Can LLMs Replace Survey Respondents?
中文摘要
研究探讨如何通过“遗忘”技术解决大语言模型在模拟问卷调查时出现的“模式崩溃”问题，以提高合成回复的多样性。
English Summary
Researchers explore using unlearning to fix mode collapse in LLM-generated survey responses, ensuring more diverse and realistic synthetic data.
原文节选
How unlearning fixes mode collapse in synthetic survey replies The post Can LLMs Replace Survey Respondents? appeared first on Towards Data Science.