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.
AuAu: A Benchmark for Auditing Authoritarian Alignment in Large Language Models
arXiv:2606. 16127v1 Announce Type: cross Abstract: The worldwide surge of authoritarianism, combined with the increasing central role in users' everyday lives, raises the question of to what extent specific models exhibit or promote authoritarian attitudes and characteristics.
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Hugging Face Trending Papers
Jul 26
Auditing Alignment Controllability in LLMs via Political Axes
Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in deployment: a model must land somewhere, and what counts is how far, and in which directions, its answers can be steered.
arXiv AI
Jun 17
From Democracies to Autocracies: How AI Systems Enable Authoritarianism by Design
arXiv:2606. 17286v1 Announce Type: cross Abstract: AI-enabled authoritarianism is not confined to autocracies.
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 22
Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User Identity
arXiv:2609.23039v1 Announce Type: new Abstract: LLM-based AI systems answer political questions for hundreds of millions of people. Current audits measure what they say to an average user, but their...
arXiv Computation and Language
Sep 1
Political Ideology Shifts in Large Language Models
arXiv:2508.16013v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in politically sensitive contexts, raising concerns about their susceptibility to ideologica...
arXiv Machine Learning
Jul 31
Sympathetic Framing: Evaluating AI Alignment across Sociodemographic Groups
arXiv:2607. 27232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly shaping how we consume information and form our worldview.
arXiv AI
Sep 15
How User-AI Mistreatment Occurs and Matters in Conversational Systems?
arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understandin...
arXiv AI
Aug 19
Beyond BFI: The CSI for Enhanced Reliability and Validity in Evaluating LLM Personality Traits
The paper introduces the Core Sentiment Inventory (CSI), a new personality trait evaluation tool for large language models (LLMs) that addresses reliability and validity issues found in existing methods like the Big Five Inventory (BFI). CSI is designed specifically for LLMs, supports both English and Chinese, and provides detailed psychological portraits of model behavior. Experiments show that CSI captures nuanced behavioral patterns, improves reliability, and correlates strongly (above 0.85) with real-world LLM outputs.
arXiv AI
Sep 10
Beyond Right and Wrong: Evaluating Second-order Social Reasoning in Large Language Models
arXiv:2609.05437v1 Announce Type: new Abstract: Previous AI alignment efforts have focused primarily on first-order social norms -- teaching models what is socially acceptable or unacceptable (e.g.,...
arXiv AI
Aug 3
The persuasive power of large language models does not depend on their perceived national origin
arXiv:2607. 29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as foreign propaganda, with consequences for democratic discourse and information sovereignty.
arXiv AI
Aug 18
Inference-Time Mitigation of Adversarial Political Bias in Large Language Models
arXiv:2608. 14629v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become the mainstay for information retrieval and summarization tasks, ensuring that they are always non-partisan and invulnerable to political bias is a critical step towards safer and more trustworthy Artificial Intelligence (AI).