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Intent Detection

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Intent Detection is a task of determining the underlying purpose or goal behind a user's search query given a context. The task plays a significant role in search and recommendations. A traditional approach for intent detection implies using an intent detector model to classify user search query into predefined intent categories, given a context. One of the key challenges of the task implies identifying user intents for cold-start sessions, i.e., search sessions initiated by a non-logged-in or unrecognized user.

Source: Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers <span class="description-source">

논문

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Intent Detection

논문

Flippi: End To End GenAI Assistant for E-Commerce

An Interdisciplinary Review of Commonsense Reasoning and Intent Detection

Invocable APIs derived from NL2SQL datasets for LLM Tool-Calling Evaluation

Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care

Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation

Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models

Learning Multimodal AI Algorithms for Amplifying Limited User Input into High-dimensional Control Space

Enhanced Urdu Intent Detection with Large Language Models and Prototype-Informed Predictive Pipelines

Improving Generalization in Intent Detection: GRPO with Reward-Based Curriculum Sampling

Fine-Grained Behavior and Lane Constraints Guided Trajectory Prediction Method

Intelligent Framework for Human-Robot Collaboration: Dynamic Ergonomics and Adaptive Decision-Making

Learning LLM Preference over Intra-Dialogue Pairs: A Framework for Utterance-level Understandings

Towards Refining Developer Questions using LLM-Based Named Entity Recognition for Developer Chatroom Conversations

Intention Recognition in Real-Time Interactive Navigation Maps

PSCon: Product Search Through Conversations

On-Device LLMs for Home Assistant: Dual Role in Intent Detection and Response Generation

Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study

Add Noise, Tasks, or Layers? MaiNLP at the VarDial 2025 Shared Task on Norwegian Dialectal Slot and Intent Detection

Fitting Different Interactive Information: Joint Classification of Emotion and Intention

Meta-Reflection: A Feedback-Free Reflection Learning Framework

HiTZ at VarDial 2025 NorSID: Overcoming Data Scarcity with Language Transfer and Automatic Data Annotation

Evaluating Pixel Language Models on Non-Standardized Languages

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning

Towards Intention Recognition for Robotic Assistants Through Online POMDP Planning

IntentGPT: Few-shot Intent Discovery with Large Language Models

A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents

Intent Detection in the Age of LLMs

Generate then Refine: Data Augmentation for Zero-shot Intent Detection

Benchmarking Adaptive Intelligence and Computer Vision on Human-Robot Collaboration

Discerning the Chaos: Detecting Adversarial Perturbations while Disentangling Intentional from Unintentional Noises

Experimental Evaluation of Machine Learning Models for Goal-oriented Customer Service Chatbot with Pipeline Architecture

EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models

Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection

MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLU

Interpretation of the Intent Detection Problem as Dynamics in a Low-dimensional Space