Sep 8, 2018 · We train stack RNN models on a number of tasks, including string reversal, context-free language modelling, and cumulative XOR evaluation.

We train stack RNN models on a number of tasks, including string reversal, context-free language modelling, and cumulative XOR evaluation.

It is shown that stack-augmented RNNs can discover intuitive stack-based strategies for solving tasks, and more complex networks often find approximate ...

This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and ...

Yiding Hao, William Merrill, Dana Angluin, Robert Frank, Noah Amsel, Andrew Benz, Simon Mendelsohn: Context-Free Transductions with Neural Stacks.

This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and ...

Figure 1: The Neural Stack architecture. Figure 5: Diagrams of network computation on the Reversal task with linear and LSTM controllers. In each diagram, the ...

Context-Free Transductions with Neural Stacks. Yiding Hao | William Merrill | Dana Angluin | Robert Frank | Noah Amsel | Andrew Benz | Simon Mendelsohn ...

This repository includes a PyTorch implementation of the paper Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages.

[language modelling] A statistical language model is a probability distribution over sequences of words. Given such a sequence, say of length m, ...