Learning grammar with a divide-and-concur neural network. (arXiv:2201.07341v1 [cs.CL])

We implement a divide-and-concur iterative projection approach to
context-free grammar inference. Unlike most state-of-the-art models of natural
language processing, our method requires a relatively small number of discrete
parameters, making the inferred grammar directly interpretable -- one can read
off from a solution how to construct grammatically valid sentences. Another
advantage of our approach is the ability to infer meaningful grammatical rules
from just a few sentences, compared to the hundreds of gigabytes of training
data many other models employ. …

arxiv grammar learning network neural network