Finding Syntactic Representations in Neural Stacks
Table 1: Results for language models trained on the Wikipedia dataset.
['[EMPTY]', '[BOLD] Stack ( [ITALIC] ut=1)', '[BOLD] Stack ( [ITALIC] dt=1)', '[BOLD] LSTM']
The stack RNN is comparable to our LSTM baseline in terms of language modeling perplexity and agreement prediction accuracy when ut is fixed to 1, though the latter performs slightly better according to both metrics. The stack RNN attains a significantly worse perplexity when dt is fixed to 1, and its agreement prediction accuracy is worse than both the LSTM baseline and the stack RNN with ut=1.