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 251–300 of 344 papers

TitleStatusHype
Meta learning to classify intent and slot labels with noisy few shot examples—0
SLURP: A Spoken Language Understanding Resource PackageCode1
Search4Code: Code Search Intent Classification Using Weak SupervisionCode1
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages—0
SciWING– A Software Toolkit for Scientific Document Processing—0
Empirical Studies of Institutional Federated Learning For Natural Language Processing—0
Iterative Feature Mining for Constraint-Based Data Collection to Increase Data Diversity and Model Robustness—0
Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes—0
Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey—0
Example-Driven Intent Prediction with ObserversCode1
End to End Binarized Neural Networks for Text Classification—0
Leveraging Unpaired Text Data for Training End-to-End Speech-to-Intent Systems—0
STIL -- Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++Code0
一种结合话语伪标签注意力的人机对话意图分类方法(A Human-machine Dialogue Intent Classification Method using Utterance Pseudo Label Attention)—0
Zero-Shot Learning with Common Sense Knowledge Graphs—0
Augmented Natural Language for Generative Sequence Labeling—0
A Comparison of LSTM and BERT for Small Corpus—0
Emora: An Inquisitive Social Chatbot Who Cares For You—0
Simple is Better! Lightweight Data Augmentation for Low Resource Slot Filling and Intent Classification—0
Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors—0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding—0
Improving End-to-End Speech-to-Intent Classification with Reptile—0
KBot: a Knowledge graph based chatBot for natural language understanding over linked data—0
Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification—0
Improving Intent Classification in an E-commerce Voice Assistant by Using Inter-Utterance Context—0
A Study on the Influence of Architecture Complexity of RNNs for Intent Classification in E-Commerce Chats in Bahasa Indonesia—0
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent ClassificationCode1
IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection—0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network—0
User Intent Inference for Web Search and Conversational Agents—0
Learning with Weak Supervision for Email Intent Detection—0
ImpactCite: An XLNet-based method for Citation Impact AnalysisCode0
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
MTSI-BERT: A Session-aware Knowledge-based Conversational AgentCode1
End-to-End Slot Alignment and Recognition for Cross-Lingual NLUCode1
Learning to Classify Intents and Slot Labels Given a Handful of Examples—0
A Financial Service Chatbot based on Deep Bidirectional Transformers—0
Intent Classification in Question-Answering Using LSTM ArchitecturesCode0
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses—0
Stacked DeBERT: All Attention in Incomplete Data for Text ClassificationCode1
Fast Intent Classification for Spoken Language UnderstandingCode0
A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features—0
A Joint Learning Framework With BERT for Spoken Language Understanding—0
Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems—0
ConveRT: Efficient and Accurate Conversational Representations from TransformersCode1
Interactive Classification by Asking Informative QuestionsCode1
Metric Learning for Dynamic Text ClassificationCode0
Cross-lingual intent classification in a low resource industrial setting—0
Reconstructing Capsule Networks for Zero-shot Intent ClassificationCode1
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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