2025
EMNLP
EMNLP 2025
Analyzing values about gendered language reform in LLMs’ revisions
Abstract
AbstractWithin the common LLM use case of text revision, we study LLMs’ revision of gendered role nouns (e.g., outdoorsperson/woman/man) and their justifications of such revisions. We evaluate their alignment with feminist and trans-inclusive language reforms for English. Drawing on insight from sociolinguistics, we further assess if LLMs are sensitive to the same contextual effects in the application of such reforms as people are, finding broad evidence of such effects. We discuss implications for value alignment.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
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Keyword Pioneer
— gendered language reform
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Human-AI Interaction
Artificial Intelligence > Core AI > Responsible AI
Machine Learning > Application Areas > Fairness
Machine Learning > Learning Types > Representation Learning
Artificial Intelligence > Core AI > Large Language Models
Artificial Intelligence > Core AI > Fairness