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 201–250 of 344 papers

TitleStatusHype
SNOiC: Soft Labeling and Noisy Mixup based Open Intent Classification Model—0
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution—0
Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction—0
Strategies to Improve Few-shot Learning for Intent Classification and Slot-Filling—0
TaDSE: Template-aware Dialogue Sentence Embeddings—0
TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding—0
The Devil is in the Details: On Models and Training Regimes for Few-Shot Intent Classification—0
The impact of domain-specific representations on BERT-based multi-domain spoken language understanding—0
The Massively Multilingual Natural Language Understanding 2022 (MMNLU-22) Workshop and Competition—0
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model—0
token2vec: A Joint Self-Supervised Pre-training Framework Using Unpaired Speech and Text—0
Towards ASR Robust Spoken Language Understanding Through In-Context Learning With Word Confusion Networks—0
Towards Better Citation Intent Classification—0
Towards Explainable Dialogue System: Explaining Intent Classification using Saliency Techniques—0
Towards Textual Out-of-Domain Detection without In-Domain Labels—0
Training data reduction for multilingual Spoken Language Understanding systems—0
Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information—0
User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario—0
User Intent Inference for Web Search and Conversational Agents—0
Using multiple ASR hypotheses to boost i18n NLU performance—0
Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders—0
Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding—0
Adapting Long Context NLM for ASR Rescoring in Conversational Agents—0
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing—0
Why do you cite? An investigation on citation intents and decision-making classification processes—0
Wizard of Tasks: A Novel Conversational Dataset for Solving Real-World Tasks in Conversational Settings—0
Word-Free Spoken Language Understanding for Mandarin-Chinese—0
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 for Joint Intent and Slot Labeling—0
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce—0
Zero-Shot Learning with Common Sense Knowledge Graphs—0
A character representation enhanced on-device Intent Classification—0
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification—0
A Comparison of LSTM and BERT for Small Corpus—0
Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages—0
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning—0
A Deep Learning Approach to Integrate Human-Level Understanding in a Chatbot—0
Adversarial Training for Multi-task and Multi-lingual Joint Modeling of Utterance Intent Classification—0
A Financial Service Chatbot based on Deep Bidirectional Transformers—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
A Joint Learning Framework With BERT for Spoken Language Understanding—0
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems—0
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval—0
An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks—0
Analyzing the Impact of Varied Window Hyper-parameters on Deep CNN for sEMG based Motion Intent Classification—0
A new data augmentation method for intent classification enhancement and its application on spoken conversation datasets—0
An Explicit-Joint and Supervised-Contrastive Learning Framework 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
A Preliminary Exploration with GPT-4o Voice Mode—0
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection—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