arXiv cs.CL论文
MAVEN：多模态内容宏观社会价值评估框架
本文提出MAVEN，一个基于国际人权文书和文化价值理论的多模态内容宏观社会价值评估框架，将价值分为6个主维度和72个二级指标，支持多级量化评分。作者构建了人工验证的基准MacroValue-Bench和软匹配指标，并提出跨度自适应多级偏好优化（SA-MDPO）和免训练多角色共识策略来优化评估器。实验表明，2B的紧凑评估器性能与同系列8B相当，接近前沿闭源VLM，为可扩展的宏观社会价值评估提供了实用路径。
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Abstract:Assessing whether multimodal content aligns with macro-societal values, such as peace, justice, and freedom, has become an increasingly urgent challenge. Existing frameworks are largely confined to safety-oriented taxonomies, text-only psychometric probes, or single-label classification. Therefore, we propose MAVEN, a hierarchical framework for macro-societal value evaluation of multimodal content, grounded in international human-rights instruments and cultural value theory. MAVEN organizes values into 6 primary dimensions and 72 secondary indicators, supporting multi-level quantitative scoring. Building on MAVEN, we construct a human-verified multimodal benchmark and a soft-match metric to evaluate VLMs' assessments across value dimensions. For evaluator optimization, we propose a span-adaptive variant of multi-level preference optimization for evaluator distillation, together with a training-free multi-role consensus strategy at inference time. We evaluate existing open- and closed-source VLMs on our benchmark, revealing shared tendencies and clear differences in macro-societal value judgments. Experiments show that our compact 2B evaluator matches its 8B counterpart in the same family and approaches frontier closed-source VLMs, offering a practical path toward scalable macro-societal value evaluation. Our SA-MDPO implementation and MacroValue-Bench are available at this https URL.