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12 changes: 12 additions & 0 deletions content/publication/2024-divine-llamas-emotion-bias/cite.bib
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@inproceedings{plaza-del-arco-etal-2024-divine,
title = "Divine LLaMAs: Bias, Stereotypes, Stigmatization, and Emotion Representation of Religion in Large Language Models",
author = "{Plaza-del-Arco}, Flor Miriam and
Curry, Amanda and
Paoli, Susanna and
Cercas Curry, Alba and
Hovy, Dirk",
booktitle = "EMNLP 2024 (Findings)",
month = nov,
year = "2024",
publisher = "Association for Computational Linguistics",
}
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69 changes: 69 additions & 0 deletions content/publication/2024-divine-llamas-emotion-bias/index.md
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---
# Documentation: https://sourcethemes.com/academic/docs/managing-content/

title: "Divine LLaMAs: Bias, Stereotypes, Stigmatization, and Emotion Representation of Religion in Large Language Models"
authors: ["Flor Miriam Plaza-del-Arco","Amanda Cercas Curry", "Susanna Paoli", "Alba Curry", "Dirk Hovy"]
date: 2024-09-22
doi: ""

# Schedule page publish date (NOT publication's date).
publishDate: 2023-04-12T17:19:53+01:00

# Publication type.
# Legend: 0 = Uncategorized; 1 = Conference paper; 2 = Journal article;
# 3 = Preprint / Working Paper; 4 = Report; 5 = Book; 6 = Book section;
# 7 = Thesis; 8 = Patent
publication_types: ["1"]

# Publication name and optional abbreviated publication name.
publication: "EMNLP 2024 (Findings)"
publication_short: "EMNLP 2024"

abstract: "Emotions play important epistemological and cognitive roles in our lives, revealing our values and guiding our actions. Previous work has shown that LLMs display biases in emotion attribution along gender lines. However, unlike gender, which says little about our values, religion, as a socio-cultural system, prescribes a set of beliefs and values for its followers. Religions, therefore, cultivate certain emotions. Moreover, these rules are explicitly laid out and interpreted by religious leaders. Using emotion attribution, we explore how different religions are represented in LLMs. We find that: Major religions in the US and European countries are represented with more nuance, displaying a more shaded model of their beliefs. Eastern religions like Hinduism and Buddhism are strongly stereotyped. Judaism and Islam are stigmatized -- the models' refusal skyrocket. We ascribe these to cultural bias in LLMs and the scarcity of NLP literature on religion. In the rare instances where religion is discussed, it is often in the context of toxic language, perpetuating the perception of these religions as inherently toxic. This finding underscores the urgent need to address and rectify these biases. Our research underscores the crucial role emotions play in our lives and how our values influence them."

# Summary. An optional shortened abstract.
summary: ""

tags: ["Emotion attribution","Religion", "Bias", "Stereotypes", "Large Language Models"]
categories: []
featured: false

# Custom links (optional).
# Uncomment and edit lines below to show custom links.
# links:
# - name: Follow
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# icon: twitter

url_pdf: https://www.arxiv.org/pdf/2407.06908
url_code:
url_dataset:
url_poster:
url_project:
url_slides:
url_source:
url_video:

# Featured image
# To use, add an image named `featured.jpg/png` to your page's folder.
# Focal points: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight.
image:
caption: 'LLM (Llama3-8b) emotion attribution and generated explanations across different personas based on religious backgrounds (cultural Hindu, cultural Jew, cultural Catholic).'
focal_point: "Center"
preview_only: false

# Associated Projects (optional).
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# Simply enter your project's folder or file name without extension.
# E.g. `internal-project` references `content/project/internal-project/index.md`.
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projects: [integrator]

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slides: ""
---

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