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Beyond Static and Linear: What Attention Constraints Best Fit Human Reading Times?
Lanni Bu, Xiulin Yang, Christian Clark +2
Transformer-based language models are widely used as models of human language processing, yet their attention mechanisms allow lossless access to the full preceding context, unlike…
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…
Linear Recency Bias During Training Improves Transformers' Fit to Reading Times
Christian Clark, Byung-Doh Oh, William Schuler
Recent psycholinguistic research has compared human reading times to surprisal estimates from language models to study the factors shaping human sentence processing difficulty. Pre…