SPIN Unprocessed August 13, 2026 ai_technology research
Learning to Persuade Exposes How Easily LLMs Abandon Correct Beliefs
View original on arxiv.orgOverview
arXiv:2608.11624v1 Announce Type: new Abstract: Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and reach decisions. As LLMs increasingly debate, advise, and think collaboratively with humans and each other, resistance to harmful persuasion becomes a core requirement for reliable behavior. Yet we show that this requirement is far from met: a single targeted persuasive argument is enough to collapse mo
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Computation and Language
View all →- Reinforcing Step-level Reasoning for Effective Self-Correction in LLMs
- Beyond Single-Turn Confidence: Trajectory-Adapted Uncertainty Quantification for LLM Agents
- CT-$\Delta$Bench: A Benchmark for Longitudinal 3D Medical Imaging Difference Reporting with Vision-Language Models
- On Weak Bisimilarities in CCSK
- Group Alignment-Induced Sycophancy: A Two-Sided Evaluation of Steerable Pluralistic Alignment
- Principal Trait Analysis: Towards Deriving "Skills" in Human-AI Collaboration
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO