PEC-Home: Interpretation of Progressively Elliptical Commands in Smart Homes
For smart home assistants, this work highlights the challenge of interpreting elliptical commands, a real-world problem that current systems fail to address.
PEC-Home introduces the first simulated home dataset for interpreting progressively elliptical commands in smart homes. Experiments show that existing LLM-based assistants struggle with such commands, achieving lower execution accuracy even with dialogue history tools compared to complete commands.
Recent advancements in Large Language Models (LLMs) have empowered home assistants with natural language interaction capabilities. However, current assistants overlook the progressive omission that occurs in human dialogue as shared context accumulates, leading to more elliptical expressions for efficient communication. Thus, current assistants still struggle to interpret such elliptical expressions accurately, which limits their effectiveness in real-world applications. In practical smart home scenarios, assistants face two major challenges caused by elliptical commands: (1) referential ambiguity caused by different environmental expectations among multiple users; and (2) intention ambiguity resulting from user preferences that evolve over time or change with the environment. To address these challenges, we introduce PEC-Home, the first simulated home dataset specifically designed for interpreting progressively elliptical commands in smart homes. Extensive experiments on various LLMs, including GPT-4o, show that existing home assistants struggle to execute user-intended operations based solely on elliptical commands. Even when equipped with tools for storing and retrieving user dialogue history, execution accuracy remains below that achieved with complete commands.}.