AI RESEARCH
Different types of syntactic agreement recruit the same units within large language models
arXiv CS.CL
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ArXi:2512.03676v2 Announce Type: replace Large language models (LLMs) can reliably distinguish grammatical from ungrammatical sentences, but how grammatical knowledge is represented within the models remains an open question. We investigate whether different syntactic phenomena recruit shared or distinct components in LLMs. Using a functional localization approach inspired by cognitive neuroscience, we identify the LLM units most responsive to 67 English syntactic phenomena in seven open-weight models.