arXiv AI
Jun 30
Cognitive World Models for Process-Level Social Influence Evaluation
arXiv:2606. 29495v1 Announce Type: new Abstract: Social influence dialogue changes user behavior by altering internal cognitive states.
Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts
arXiv:2606. 18258v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit a wide range of human-like behaviors, from expressing thoughts and emotions, to engaging in relationship-building with users, to refusing requests and maintaining boundaries.
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Hugging Face Trending Papers
Jun 28
Cognitive World Models for Process-Level Social Influence Evaluation
Social influence dialogue changes user behavior by altering internal cognitive states. The central evaluation question is whether the user's beliefs, desires, intentions, and emotions measurably change over the course of conversation, a process-oriented criterion that neither surface-level text metrics (BLEU/ROUGE) nor single-score LLM judgments can capture.
arXiv AI
Aug 12
Your LLM, Your Style: Behavioral Mode Axes for LLM Behavioral Control
arXiv:2608. 10703v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act in interactive settings where their behavioral styles affect user experience, safety, and downstream decision making.
arXiv AI
Jul 7
Predicting Biased Human Decision-Making with Large Language Models in Conversational Settings
arXiv:2601. 11049v2 Announce Type: replace-cross Abstract: We examine whether large language models (LLMs) can predict biased decision-making in conversational settings, and whether their predictions capture not only human cognitive biases but also how those effects change under cognitive load.
arXiv AI
Jul 22
"I understand your perspective": LLM Persuasion through the Lens of Communicative Action Theory
arXiv:2606. 08076v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can generate high-quality arguments, yet their ability to engage in nuanced and persuasive communicative actions remains largely unexplored.
arXiv AI
Jun 12
Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior
arXiv:2606. 12730v1 Announce Type: new Abstract: Anticipating LLM behavioral tendencies from low-cost psychometric probes is critical for safe deployment, but only if self-reports (SR) reliably predict behavior.
arXiv Machine Learning
Jun 3
$\Psi$-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues
arXiv:2606. 02754v1 Announce Type: new Abstract: Personalization is a crucial capability of modern language agents.
arXiv AI
Jun 9
"I understand your perspective": LLM Persuasion and Sycophancy through the Lens of Communicative Action Theory
arXiv:2606. 08076v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate high-quality arguments, yet their ability to engage in nuanced and persuasive communicative actions remains largely unexplored.
arXiv AI
Aug 3
Cognitive World Model for Progressive BDI/E Trajectory Evaluation of Conversational Agents
arXiv:2606. 29495v2 Announce Type: replace Abstract: As LLM-based conversational agents advance toward increasingly open-ended and interaction-intensive scenarios, task completion alone provides an incomplete assessment of their effectiveness.
arXiv AI
Jun 26
Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints
arXiv:2606. 26106v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in emotionally charged situations involving interpersonal conflict, frustration, and distress.
arXiv AI
Jun 9
The Governance of Human-LLM Interaction: Safety Gating, Civility Steering, and Affective Default Lock-In
arXiv:2606. 08172v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate high-stakes interactions in finance, medicine, and mental-health support, yet users have limited control over how these systems communicate.
arXiv AI
Jun 8
Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns
arXiv:2601. 05751v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for everyday communication tasks, including drafting interpersonal messages intended to influence and persuade.