大模型
arxiv.org ·
LLM-Ideoplasticity：将 LLM 政治行为中的意识形态可塑性测量为上下文条件分布
该论文主张 LLM 的政治意识形态并非固定点，而是真实政治空间上的条件分布 P(立场|上下文)。作者用 VAA-CHES 投影模型构建统一测量框架，在 lrgen、lrecon、galtan 三个已验证维度、六个上下文轴上评估九个当前 LLM。结果显示模型对上下文高度敏感：说服性框架与低资源语言分别使坐标最多偏移 0.57 和 0.52 单位，而思维链推理往往放大而非抑制改写带来的不稳定性。尽管存在局部可塑性，模型群体整体占据的 Overton 范围很窄，约为主要欧洲政党分布跨度的三分之一。多特质多方法（MTMM）分析支持其结论：单一坐标无法概括 LLM 政治行为，需以分布形态刻画。代码与数据已公开。
AI推荐理由 arXiv 论文（v3，2026-09-10 修订），有明确方法（VAA-CHES 投影、六个上下文轴、MTMM 分析）与可复现声明（代码与数据公开），事实密度较高。新信息在于把 LLM 政治立场建模为上下文条件分布而非固定点，并给出说服性框架与低资源语言可位移坐标最多 0.57/0.52 单位、CoT 常放大改写不稳定性的量化结果。局限：属 cs.CY 社会计算方向，对模型能力、Agent 或工程落地的直接价值有限，且摘要未给出具体模型名单与统计细节，需读全文验证。
72
正文
Computer Science > Computers and Society
arXiv:2606.28335 (cs)
[Submitted on 26 May 2026 (v1), last revised 10 Sep 2026 (this version, v3)]
Title:LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution
Authors:Adib Sakhawat, Syed Rifat Raiyan, Tahsin Islam, Takia Farhin, Hasan Mahmud, Md Kamrul Hasan
View a PDF of the paper titled LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution, by Adib Sakhawat and 5 other authors
View PDF
HTML (experimental)
Abstract:We argue, with systematic empirical evidence, that a large language model's political ideology is not a fixed point, but a conditional distribution $\mathbb{P}($position$\mid$context$)$ over a real political space. We evaluate nine current LLMs using a unified measurement framework anchored by VAA-CHES projection models, which map responses onto three validated dimensions (lrgen, lrecon, galtan) across six contextual axes. Our findings reveal high sensitivity to context: persuasive framing and under-represented languages displace coordinates by up to 0.57 and 0.52 units, respectively, while chain-of-thought reasoning often amplifies rather than dampens paraphrase instability. Despite this local plasticity, the model cohort occupies a remarkably narrow Overton envelope overall, occupying roughly one-third the spread of major European parties. Supported by a multi-trait multi-method (MTMM) analysis, we conclude that a single point cannot summarize LLM political behavior; it must be characterized as a shape. Our code and data are publicly available at this https URL.
Comments:
Subjects:
Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
Cite as:
arXiv:2606.28335 [cs.CY]
(or
arXiv:2606.28335v3 [cs.CY] for this version)
https://doi.org/10.48550/arXiv.2606.28335
Focus to learn more
arXiv-issued DOI via DataCite
Submission history
From: Syed Rifat Raiyan [view email]
[v1]
Tue, 26 May 2026 17:01:07 UTC (10,411 KB)
[v2]
Sun, 26 Jul 2026 16:23:04 UTC (10,414 KB)
[v3]
Thu, 10 Sep 2026 11:17:47 UTC (10,426 KB)
Full-text links:
Access Paper:
View a PDF of the paper titled LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution, by Adib Sakhawat and 5 other authors
View PDF
HTML (experimental)
TeX Source
view license
Current browse context:
cs.CY
new
|
recent
| 2026-06
Change to browse by:
cs
cs.AI
cs.CL
References & Citations
NASA ADS
Google Scholar
Semantic Scholar
export BibTeX citation
Loading...
BibTeX formatted citation
×
loading...
Data provided by:
Bookmark
Bibliographic Tools
Bibliographic and Citation Tools
Bibliographic Explorer Toggle
Bibliographic Explorer (What is the Explorer?)
Connected Papers Toggle
Connected Papers (What is Connected Papers?)
Litmaps Toggle
Litmaps (What is Litmaps?)
scite.ai Toggle
scite Smart Citations (What are Smart Citations?)
Code, Data, Media
Code, Data and Media Associated with this Article
alphaXiv Toggle
alphaXiv (What is alphaXiv?)
Links to Code Toggle
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub Toggle
DagsHub (What is DagsHub?)
GotitPub Toggle
Gotit.pub (What is GotitPub?)
Huggingface Toggle
Hugging Face (What is Huggingface?)
ScienceCast Toggle
ScienceCast (What is ScienceCast?)
Demos
Demos
Replicate Toggle
Replicate (What is Replicate?)
Spaces Toggle
Hugging Face Spaces (What is Spaces?)
Spaces Toggle
TXYZ.AI (What is TXYZ.AI?)
Related Papers
Recommenders and Search Tools
Link to Influence Flower
Influence Flower (What are Influence Flowers?)
Core recommender toggle
CORE Recommender (What is CORE?)
Author
Venue
Institution
Topic
About arXivLabs
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Which authors of this paper are endorsers? |
Disable MathJax (What is MathJax?)