Papers Intent Classification
“Intent Classification” 태그가 달린 논문 375편 · 필터 해제
Ellipsoid-Based Decision Boundaries for Open Intent Classification
Textual open intent classification is crucial for real-world dialogue systems, enabling robust detection of unknown user intents without prior knowledge and contributing to the robustness of the system. While adaptive de…
Open Intent DetectionIntent ClassificationContrastive LearningText ClassificationMAFA: A Multi-Agent Framework for Enterprise-Scale Annotation with Configurable Task Adaptation
We present MAFA (Multi-Agent Framework for Annotation), a production-deployed system that transforms enterprise-scale annotation workflows through configurable multi-agent collaboration. Addressing the critical challenge…
Intent ClassificationStandard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects
Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are primarily spoken, and non-standard spellings cause issues in text processin…
Intent ClassificationVersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
Retrieval-Augmented Generation (RAG) systems fail when documents evolve through versioning-a ubiquitous characteristic of technical documentation. Existing approaches achieve only 58-64% accuracy on version-sensitive que…
Intent ClassificationChange DetectionTaxonomy of Comprehensive Safety for Clinical Agents
Safety is a paramount concern in clinical chatbot applications, where inaccurate or harmful responses can lead to serious consequences. Existing methods--such as guardrails and tool calling--often fall short in addressin…
Intent ClassificationAutoIntent: AutoML for Text Classification
AutoIntent is an automated machine learning tool for text classification tasks. Unlike existing solutions, AutoIntent offers end-to-end automation with embedding model selection, classifier optimization, and decision thr…
Multi-Label ClassificationIntent ClassificationText ClassificationWolBanking77: Wolof Banking Speech Intent Classification Dataset
Intent classification models have made a significant progress in recent years. However, previous studies primarily focus on high-resource language datasets, which results in a gap for low-resource languages and for regio…
Intent ClassificationMulti-Intent Recognition in Dialogue Understanding: A Comparison Between Smaller Open-Source LLMs
In this paper, we provide an extensive analysis of multi-label intent classification using Large Language Models (LLMs) that are open-source, publicly available, and can be run in consumer hardware. We use the MultiWOZ 2…
Natural Language UnderstandingIntent ClassificationIntent Recognition"Where does it hurt?" -- Dataset and Study on Physician Intent Trajectories in Doctor Patient Dialogues
In a doctor-patient dialogue, the primary objective of physicians is to diagnose patients and propose a treatment plan. Medical doctors guide these conversations through targeted questioning to efficiently gather the inf…
Intent ClassificationAGENTiGraph: A Multi-Agent Knowledge Graph Framework for Interactive, Domain-Specific LLM Chatbots
AGENTiGraph is a user-friendly, agent-driven system that enables intuitive interaction and management of domain-specific data through the manipulation of knowledge graphs in natural language. It gives non-technical users…
Intent ClassificationKnowledge GraphsSOI Matters: Analyzing Multi-Setting Training Dynamics in Pretrained Language Models via Subsets of Interest
This work investigates the impact of multi-task, multi-lingual, and multi-source learning approaches on the robustness and performance of pretrained language models. To enhance this analysis, we introduce Subsets of Inte…
Intent ClassificationMulti-Task LearningSentiment AnalysisLeveraging GANs for citation intent classification and its impact on citation network analysis
Citations play a fundamental role in the scientific ecosystem, serving as a foundation for tracking the flow of knowledge, acknowledging prior work, and assessing scholarly influence. In scientometrics, they are also cen…
Citation Intent Classificationintent-classificationIntent ClassificationReward-Driven Interaction: Enhancing Proactive Dialogue Agents through User Satisfaction Prediction
Reward-driven proactive dialogue agents require precise estimation of user satisfaction as an intrinsic reward signal to determine optimal interaction strategies. Specifically, this framework triggers clarification quest…
intent-classificationIntent ClassificationSelf-Supervised LearningIntent Classification on Low-Resource Languages with Query Similarity Search
Intent classification is an important component of a functional Information Retrieval ecosystem. Many current approaches to intent classification, typically framed as a classification problem, can be problematic as inten…
ClassificationInformation Retrievalintent-classificationIntent ClassificationIn a Few Words: Comparing Weak Supervision and LLMs for Short Query Intent Classification
User intent classification is an important task in information retrieval. Previously, user intents were classified manually and automatically; the latter helped to avoid hand labelling of large datasets. Recent studies e…
ClassificationIn-Context LearningInformation Retrievalintent-classification+1ConvoGen: Enhancing Conversational AI with Synthetic Data: A Multi-Agent Approach
In this paper, we present ConvoGen: an innovative framework for generating synthetic conversational data using multi-agent systems. Our method leverages few-shot learning and introduces iterative sampling from a dynamica…
Conversation SummarizationFew-Shot Learningintent-classificationIntent ClassificationEfficient Intent-Based Filtering for Multi-Party Conversations Using Knowledge Distillation from LLMs
Large language models (LLMs) have showcased remarkable capabilities in conversational AI, enabling open-domain responses in chat-bots, as well as advanced processing of conversations like summarization, intent classifica…
intent-classificationIntent ClassificationKnowledge DistillationPythonPal: Enhancing Online Programming Education through Chatbot-Driven Personalized Feedback
The rise of online programming education has necessitated more effective, personalized interactions, a gap that PythonPal aims to fill through its innovative learning system integrated with a chatbot. This research delve…
Chatbotintent-classificationIntent ClassificationTestNUC: Enhancing Test-Time Computing Approaches through Neighboring Unlabeled Data Consistency
Test-time computing approaches, which leverage additional computational resources during inference, have been proven effective in enhancing large language model performance. This work introduces a novel, linearly scaling…
intent-classificationIntent ClassificationLanguage ModelingLanguage Modelling+1A Preliminary Exploration with GPT-4o Voice Mode
With the rise of multimodal large language models, GPT-4o stands out as a pioneering model, driving us to evaluate its capabilities. This report assesses GPT-4o across various tasks to analyze its audio processing and re…
Age ClassificationAudio Deepfake DetectionClassificationDeepFake Detection+7