AI RESEARCH
An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal
arXiv CS.CL
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ArXi:2604.18293v1 Announce Type: new Surprisal theory hypothesizes that the difficulty of human sentence processing increases linearly with surprisal, the negative log-probability of a word given its context. Computational psycholinguistics has tested this hypothesis using language models (LMs) as proxies for human prediction.