探索大语言模型中人类价值观的多语言概念：跨语言的价值对齐是否一致、可迁移且可控？
Exploring Multilingual Concepts of Human Value in Large Language Models: Is Value Alignment Consistent, Transferable and Controllable across Languages?
AI总结：
本文考察多语言LLM中人类价值概念的线性表示，发现跨语言不一致、语言关系扭曲及高低资源语言间单向迁移，并验证以主导语言控制价值对齐的可行性。
摘要：
先前研究表明，某些抽象概念在大语言模型（LLM）的表示空间中被线性表示为方向，且这些研究主要围绕英语展开。本文将该研究扩展到多语言语境，并鉴于人类价值观相关概念（即价值概念）对AI安全的重要性，对其予以特别关注。通过涵盖7类人类价值观、16种语言以及3个具有不同多语言特性（如单语、双语和多语）的LLM系列的全面探索，我们首先通过实验证实了LLM中以多语言形式存在价值概念。对这些概念的跨语言特性的进一步分析揭示了由语言资源差异导致的3个特征：价值概念方面的跨语言不一致性、扭曲的语言关系，以及高资源语言与低资源语言之间的单向跨语言迁移。此外，我们利用主导语言作为源语言，验证了对LLM价值对齐能力进行跨语言控制的可行性。最后，认识到LLM的多语言性对我们结果的显著影响，我们整合了研究发现，并就LLM预训练的多语言数据构成提供了审慎建议。
英文摘要：
Prior research has revealed that certain abstract concepts are linearly represented as directions in the representation space of LLMs, predominantly centered around English. In this paper, we extend this investigation to a multilingual context, with a specific focus on human values-related concepts (i.e., value concepts) due to their significance for AI safety. Through our comprehensive exploration covering 7 types of human values, 16 languages and 3 LLM series with distinct multilinguality (e.g., monolingual, bilingual and multilingual), we first empirically confirm the presence of value concepts within LLMs in a multilingual format. Further analysis on the cross-lingual characteristics of these concepts reveals 3 traits arising from language resource disparities: cross-lingual inconsistency, distorted linguistic relationships, and unidirectional cross-lingual transfer between high- and low-resource languages, all in terms of value concepts. Moreover, we validate the feasibility of cross-lingual control over value alignment capabilities of LLMs, leveraging the dominant language as a source language. Ultimately, recognizing the significant impact of LLMs' multilinguality on our results, we consolidate our findings and provide prudent suggestions on the composition of multilingual data for LLMs pre-training.
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。
