mlsanityData to 14 Oct 2026

The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trends

arXiv 2402.04631 ↗First posted 7 Feb 2024cs.CLcited by 4

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Persuasion, as one of the crucial abilities in human communication, has garnered extensive attention from researchers within the field of intelligent dialogue systems. We humans tend to persuade others to change their viewpoints, attitudes or behaviors through conversations in various scenarios (e.g., persuasion for social good, arguing in online platforms). Developing dialogue agents that can persuade others to accept certain standpoints is essential to achieving truly intelligent and anthropomorphic dialogue system. Benefiting from the substantial progress of Large Language Models (LLMs), dialogue agents have acquired an exceptional capability in context understanding and response generation. However, as a typical and complicated cognitive psychological system, persuasive dialogue agents also require knowledge from the domain of cognitive psychology to attain a level of human-like persuasion. Consequently, the cognitive strategy-enhanced persuasive dialogue agent (defined as CogAgent), which incorporates cognitive strategies to achieve persuasive targets through conversation, has become a predominant research paradigm. To depict the research trends of CogAgent, in this paper, we first present several fundamental cognitive psychology theories and give the formalized definition of three typical cognitive strategies, including the persuasion strategy, the topic path planning strategy, and the argument structure prediction strategy. Then we propose a new system architecture by incorporating the formalized definition to lay the foundation of CogAgent. Representative works are detailed and investigated according to the combined cognitive strategy, followed by the summary of authoritative benchmarks and evaluation metrics. Finally, we summarize our insights on open issues and future directions of CogAgent for upcoming researchers.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 111 of its 225 references that are in the map. First posted on arXiv 7 Feb 2024.

Builds on

111 of 225 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate14 Aug

Other references · 110

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38 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 2.

4 papers.

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Close in wording, no citation either way

  1. 2026MA2P: A Meta-Cognitive Autonomous Intelligent Agents Framework for Complex Persuasion
  2. 2025PersuasiveToM: A Benchmark for Evaluating Machine Theory of Mind in Persuasive Dialogues
  3. 2026Evaluating the Capabilities of LLMs for Persuasive Dialogue
  4. 2025Towards Strategic Persuasion with Language Models
  5. 2025Can (A)I Change Your Mind?
  6. 2026Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents
  7. 2026Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action
  8. 2026Unlocking Proactivity in Task-Oriented Dialogue