AI RESEARCH

Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs

arXiv CS.AI

ArXi:2605.23039v1 Announce Type: cross How do learners acquire knowledge of what is unacceptable without negative evidence? Construction Grammar proposes statistical preemption: exposure to a conventional form (e.g., "donated the books to the library") preempts structurally possible but unattested alternatives ("*donated the library the books"). We present a computational study that, for the first time, directly dissociates statistical preemption from the competing entrenchment hypothesis in large language models within a single converging design.