LLMs show statistical preemption for 120 verb-construction pairs, with surprisal driven by competing-form frequency rather than verb frequency, scaling as a power law with size, and causally shifted by controlled fine-tuning.
We address the resulting circularity concern with non-circular partial correlations against human data (§5.4)
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Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs
LLMs show statistical preemption for 120 verb-construction pairs, with surprisal driven by competing-form frequency rather than verb frequency, scaling as a power law with size, and causally shifted by controlled fine-tuning.