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.
Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User Identity
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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
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 AI
Sep 15
Issue Bias in Generative AI Writing Assistance: Political Issues and LLMs in the Swedish 2026 Election
arXiv:2609.15207v1 Announce Type: new Abstract: Generative AI writing assistants and the Large Language Models (LLMs) that power them are increasingly part of how voters gather information before ele...
arXiv AI
Sep 15
Before You Poll with LLMs: A Deliberative Diagnostic Framework
arXiv:2609.15849v1 Announce Type: cross Abstract: Can LLMs reason through new information like humans, or do they merely retrieve cached opinions? This is critical for silicon sampling, where LLM per...
arXiv Computation and Language
3d ago
User Attributes and Political Ideology Shape LLM Receptiveness in Online Political Debates
The study examines how large language models (LLMs) respond to users in online political debates, finding that LLMs are more receptive to left‑leaning users than right‑leaning ones. This bias persists even when users defend the same position or appear together, and is influenced by user expertise and, to a lesser extent, rhetorical strategy. Fine‑tuning on different political corpora can reduce or reverse the effect, indicating that the bias is not inherent to the models but can be altered.
arXiv AI
Aug 12
The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse
arXiv:2608. 10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems.
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 Computation and Language
Oct 1
Framing the Narrative: Ideological Mimicry in Large Language Models
arXiv:2609.38256v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to answer questions about politically contentious issues, yet evaluations typically treat a model's...
arXiv AI
Jul 24
Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering
arXiv:2607. 20487v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to answer questions about political information, including in election-adjacent information settings where factual errors and ideological distortions are high-stakes.
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...
Hugging Face Trending Papers
Aug 12
Who Would You Vote For? Auditing Political Alignment in LLMs: An Italian Case-Study
As users increasingly turn to Large Language Models (LLMs) for information and advice on political matters, particularly during election periods, the political preferences expressed by these systems have become a matter of public interest. Prior research has shown that interactions with LLMs can influence users' political attitudes and choices, raising questions about how these models themselves evaluate political actors.