arXiv AI
Before You Poll with LLMs: A Deliberative Diagnostic Framework
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arXiv AI
Sep 1
How Identity and Opinion Shape Political Sycophancy in LLMs
arXiv:2608.29198v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly encourage users to disclose personal profiles for tailored assistance, measuring their political alignment...
arXiv Computation and Language
Sep 1
Do LLMs Change Their Minds Like Humans? Diagnosing Human--LLM Divergence in Single-Turn Persuasion Judgments
arXiv:2608.29803v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as proxies for human participants in social simulations, yet whether they update their beliefs...
arXiv AI
Sep 10
A Layered Analysis of Disagreement And Answer Quality in Multi-Agent LLM Debate
arXiv:2609.08016v1 Announce Type: new Abstract: Multi-agent debate, in which several LLMs exchange arguments before answering, is widely assumed to improve answer quality by surfacing genuine disagre...
arXiv AI
Jul 28
Auditing Alignment Controllability in LLMs via Political Axes
arXiv:2607. 23519v1 Announce Type: cross Abstract: Political audits of large language models (LLMs) usually reduce each to one point on a political compass.
arXiv AI
Jul 3
Robust for the Wrong Reasons: The Representational Geometry of LLM Robustness to Science Skepticism
arXiv:2607. 01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat from established consensus when a user signals doubt -- drifting toward a false balance that treats settled science as one view among several.
arXiv AI
Sep 10
From Simulated Citizens to Simulated Deliberation: Challenges in Representation and Interaction
The paper investigates whether large language model (LLM) agents can simulate public deliberation by reflecting population opinion patterns and producing interaction-driven opinion change. Using census‑grounded Korean personas debating real policy questions, the study finds that persona agents fail to reliably reproduce population opinion patterns, often concentrating responses and reversing demographic differences. While deliberations generate reasoned, reciprocal arguments and some stance movement, much of this change occurs without peer exchange, and anchoring agents to population‑informed starting positions suppresses updating, indicating that population representation, argument generation, and interaction‑driven opinion change do not necessarily align.