# Quantifying and alleviating political bias in language models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/quantifying-and-alleviating-political-bias-in-language-models/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ruibo Liu,Chenyan Jia,Jason Wei,Guangxuan Xu,Soroush Vosoughi |
| Citations | 72 |
| DOI | 10.1016/j.artint.2021.103654 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4206590911 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Chenyan Jia](https://scholariq.org/researchers/chenyan-jia/)

## Paper primary topic

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

## Paper topics

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Text Readability and Simplification](https://scholariq.org/topics/text-readability-and-simplification/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.