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title: "Language is Scary when Over-Analyzed: Unpacking Implied Misogynistic Reasoning with Argumentation Theory-Driven Prompts" | ||
authors: ["Arianna Muti", "Federico Ruggeri", "Khalid Al Khatib", "Alberto Barrón-Cedeño", "Tommaso Caselli"] | ||
date: 2024-01-10 | ||
doi: "" | ||
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# Schedule page publish date (NOT publication's date). | ||
publishDate: 2024-11-11T14:48:20+01:00 | ||
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# 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"] | ||
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# Publication name and optional abbreviated publication name. | ||
publication: "EMNLP 2024" | ||
publication_short: "EMNLP 2024" | ||
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abstract: "We propose misogyny detection as an Argumentative Reasoning task and we investigate the capacity of large language models (LLMs) to understand the implicit reasoning used to convey misogyny in both Italian and English. The central aim is to generate the missing reasoning link between a message and the implied meanings encoding the misogyny. Our study uses argumentation theory as a foundation to form a collection of prompts in both zero-shot and few-shot settings. These prompts integrate different techniques, including chain-of-thought reasoning and augmented knowledge. Our findings show that LLMs fall short on reasoning capabilities about misogynistic comments and that they mostly rely on their implicit knowledge derived from internalized common stereotypes about women to generate implied assumptions, rather than on inductive reasoning." | ||
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# Summary. An optional shortened abstract. | ||
summary: "" | ||
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tags: ["Large Language Models","Argument Mining", "NLP", "Implicit Hate"] | ||
categories: [] | ||
featured: false | ||
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# Custom links (optional). | ||
# Uncomment and edit lines below to show custom links. | ||
# links: | ||
# - name: Follow | ||
# url: https://twitter.com | ||
# icon_pack: fab | ||
# icon: twitter | ||
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url_pdf: https://aclanthology.org/2024.emnlp-main.1174.pdf | ||
url_code: | ||
url_dataset: | ||
url_poster: | ||
url_project: | ||
url_slides: | ||
url_source: | ||
url_video: | ||
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# 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: 'Our pipeline' | ||
focal_point: "Center" | ||
preview_only: false | ||
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# Associated Projects (optional). | ||
# Associate this publication with one or more of your projects. | ||
# Simply enter your project's folder or file name without extension. | ||
# E.g. `internal-project` references `content/project/internal-project/index.md`. | ||
# Otherwise, set `projects: []`. | ||
projects: [] | ||
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# Slides (optional). | ||
# Associate this publication with Markdown slides. | ||
# Simply enter your slide deck's filename without extension. | ||
# E.g. `slides: "example"` references `content/slides/example/index.md`. | ||
# Otherwise, set `slides: ""`. | ||
slides: "" | ||
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