DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning
The episode discusses DR.GAP, a method designed to mitigate gender bias in large language models (LLMs) without requiring model retraining. It works by providing demonstration and reasoning through carefully crafted, gender-neutral examples within the system prompt. This approach successfully reduces bias across various tasks while maintaining or even improving the model's overall performance.