The CogNLP-Sheffield submissions to the CMCL 2021 Shared Task examine the value of a variety of cognitively and linguistically inspired features for predicting eye tracking patterns, as both standalone model inputs and as supplements to contextual word embeddings (XLNet). Surprisingly, the smaller pre-trained model (XLNet-base) outperforms the larger (XLNet-large), and despite evidence that multi-word expressions (MWEs) provide cognitive processing advantages, MWE features provide little benefit to either model.
|Title of host publication||Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics|
|Place of Publication||Online|
|Publisher||Association for Computational Linguistics|
|Number of pages||9|
|Publication status||Published - 1 Jun 2021|