Why are language models less surprised than humans? Testing the Parse Multiplicity Mismatch Hypothesis

This paper explores why language models exhibit less surprisal than humans when processing syntactically ambiguous sentences. It tests the hypothesis that LMs can simultaneously consider a greater number of sentence interpretations using Recurrent Neural Network Grammars.