2024/11/11 by Lingbo Mo, Shun Jiang, Mo, Lingbo +6 · 3 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Multi-Agent Systems and Negotiation #Speech and dialogue systems #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2411.07152
openalex publication_date 2024/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.