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 251–300 of 344 papers

TitleStatusHype
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism—0
A Single Example Can Improve Zero-Shot Data Generation—0
A Study on the Influence of Architecture Complexity of RNNs for Intent Classification in E-Commerce Chats in Bahasa Indonesia—0
A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog—0
A survey of joint intent detection and slot-filling models in natural language understanding—0
A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification—0
A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features—0
Audio-to-Intent Using Acoustic-Textual Subword Representations from End-to-End ASR—0
Augmented Natural Language for Generative Sequence Labeling—0
Augmenting Task-Oriented Dialogue Systems with Relation Extraction—0
ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling—0
Balancing Accuracy and Efficiency in Multi-Turn Intent Classification for LLM-Powered Dialog Systems in Production—0
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling—0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch—0
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding—0
Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders—0
CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots—0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network—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
Class Embeddings for Improved Out-of-Scope Detection in Intent Classification—0
CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection—0
Conformal Intent Classification and Clarification for Fast and Accurate Intent Recognition—0
Controlled Data Generation via Insertion Operations for NLU—0
Controlled Text Generation for Data Augmentation in Intelligent Artificial Agents—0
Conversation Style Transfer using Few-Shot Learning—0
ConvoGen: Enhancing Conversational AI with Synthetic Data: A Multi-Agent Approach—0
CourseAssist: Pedagogically Appropriate AI Tutor for Computer Science Education—0
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings—0
Cross-lingual intent classification in a low resource industrial setting—0
CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss—0
DASB -- Discrete Audio and Speech Benchmark—0
Data Augmentation for Intent Classification with Generic Large Language Models—0
Data Augmentation for Intent Classification—0
Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain—0
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase—0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding—0
Data Collection for Dialogue System: A Startup Perspective—0
Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems—0
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data—0
Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling—0
DeepPavlov: Open-Source Library for Dialogue Systems—0
Delexicalized Paraphrase Generation—0
Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing—0
Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification—0
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection—0
Domain- and Task-Adaptation for VaccinChatNL, a Dutch COVID-19 FAQ Answering Corpus and Classification Model—0
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification—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