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 276300 of 344 papers

TitleStatusHype
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 Graphs0
Augmented Natural Language for Generative Sequence Labeling0
A Comparison of LSTM and BERT for Small Corpus0
Emora: An Inquisitive Social Chatbot Who Cares For You0
Simple is Better! Lightweight Data Augmentation for Low Resource Slot Filling and Intent Classification0
Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors0
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding0
Improving End-to-End Speech-to-Intent Classification with Reptile0
KBot: a Knowledge graph based chatBot for natural language understanding over linked data0
Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification0
Improving Intent Classification in an E-commerce Voice Assistant by Using Inter-Utterance Context0
A Study on the Influence of Architecture Complexity of RNNs for Intent Classification in E-Commerce Chats in Bahasa Indonesia0
IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection0
Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network0
User Intent Inference for Web Search and Conversational Agents0
Learning with Weak Supervision for Email Intent Detection0
ImpactCite: An XLNet-based method for Citation Impact AnalysisCode0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque0
Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data0
Learning to Classify Intents and Slot Labels Given a Handful of Examples0
A Financial Service Chatbot based on Deep Bidirectional Transformers0
Intent Classification in Question-Answering Using LSTM ArchitecturesCode0
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses0
Fast Intent Classification for Spoken Language UnderstandingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TDT 0-8Accuracy (%)90.07Unverified
2Partially Fine-tuned HuBERTAccuracy (%)87.51Unverified
3Multi-SLURPAccuracy (%)78.33Unverified
4Finstreder (Conformer)Accuracy (%)53.11Unverified
5Finstreder (Quartznet)Accuracy (%)43.15Unverified
#ModelMetricClaimedVerifiedStatus
1mT5 Base (encoder-only)Intent Accuracy86.1Unverified
2mT5 Base (text-to-text)Intent Accuracy85.3Unverified
3XLM-R BaseIntent Accuracy85.1Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-wwm-ext-baseAccuracy85.5Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (query + URL)F1-score0.77Unverified