manifold MixupCode0
Metric Learning for Dynamic Text ClassificationCode0
Intent Classification in Question-Answering Using LSTM ArchitecturesCode0
Fast Intent Classification for Spoken Language UnderstandingCode0
Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-ClassificationCode0
ImpactCite: An XLNet-based method for Citation Impact AnalysisCode0
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case StudyCode0
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue systemCode0
Uddessho: An Extensive Benchmark Dataset for Multimodal Author Intent Classification in Low-Resource Bangla LanguageCode0
Exploring Fluent Query Reformulations with Text-to-Text Transformers and Reinforcement Learning—0
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems—0
A Single Example Can Improve Zero-Shot Data Generation—0
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification—0
CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training—0
Ericson: An Interactive Open-Domain Conversational Search Agent—0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism—0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval—0
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU—0
Enhancing Pipeline-Based Conversational Agents with Large Language Models—0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network—0
End-to-End Speech to Intent Prediction to improve E-commerce Customer Support Voicebot in Hindi and English—0
End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents—0
CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots—0
arXivEdits: Understanding the Human Revision Process in Scientific Writing—0
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems—0
End to End Binarized Neural Networks for Text Classification—0
Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders—0
Empirical Studies of Institutional Federated Learning For Natural Language Processing—0
Emora: An Inquisitive Social Chatbot Who Cares For You—0
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding—0
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection—0
Efficient Intent-Based Filtering for Multi-Party Conversations Using Knowledge Distillation from LLMs—0
Efficacy of Synthetic Data as a Benchmark—0
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch—0
A Joint Learning Framework With BERT for Spoken Language Understanding—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification—0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data—0
A Preliminary Exploration with GPT-4o Voice Mode—0
Domain- and Task-Adaptation for VaccinChatNL, a Dutch COVID-19 FAQ Answering Corpus and Classification Model—0
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection—0
Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification—0
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling—0
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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