2 papers
cs.CL2024
Safe-Embed: Unveiling the Safety-Critical Knowledge of Sentence Encoders
Jinseok Kim, Jaewon Jung, Sangyeop Kim +2
Despite the impressive capabilities of Large Language Models (LLMs) in various tasks, their vulnerability to unsafe prompts remains a critical issue. These prompts can lead LLMs to…
cs.CL2024
Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
Zhiwen You, HaeJin Lee, Shubhanshu Mishra +4
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can…