The Subregular Complexity of Syntactic Islands

What Syntactic Structures block Dependencies in RNN Language Models?

Recurrent Neural Networks (RNNs) trained on a language modeling task have been shown to acquire a number of non-local grammatical dependencies with some success. Here, we provide new evidence that RNN language models are…

What do RNN Language Models Learn about Filler-Gap Dependencies?

RNN language models have achieved state-of-the-art perplexity results and have proven useful in a suite of NLP tasks, but it is as yet unclear what syntactic generalizations they learn. Here we investigate whether state-…

What do RNN Language Models Learn about Filler--Gap Dependencies?

RNN language models have achieved state-of-the-art perplexity results and have proven useful in a suite of NLP tasks, but it is as yet unclear what syntactic generalizations they learn. Here we investigate whether state-…

MG Parsing as a Model of Gradient Acceptability in Syntactic Islands

Multiple Wh-Movement is not Special: The Subregular Complexity of Persistent Features in Minimalist Grammars