通过激活工程识别和操纵大语言模型中的人格特质
Identifying and Manipulating Personality Traits in LLMs Through Activation Engineering
AI总结：
本研究基于激活工程方法，借鉴相关研究开发出识别和调整LLMs中人格特质相关激活方向的技术，以实现人格动态微调，同时深化对LLMs可解释性的理解并审视伦理意义。
摘要：
近年来，受对更高效率、可解释性和安全使用的需求推动，大语言模型（LLMs）领域发展迅速。本研究基于“激活工程”这一新颖方法，借鉴《LLMs的拒绝行为由单一方向介导》（arXiv:2406.11717）和《通过对比激活添加引导Llama 2》（arXiv:2312.06681）等研究，探索LLMs的人格修改。我们利用激活工程开发出一种识别和调整与人格特质相关的激活方向的方法，这可能实现LLMs人格的动态微调。本工作旨在进一步理解LLMs的可解释性，同时审视此类发展的伦理意义。
英文摘要：
The field of large language models (LLMs) has grown rapidly in recent years, driven by the desire for better efficiency, interpretability, and safe use. Building on the novel approach of "activation engineering," this study explores personality modification in LLMs, drawing inspiration from research like Refusal in LLMs Is Mediated by a Single Direction (arXiv:2406.11717) and Steering Llama 2 via Contrastive Activation Addition (arXiv:2312.06681). We leverage activation engineering to develop a method for identifying and adjusting activation directions related to personality traits, which may allow for dynamic LLM personality fine-tuning. This work aims to further our understanding of LLM interpretability while examining the ethical implications of such developments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
