Ideology as a Problem: Lightweight Logit Steering for Annotator-Specific Alignment in Social Media Analysis

Wei Xia, Haowen Tang, Luozheng Li
12/8/2025
cs.CLcs.AIcs.SI

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Abstract

LLMs internally organize political ideology along low-dimensional structures that are partially, but not fully aligned with human ideological space. This misalignment is systematic, model specific, and measurable. We introduce a lightweight linear probe that both quantifies the misalignment and minimally corrects the output layer. This paper introduces a simple and efficient method for aligning models with specific user opinions. Instead of retraining the model, we calculated a bias score from its internal features and directly adjusted the final output probabilities. This solution is practical and low-cost and preserves the original reasoning power of the model.

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Cite this paper

@article{xia2025ideology,
  title  = {Ideology as a Problem: Lightweight Logit Steering for Annotator-Specific Alignment in Social Media Analysis},
  author = {Wei Xia and Haowen Tang and Luozheng Li},
  year   = {2025},
  eprint = {2601.04207},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2601.04207v1}
}

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