用统一框架分析语言随时间演变的多维度规律。
ChronoLens: Measuring Language Change Across Time, Languages, and Linguistic Levels
- 融合冻结多语言模型与跨编码器，统一建模语言各层次变化
- 在172亿词上验证，稀疏表示与语言学统计相关性达0.72
- 发现不同语言变化幅度相似但轨迹各异，需同时看方向与距离
历史语言变化影响形态、句法、语义和语用，但现有计算研究常使用不兼容的表征，难以判断各层面是否同步演化。本文提出ChronoLens框架，结合冻结多语言模型、特征对齐跨编码器和后处理语言干预，应用于涵盖1803–2026年五条议会传统的4498万份文档（约172亿词）。结果表明，稀疏表示与语言学统计的相关性显著高于密集嵌入或拼接稀疏自编码器（ρ=0.72 对比 0.29 和 0.28）。研究发现：同一语言内，形态、句法、语义和语用的变化量级相近；但不同语言在变化时间、程度与方向上差异明显。这表明语言历史演变是结构化、多维的过程——相同变化幅度可能对应不同轨迹，跨语言比较必须同时衡量距离与方向。
原文摘要 · Abstract (English)
Historical language change affects morphology, syntax, semantics, and pragmatics, yet computational studies typically examine these levels with incompatible representations and therefore cannot determine whether they evolve together across languages. We address this problem by asking how the magnitude and direction of change vary across linguistic levels, languages, and historical periods within a single analytical space. We introduce ChronoLens, a framework that combines frozen multilingual language models, feature-aligned crosscoders, and post-hoc linguistic interventions, and apply it to 44.98 million documents and approximately 17.2 billion tokens from five parliamentary traditions spanning 1803--2026. The resulting sparse representations agree substantially more strongly with linguistic statistics than dense embeddings or a pooled sparse autoencoder ($ρ=0.72$ versus $0.29$ and $0.28$), and reveal that morphology, syntax, semantics, and pragmatics generally change by comparable amounts within a language, while languages differ markedly in when, how far, and in which direction they change. These findings show that historical language change is a structured, multidimensional process: similar magnitudes can conceal different trajectories, and meaningful cross-linguistic comparison requires measuring both distance and direction.
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