This article discusses a novel method for aligning large language models (LLMs) with human values, using a social scene simulator called MATRIX. MATRIX emulates realistic social scenes based on user input, allowing the LLM to consider social consequences before responding. This self-alignment process is shown to enhance the alignment of LLMs with human values without compromising inference speed. The method is theoretically and empirically validated, with results showing that it outperforms other methods across various benchmarks.
Publication date: 8 Feb 2024
Project Page: https://github.com/pangxianghe/MATRIX
Paper: https://arxiv.org/pdf/2402.05699
