arxiv preprint - High-Dimension Human Value Representation in Large Language Models

In this episode, we discuss High-Dimension Human Value Representation in Large Language Models by Samuel Cahyawijaya, Delong Chen, Yejin Bang, Leila Khalatbari, Bryan Wilie, Ziwei Ji, Etsuko Ishii, Pascale Fung. The paper addresses the importance of aligning large language models (LLMs) with human values, introducing a new method called UniVaR for representing human value distributions within these models. UniVaR, which is independent of model architecture and training data, has been applied to eight multilingual LLMs and tested on four distinct LLMs to compare the embedded value distributions. The findings show that UniVaR can illuminate the variation in human values across different languages and cultures within various LLMs.