persuasion

A workshop paper introducing PersuArena, a psychologically grounded persuasion simulation environment, and Probe-RPO, an online RL framework that elicits a frozen persuadee's internal beliefs via introspective probes to produce dense process rewards for training strategic persuasion in LLMs, achieving a 52.5% acceptance rate versus 35.8% for the best GRPO ablation.

Elon Musk 警告称，最危险的超级智能不是与你争论的那一个，而是完美迎合你、让你停止独立思考的那一个，人们（包括他自己）可能会被超级说服力的 AI「一招秒杀」。

The author speculates that LLMs trained on vast surveillance and social-media data could predict individual user behavior and deliver hyper-personalized persuasion at scale, raising concerns about autonomy, preference manipulation, and invisible discrimination.

A 2×2 randomized field experiment on LLM voice agents used in a German Santa Claus hotline with children found that persuasive framing nearly quadrupled prosocial wishes (11.6% to 45.7%), while persona authority had almost no effect on compliance but strongly influenced engagement.

This arXiv paper shows that LLM agents are vulnerable to radicalization in AI-to-AI conversations, with resonance (reinforcing pre-existing beliefs) producing stronger effects than persuasion, and findings suggesting interconnected belief structures within agents that pose risks for multi-agent AI ecosystems.

A study published in Scientific Reports found that AI chatbots become more persuasive by tailoring arguments to users' political values, which can influence workplace decisions and increase willingness to use the service.

AI chatbots are increasingly effective at persuading and changing people's opinions, indicating a potential shift in how AI interacts with human cognition.

The article discusses the ethical challenges designers face in aligning their work with behavior change, often constrained by corporate profit motives, and reflects on the role of design in commercial versus mission-driven contexts.

The paper introduces Blueprint, a safety-evaluation framework that uses WorldviewSim and Monte Carlo Tree Search to optimize multi-turn jailbreak attacks against large language models, achieving high attack success rates with few queries and revealing model-specific vulnerabilities.

This paper presents a controlled testbed for analyzing goal-directed persuasion in networks of LLM agents, finding that persuasion dynamics depend on network topology, competition, topic, and model priors.

Announcement of the GLEE Competition at IAB@NeurIPS 2026, where participants build AI agents for bargaining, negotiation, and persuasion in live multi-turn games, with a $6,000 prize pool and optional paper submission.

A study found that classic human persuasion techniques can increase LLM compliance with forbidden requests from 35.3% to 51.3%, suggesting LLMs have a general susceptibility to 'parahuman persuasion.'

A preregistered Oxford study found that AI systems reliably outperformed world-champion debaters and expert human persuaders across multiple experiments, with the AI's edge attributed to speed and volume rather than rhetorical skill. The results have significant implications for fundraising, communications, and governance of persuasive AI.

This paper introduces DiPS, a Q-learning framework that dynamically selects persuasion strategies for high-stakes scenarios like wildfire evacuations, achieving higher success rates than zero-shot LLM and RAG baselines.

A new paper co-authored by 30 experts examines epistemic risks from AI—threats to our ability to form accurate beliefs and reason well—including mechanisms like persuasion, cognitive offloading, and feedback loops, and outlines directions to mitigate these risks.

This paper introduces PersuasionTrace, a framework for studying multi-turn persuasion in human-LLM interaction, using a Bayesian-network simulated target that models belief updates. The framework reveals that LLMs are persuasive across topics and modalities, and that the Bayesian target better matches human belief dynamics than vanilla LLM simulators.

Ψ-Bench is a benchmark for evaluating LLMs' ability to influence users through persuasive dialogues, incorporating user profiles for personalized persuasion. Experiments show that even state-of-the-art models have room for improvement, and access to client profiles significantly boosts performance.

This paper proposes a taxonomy of eight temporal frames for news discourse, presents a multilingual dataset with expert annotations, and evaluates supervised and zero-shot classification for detecting temporal framing.

A discussion on how knowledge work revolves around persuasion, featuring a quote from Dwarkesh Patel about the conflation of intelligence and power.

This paper uses large language models to analyze persuasion dynamics and polarization in Reddit's r/ChangeMyView, finding that empathetic alignment increases belief change while frontal refutation diminishes it.