Tracking the World State with Recurrent Entity Networks

12 Dec 2016Mikael Henaff • Jason Weston • Arthur Szlam • Antoine Bordes • Yann LeCun

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.

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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