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 51–75 of 344 papers

TitleStatusHype
PythonPal: Enhancing Online Programming Education through Chatbot-Driven Personalized Feedback—0
TestNUC: Enhancing Test-Time Computing Approaches through Neighboring Unlabeled Data ConsistencyCode0
A Preliminary Exploration with GPT-4o Voice Mode—0
Exploring Robustness of Multilingual LLMs on Real-World Noisy DataCode0
Joint Automatic Speech Recognition And Structure Learning For Better Speech UnderstandingCode0
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language UnderstandingCode0
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case StudyCode0
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification—0
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision BoundaryCode0
Intent-Aware Dialogue Generation and Multi-Task Contrastive Learning for Multi-Turn Intent Classification—0
Balancing Accuracy and Efficiency in Multi-Turn Intent Classification for LLM-Powered Dialog Systems in Production—0
Predicting User Intents and Musical Attributes from Music Discovery ConversationsCode0
Improved intent classification based on context information using a windows-based approach—0
Building Dialogue Understanding Models for Low-resource Language Indonesian from Scratch—0
A new approach for fine-tuning sentence transformers for intent classification and out-of-scope detection tasksCode0
Intent Classification for Bank Chatbots through LLM Fine-Tuning—0
Efficacy of Synthetic Data as a Benchmark—0
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection—0
Uddessho: An Extensive Benchmark Dataset for Multimodal Author Intent Classification in Low-Resource Bangla LanguageCode0
LLM-based Weak Supervision Framework for Query Intent Classification in Video Search—0
LLMs Will Always Hallucinate, and We Need to Live With This—0
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog SystemCode0
Practical token pruning for foundation models in few-shot conversational virtual assistant systems—0
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce—0
Exploring Description-Augmented Dataless Intent ClassificationCode0
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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