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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…
cs.CL2025★ 1 cited
Vectors from Larger Language Models Predict Human Reading Time and fMRI Data More Poorly when Dimensionality Expansion is Controlled
Yi-Chien Lin, Hongao Zhu, William Schuler
The impressive linguistic abilities of large language models (LLMs) have recommended them as models of human sentence processing, with some conjecturing a positive 'quality-power'…