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cs.CL2025
To model human linguistic prediction, make LLMs less superhuman
Byung-Doh Oh, Tal Linzen
When we read, we make predictions about upcoming words; these predictions influence our reading behavior. The success of large language models (LLMs), which, like humans, make pred…
cs.CL2025
How Well Does First-Token Entropy Approximate Word Entropy as a Psycholinguistic Predictor?
Christian Clark, Byung-Doh Oh, William Schuler
Contextual entropy is a psycholinguistic measure capturing the anticipated difficulty of processing a word just before it is encountered. Recent studies have tested for entropy-rel…
cs.CL2025
The Inverse Scaling Effect of Pre-Trained Language Model Surprisal Is Not Due to Data Leakage
Byung-Doh Oh, Hongao Zhu, William Schuler
In psycholinguistic modeling, surprisal from larger pre-trained language models has been shown to be a poorer predictor of naturalistic human reading times. However, it has been sp…