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 1–25 of 344 papers

TitleStatusHype
Leveraging GANs for citation intent classification and its impact on citation network analysisCode0
Reward-Driven Interaction: Enhancing Proactive Dialogue Agents through User Satisfaction Prediction—0
Intent Classification on Low-Resource Languages with Query Similarity Search—0
In a Few Words: Comparing Weak Supervision and LLMs for Short Query Intent Classification—0
Efficient Intent-Based Filtering for Multi-Party Conversations Using Knowledge Distillation from LLMs—0
ConvoGen: Enhancing Conversational AI with Synthetic Data: A Multi-Agent Approach—0
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
Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document RevisionsCode1
Efficacy of Synthetic Data as a Benchmark—0
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution 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