arXiv:2605.28616 · v2
Measuring Form and Function in Language Models
摘要
We introduce quantitative metrics for child language acquisition to evaluate language models. Our focus is on the formal syntactic and functional discourse properties of determiners in English, which young children acquire early and accurately. We propose Contextual Alternative Choice (CAC), a new prompting method which provides targeted tests for both syntactic and discourse knowledge of language. The method enables direct comparison of language models against children, and more importantly, against statistical benchmarks independently established in empirical research. No current model trained on a comparable amount of data simultaneously meet both formal and functional benchmarks like human children, but some very large models do. We present our results as methodological and technical contributions, with specific emphasis on cognitive status of language models.
作者备注：Under review at ACL Rolling Review May 2026 cycle
期刊信息：2026.babylm-main, pages 438-458, Budapest, Hungary. Association for Computational Linguistics