Tagged articles

12 articles

Page 1 of 1

May 29, 2024 · Artificial Intelligence

End-to-End Task-Oriented Dialogue Agent Construction Using Monte Carlo Simulation and LLM Fine-Tuning

This article presents an end‑to‑end approach for building task‑oriented dialogue agents by simulating user behavior with Monte Carlo methods, generating training data via LLMs, and efficiently fine‑tuning multiple large language models using LLaMA Factory, demonstrating significant improvements in intent recognition, slot filling, and contextual understanding.

Data GenerationLLM fine-tuningMonte Carlo simulation

0 likes · 17 min read

End-to-End Task-Oriented Dialogue Agent Construction Using Monte Carlo Simulation and LLM Fine-Tuning

Laiye Technology Team

Aug 29, 2022 · Artificial Intelligence

Evolution of Dialogue Management: From Rule‑Based to Data‑Driven Systems and Industrial Deployments

This article reviews the historical development of dialogue management—from early rule‑based and finite‑state approaches to modern data‑driven and reinforcement‑learning methods—and examines how major industry platforms such as Amazon Alexa, Amazon Lex, and RASA implement these techniques in practice.

Amazon AlexaData-drivenNLU

0 likes · 16 min read

Evolution of Dialogue Management: From Rule‑Based to Data‑Driven Systems and Industrial Deployments

58 Tech

Jun 24, 2022 · Artificial Intelligence

Reinforcement Learning for Lead Generation in Task‑Oriented Dialogue Systems

This article presents a reinforcement‑learning‑based approach to improve lead‑capture efficiency of a task‑oriented chatbot used in local services, detailing the system architecture, RL algorithms (DQN/DDQN), data construction, model training, offline and online evaluation, and the resulting commercial gains.

DQNLead Generationcustomer-service

0 likes · 27 min read

Reinforcement Learning for Lead Generation in Task‑Oriented Dialogue Systems

NetEase Smart Enterprise Tech+

Jun 14, 2022 · Artificial Intelligence

How Outbound Call Robots Work: Challenges and Optimizations in Voice Dialogue Systems

This article explains the architecture of outbound call robots, classifies dialogue system types, details pipeline and end‑to‑end task‑oriented designs, highlights technical challenges such as dialects and transcription errors, and presents optimization techniques like ASR correction and script improvement.

AI OptimizationASR correctionNLU

0 likes · 12 min read

How Outbound Call Robots Work: Challenges and Optimizations in Voice Dialogue Systems

Airbnb Technology Team

Nov 11, 2021 · Artificial Intelligence

Airbnb’s Task‑Oriented Dialogue System for Mutual Cancellation: Architecture, Data Collection, Modeling, and Deployment

Airbnb’s ATIS task‑oriented dialogue system for Mutual Cancellation combines hierarchical domain classification, Q&A‑style intent annotation, large‑scale RoBERTa pre‑training with multilingual fine‑tuning, multi‑turn context handling, GPU‑accelerated inference, and contextual‑bandit reinforcement learning to deliver a scalable, efficient customer‑support solution.

AIGPU deploymentmultilingual

0 likes · 22 min read

Airbnb’s Task‑Oriented Dialogue System for Mutual Cancellation: Architecture, Data Collection, Modeling, and Deployment

Laiye Technology Team

Jun 8, 2021 · Artificial Intelligence

Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue Systems

This paper presents a hierarchical reinforcement learning approach that jointly trains dialogue policy and natural language generation modules for task-oriented dialogue systems, achieving state‑of‑the‑art performance on MultiWOZ 2.0 and 2.1 while preserving response fluency.

MultiWOZdialogue policyhierarchical RL

0 likes · 10 min read

Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue Systems

DataFunTalk

Dec 30, 2020 · Artificial Intelligence

Meta-Dialog System: Using Meta-Learning for Fast Adaptation and Robustness in Task-Oriented Conversational AI

This article presents a meta‑learning based end‑to‑end task‑oriented dialogue system that quickly adapts to new scenarios with limited data and improves robustness through a human‑machine collaboration decision module, validated on extended‑bAbI benchmarks and real‑world Alibaba Cloud customer‑service applications.

Few‑Shot LearningMAMLdialogue system

0 likes · 15 min read

Meta-Dialog System: Using Meta-Learning for Fast Adaptation and Robustness in Task-Oriented Conversational AI

Alibaba Cloud Developer

Feb 7, 2020 · Artificial Intelligence

Tackling Scalability, Data Scarcity, and Training Efficiency in Dialogue Management Models

This article reviews the evolution of dialogue management models from rule‑based systems to deep‑learning approaches, identifies three major challenges—poor scalability, limited annotated data, and low training efficiency—and surveys recent research solutions including semantic matching, knowledge distillation, hierarchical reinforcement learning, model‑based RL, and human‑in‑the‑loop methods.

Conversational AIdata annotationdialogue management

0 likes · 44 min read

Tackling Scalability, Data Scarcity, and Training Efficiency in Dialogue Management Models

DataFunTalk

Nov 20, 2019 · Artificial Intelligence

Advances and Reflections on Human‑Machine Dialogue Technologies

This presentation reviews recent progress in spoken and multimodal dialogue systems, covering X‑driven architectures, task‑oriented and open‑domain approaches, NLU/DM integration, FAQ, KB/KG‑driven methods, document‑driven dialogue, and outlines remaining challenges and future research directions.

Dialogue SystemsKnowledge Graphartificial intelligence

0 likes · 21 min read

Advances and Reflections on Human‑Machine Dialogue Technologies

Alibaba Cloud Developer

Nov 7, 2019 · Artificial Intelligence

Boosting Task-Oriented Dialogue with Heterogeneous Memory Networks

This paper introduces Heterogeneous Memory Networks (HMNs), combining context‑free and context‑aware memory modules to jointly process user queries, dialogue history, and knowledge bases, achieving state‑of‑the‑art performance on three task‑oriented dialogue datasets in both BLEU and F1 metrics.

Dialogue Systemsknowledge integrationmemory networks

0 likes · 17 min read

Boosting Task-Oriented Dialogue with Heterogeneous Memory Networks

DataFunTalk

Oct 25, 2019 · Artificial Intelligence

Advances and Challenges in Human‑Machine Dialogue: Open‑Domain and Task‑Oriented Systems

This article reviews recent progress and open research problems in human‑machine dialogue, covering both open‑domain chat and task‑oriented systems, with focus on reply quality, decoding, retrieval‑augmented generation, controllable and personalized responses, multi‑turn modeling, reinforcement‑learning strategies, low‑resource NLU, and data augmentation techniques.

Dialogue SystemsResponse Generationnatural language processing

0 likes · 16 min read

Advances and Challenges in Human‑Machine Dialogue: Open‑Domain and Task‑Oriented Systems

Alibaba Cloud Developer

Nov 20, 2018 · Artificial Intelligence

How Reinforcement Learning Powers Interactive Search in E‑Commerce

This article explains how reinforcement learning can be modeled and deployed to enable intelligent, interactive product search on e‑commerce platforms, detailing problem definition, system architecture, training methodology, online results, and future research directions.

Deep Learningdialogue systeme‑commerce

0 likes · 17 min read