Intent Classification
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Benchmarks
Most implemented
BERT for Joint Intent Classification and Slot Filling
Benchmarking Natural Language Understanding Services for building Conversational Agents
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
Papers
UpgradeBench: A Decision-Centric Benchmark for Upgrading Fine-Tuned LLM Specialists
Organizations maintain task-specific adapters for open-weight language models, and each new base-model release forces a migration decision: retain existing specialists, port adapters, refresh from preserved behavior, or …
Intent ClassificationDziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect
Automatic speech and language technologies are still heavily biased toward high-resource languages, limiting their applicability to dialectal and low-resource settings such as Algerian Dialect. This language presents add…
Natural Language UnderstandingText-To-Speech SynthesisIntent ClassificationResponse GenerationThe Significance of Style Diversity in Annotation-Free Synthetic Data Generation
Generating high-utility synthetic data for intent classification typically requires human-annotated seed data, which is often unavailable in fast-paced industrial settings. In this paper, we propose a framework for synth…
Synthetic Data GenerationIntent ClassificationDialogue GenerationDroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace
Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified open framework integrating six processing layers: RF signal classific…
Intent ClassificationGraph Neural NetworkDisentangling Adversarial Prompts: A Semantic-Graph Defense for Robust LLM Security
Large Language Models (LLMs) are increasingly vulnerable to adversarial prompts that exploit semantic ambiguities to bypass safety mechanisms, resulting in harmful or inappropriate outputs. Such attacks, including jailbr…
Computational EfficiencyIntent ClassificationIntent DetectionAI-Care: A Conversational Agentic System for Task Coordination in Alzheimer's Disease Care
Individuals with Alzheimer's disease (AD) and Alzheimer's disease-related dementia (ADRD) experience memory and thinking changes that impact their ability to use digital daily management tools. For example, adding an eve…
Intent Classification