AI RESEARCH
Neuron-Level Interventions for Gendered and Gender-Neutral Generation in Language Models
arXiv CS.CL
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ArXi:2605.30717v1 Announce Type: new Language models (LMs) can produce gendered language and stereotypes even when given neutral prompts. Most prior work on gender bias in LMs primarily examines gender through a binary lens (feminine vs. masculine), with limited attention to gender-neutral forms, such as they/them pronouns or neutrally phrased job titles. How gender-related signals are encoded in the internal representations of LMs remains an open question. In this work, we study gender-specific neurons in LMs across three categories: feminine, masculine, and gender-neutral.