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cs.CL2026
Estimating Surprisal from the Speech Signal
Zachary Hopton, Samuel Kiegeland, Francesco Ignazio Re +4
Although language is predominantly spoken, empirical tests of surprisal theory rely almost entirely on written text. In practice, surprisal is estimated using language models (LMs)…
cs.CL2026
Revisiting the Estimation of Unigram Surprisal in Computational Psycholinguistics
Zachary Hopton, Francesco Ignazio Re, Samuel Kiegeland +3
Contextual and unigram surprisal are standard predictors of reading time in computational psycholinguistics. While contextual surprisal is typically derived from neural language mo…
cs.CL2026
Probing for Reading Times
Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re +4
Probing has shown that language model representations encode rich linguistic information, but it remains unclear whether they also capture cognitive signals about human processing.…