Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents

2026-05-21 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Expert, quick

Summary

The "Think Thrice Before You Speak" (TTBYS) framework addresses challenges in persuasive dialogue by enhancing Large Language Models' (LLMs) Theory of Mind (ToM) reasoning. Existing LLMs struggle with intrinsic dependencies among mental states due to simple prompting and insufficient ToM knowledge. TTBYS, grounded in the Belief-Desire-Intention (BDI) framework, explicitly models sequential mental state dependencies in multi-turn dialogues. Researchers also created ToM-based Broad Persuasive Dialogues (ToM-BPD), a large-scale annotated dataset capturing fine-grained mental states and persuasive strategies. Experiments show Qwen3-8B equipped with TTBYS outperforms GPT-5 by 1.20% in desire prediction, 22.80% in belief prediction, and 16.97% in persuasive strategy prediction, demonstrating enhanced interpretability and consistency.

Key takeaway

For Machine Learning Engineers developing persuasive agents, if you are struggling with LLM consistency in social reasoning, consider adopting the TTBYS framework. Implementing its knowledge-enhanced stepwise reasoning, grounded in the BDI framework, can significantly improve your model's ability to infer user desires and beliefs, boosting persuasive strategy prediction by over 16% compared to advanced models like GPT-5.

Key insights

Enhancing LLM persuasive dialogue requires explicitly modeling mental state dependencies using dual knowledge for robust Theory of Mind.

Principles

• Persuasive dialogue requires Theory of Mind (ToM) reasoning.
• Explicitly modeling mental state dependencies improves LLM reasoning.
• Dual knowledge (explicit/implicit) enhances ToM inference.

Method

TTBYS is a knowledge-enhanced stepwise reasoning framework leveraging explicit and implicit prior experiences to infer desires, beliefs, and persuasive strategies in dialogue.

In practice

• Use BDI framework for sequential mental state modeling.
• Annotate fine-grained mental states for dataset creation.
• Integrate dual knowledge for improved ToM inference.

Topics

• Theory of Mind
• Persuasive Dialogue
• Large Language Models
• Belief-Desire-Intention
• Knowledge-Enhanced Reasoning
• Dialogue Systems

Best for: Research Scientist, AI Scientist, Machine Learning Engineer, NLP Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.