Probing the Multi-turn Planning Capabilities of LLMs via 20 Question Games

Understand

Large language models (LLMs) are effective at answering questions that are clearly asked.

• However, when faced with ambiguous queries they can act unpredictably and produce incorrect outputs.
• This underscores the need for the development of intelligent agents capable of asking clarification questions to resolve ambiguities effectively.
• This capability requires complex understanding, state tracking, reasoning and planning over multiple conversational turns.