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 51–75 of 344 papers

TitleStatusHype
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data—0
Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders—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
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch—0
CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots—0
A Joint Learning Framework With BERT for Spoken Language Understanding—0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network—0
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism—0
CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training—0
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems—0
A Single Example Can Improve Zero-Shot Data Generation—0
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—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
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning—0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding—0
Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling—0
An Exploration into the Performance of Unsupervised Cross-Task Speech Representations for "In the Wild'' Edge Applications—0
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling—0
Balancing Accuracy and Efficiency in Multi-Turn Intent Classification for LLM-Powered Dialog Systems in Production—0
A Financial Service Chatbot based on Deep Bidirectional Transformers—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