AI RESEARCH
DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping
arXiv CS.AI
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ArXi:2605.14420v1 Announce Type: new Current Large Language Models (LLMs) typically rely on coarse-grained national labels for pluralistic value alignment. However, such macro-level supervision often obscures intra-country value heterogeneity, yielding a loose alignment. We argue that resolving this limitation requires shifting from national labels to multi-dimensional graphic constraints, which can identify groups with predictable, high-consensus value preference. To this end, we propose DVMap (High-Consensus graphic-Value Mapping), a framework for fine-grained pluralistic value alignment.