It is equipped with a dynamic long-term memory which allows it to maintain and update a representation of the state of the world as it receives new data. Like a Neural Turing Machine or Differentiable Neural Computer (Graves et al., 2014; 2016) it maintains a fixed size memory and can learn to perform location and content-based read and write operations. The EntNet sets a new state-of-the-art on the bAbI tasks, and is the first method to solve all the tasks in the 10k training examples setting.
|Task||Dataset||Model||Metric name||Metric value||Global rank||Compare|
|Question Answering||bAbi||EntNet||Accuracy (trained on 10k)||99.5%||# 2|
|Question Answering||bAbi||EntNet||Accuracy (trained on 1k)||89.1%||# 2|
|Question Answering||bAbi||EntNet||Mean Error Rate||9.7%||# 2|