From Doubt to Action

Abstract

Large language models are increasingly used as conversational agents but often follow user instructions uncritically, even when based on false beliefs. We introduce the DIVE protocol, a prompting strategy grounded in the Belief–Desire–Intention (BDI) framework, which guides models to Doubt the premise, Infer the user’s mental state, Verify belief consistency, and Expand the plan. We evaluated ChatGPT-4o, as an LLM target on ten story-based scenarios under four progressively structured prompting conditions. Success rates rose from 30% (baseline) to 40%, 70%, and 90% as BDI scaffolding and relations were added, indicating that the BDI structure can substantially improve belief-sensitive reasoning in LLMs.

Ähnliche Arbeiten