HierTOD: A Task-Oriented Dialogue System Driven by Hierarchical Goals
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Abstract (arXiv)
Task-Oriented Dialogue (TOD) systems assist users in completing tasks through natural language interactions, often relying on a single-layered workflow structure for slot-filling in public tasks, such as hotel bookings. However, in enterprise environments, which involve rich domain-specific knowledge, TOD systems face challenges due to task complexity and the lack of standardized documentation. In this work, we introduce HierTOD, an enterprise TOD system driven by hierarchical goals that can support composite workflows. By focusing on goal-driven interactions, our system serves a more proactive role, facilitating mixed-initiative dialogue and improving task completion. Equipped with components for natural language understanding, composite goal retriever, dialogue management, and response generation, backed by a well-organized data service with domain knowledge base and retrieval engine, HierTOD delivers efficient task assistance as judged by human evaluators. Furthermore, our system implementation unifies two TOD paradigms: slot-filling for information collection and step-by-step guidance for task execution. Our user study demonstrates the effectiveness and helpfulness of HierTOD in performing both paradigms.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 11 Nov 2024.
Builds on
9 of 20 references.
References · 9
- 2021Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue Systemcited by 139
- 2020Task-Oriented Dialogue as Dataflow Synthesiscited by 122
- 2020UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2cited by 111
- 2023Are LLMs All You Need for Task-Oriented Dialogue?cited by 52
- 2019Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attentioncited by 43
- 2022Alexa, Let's Work Together: Introducing the First Alexa Prize TaskBot Challenge on Conversational Task Assistancecited by 15
- 2022AnyTOD: A Programmable Task-Oriented Dialog Systemcited by 10
- 2024Evaluation and Continual Improvement for an Enterprise AI Assistantcited by 7
- 2023Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue Systemcited by 5
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Citing papers per year: 2025: 4; 2026: 2.
6 papers.
- 2025SEADialogues: A Multilingual Culturally Grounded Multi-turn Dialogue Dataset on Southeast Asian Languagescited by 3
- 2026Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimizationcited by 2
- 2025Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialoguescited by 1
- 2025Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarioscited by 1
- 2025Multi-Intent Spoken Language Understanding: Methods, Trends, and Challengescited by 0
- 2026ATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systemscited by 0
- 2026Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization11 Feb 2026
- 2026ATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systems17 Jan 2026
- 2025Multi-Intent Spoken Language Understanding: Methods, Trends, and Challenges12 Dec 2025
- 2025Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarios30 Nov 2025
- 2025Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialogues22 Sep 2025
- 2025SEADialogues: A Multilingual Culturally Grounded Multi-turn Dialogue Dataset on Southeast Asian Languages9 Aug 2025