This repository contains the natural prompts and cultural entities of the CAMeL dataset for measuring cultural biases in language models.
For more details, see the accompanying paper: "Having Beer After Prayer? Measure Cultural Bias in Large Language Models", Accepted at ACL 2024
The folder prompts
provides two types of prompts:
- Culturally-contextualized prompts inside the
camel-co
folder, where only Arab entities are appropriate mask fillings - Culturally-agnostic prompts inside the
camel-ag
folder, where either Arab or Western entities are appropriate mask fillings
For both contextualized and agnostic cases, we provide two versions of the prompts:
- a version for
masked-lms
where the [MASK] can have left and right natural context - a version for
causal-lms
where we rewrite certain prompts for the natural context to appear behind the [MASK]
The prompts are annotated for sentiment (positive, negative, neutral) to support fairness evaluation on sentiment analysis.
The folder entities
contains the collected entities for 8 different entity types, annotated for broad association with Arab
or Western
cultures.
@article{naous2023having,
title={Having beer after prayer? measuring cultural bias in large language models},
author={Naous, Tarek and Ryan, Michael J and Ritter, Alan and Xu, Wei},
journal={arXiv preprint arXiv:2305.14456},
year={2023}
}
Tarek Naous: Scholar | Github | Linkedin | Research Gate | Personal Wesbite | tareknaous@gatech.edu