Developing Interactive Tourism Planning: A Dialogue Robot System Powered by a Large Language Model
This work addresses the need for efficient trip planning with reduced speaking load for users, though it appears incremental as it builds on existing LLM capabilities for a specific domain.
The researchers tackled the problem of interactive tourism planning by developing a dialogue robot system powered by a large language model, which achieved fourth place in the Dialogue Robot Competition 2023 preliminaries.
In recent years, large language models (LLMs) have rapidly proliferated and have been utilized in various tasks, including research in dialogue systems. We aimed to construct a system that not only leverages the flexible conversational abilities of LLMs but also their advanced planning capabilities to reduce the speaking load on human interlocutors and efficiently plan trips. Furthermore, we propose a method that divides the complex task of a travel agency into multiple subtasks, managing each as a separate phase to effectively accomplish the task. Our proposed system confirmed a certain level of success by achieving fourth place in the Dialogue Robot Competition 2023 preliminaries rounds. We report on the challenges identified through the competition.