作者位次 #2/2ACL 2026Poster· Natural Language Processing
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal
Sathvik Nair · Byung-Doh Oh
摘要
How predictable a word is can be generally quantified in two ways: using human responses to the cloze task or using probabilities from language models (LMs). When used as predictors of processing effort, LM probabilities outperform probabilities derived from cloze data. However, it is important t...