%0 Conference Proceedings %T A Neural Model of Adaptation in Reading %A van Schijndel, Marten %A Linzen, Tal %Y Riloff, Ellen %Y Chiang, David %Y Hockenmaier, Julia %Y Tsujii, Jun’ichi %S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing %D 2018 %8 oct nov %I Association for Computational Linguistics %C Brussels, Belgium %F van-schijndel-linzen-2018-neural %X It has been argued that humans rapidly adapt their lexical and syntactic expectations to match the statistics of the current linguistic context. We provide further support to this claim by showing that the addition of a simple adaptation mechanism to a neural language model improves our predictions of human reading times compared to a non-adaptive model. We analyze the performance of the model on controlled materials from psycholinguistic experiments and show that it adapts not only to lexical items but also to abstract syntactic structures. %R 10.18653/v1/D18-1499 %U https://aclanthology.org/D18-1499 %U https://doi.org/10.18653/v1/D18-1499 %P 4704-4710