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 251–300 of 344 papers

TitleStatusHype
NUBOT: Embedded Knowledge Graph With RASA Framework for Generating Semantic Intents Responses in Roman Urdu—0
Leveraging Acoustic and Linguistic Embeddings from Pretrained speech and language Models for Intent Classification—0
Neural Data Augmentation via Example ExtrapolationCode0
ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification—0
A survey of joint intent detection and slot-filling models in natural language understanding—0
A character representation enhanced on-device Intent Classification—0
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection—0
Exploring Fluent Query Reformulations with Text-to-Text Transformers and Reinforcement Learning—0
Generation of complex database queries and API calls from natural language utterances—0
Using multiple ASR hypotheses to boost i18n NLU performance—0
Delexicalized Paraphrase Generation—0
Attentively Embracing Noise for Robust Latent Representation in BERTCode0
Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems—0
STIL - Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++Code0
Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hypotheses with Hierarchical Attention—0
Meta learning to classify intent and slot labels with noisy few shot examples—0
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages—0
Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey—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
SciWING– A Software Toolkit for Scientific Document Processing—0
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
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
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data—0
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
Fast Intent Classification for Spoken Language UnderstandingCode0
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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