7 citations · 23 across the 11 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.CL2026
A Systematic Analysis of the Predictive Power of LM Surprisal in Reading Chinese
Hongao Zhu, Muxiaoqiao Xu, Yikang Liu +4
This study analyzes the predictive power of LM-derived, token-level surprisal on Mandarin Chinese reading times. We first propose the Shortest Matching Sequence (SMS), an alignment…
cs.CL2026
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal
Sathvik Nair, Byung-Doh Oh
How predictable a word is can be quantified in two ways: using human responses to the cloze task or using probabilities from language models (LMs).When used as predictors of proces…