mlsanityData to 14 Oct 2026

Must Read: A Comprehensive Survey of Computational Persuasion

arXiv 2505.07775 ↗First posted 12 May 2025cs.CL cs.AI cs.CYcited by 13

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Abstract (arXiv)

Persuasion is a fundamental aspect of communication, influencing decision-making across diverse contexts, from everyday conversations to high-stakes scenarios such as politics, marketing, and law. The rise of conversational AI systems has significantly expanded the scope of persuasion, introducing both opportunities and risks. AI-driven persuasion can be leveraged for beneficial applications, but also poses threats through unethical influence. Moreover, AI systems are not only persuaders, but also susceptible to persuasion, making them vulnerable to adversarial attacks and bias reinforcement. Despite rapid advancements in AI-generated persuasive content, our understanding of what makes persuasion effective remains limited due to its inherently subjective and context-dependent nature. In this survey, we provide a comprehensive overview of persuasion, structured around three key perspectives: (1) AI as a Persuader, which explores AI-generated persuasive content and its applications; (2) AI as a Persuadee, which examines AI's susceptibility to influence and manipulation; and (3) AI as a Persuasion Judge, which analyzes AI's role in evaluating persuasive strategies, detecting manipulation, and ensuring ethical persuasion. We introduce a taxonomy for persuasion research and discuss key challenges for future research to enhance the safety, fairness, and effectiveness of AI-powered persuasion while addressing the risks posed by increasingly capable language models.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 83 of its 169 references that are in the map. First posted on arXiv 12 May 2025.

Builds on

83 of 169 references.

References · 83

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38 more
  1. 2021Towards Emotional Support Dialog Systemscited by 299
  2. 2017Deal or No Deal? End-to-End Learning for Negotiation Dialoguescited by 209
  3. 2019Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Goodcited by 209
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 9.

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  1. 2025Synthetic Socratic Debates: Examining Persona Effects on Moral Decision and Persuasion Dynamicscited by 19
  2. 2025Towards Strategic Persuasion with Language Modelscited by 10
  3. 2025Evaluating Large Language Models as Expert Annotatorscited by 9
  4. 2025Mitigating Manipulation and Enhancing Persuasion: A Reflective Multi-Agent Approach for Legal Argument Generationcited by 8
  5. 2026Analyzing Defensive Misdirection Against Model-Guided Automated Attacks on Agentic AI Systemscited by 2
  6. 2026ElecTwit: A Framework for Studying Persuasion in Multi-Agent Social Systemscited by 1
  7. 2026Large Language Models Persuade Without Planning Theory of Mindcited by 1
  8. 2026LLM Wardens: Mitigating Adversarial Persuasion with Third-Party Conversational Oversightcited by 0
  9. 2026Persuasion Index: A Theory-Guided Framework for Persuasion Analysiscited by 0
  10. 2026PersuaRL: Reinforcement Learning-Driven Multi-Expert Selection for Persuasive Dialogue Generation in Insurancecited by 0
  11. 2026VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformationcited by 0
  12. 2026AI Agents are Vulnerable to Radicalizationcited by 0
1 more
  1. 2026Understanding and Reducing Misalignment in Persuasion Optimizationcited by 0