Neural Arithmetic Logic Units

Andrew Trask, Felix Hill, Scott E. Reed, Jack Rae, Chris Dyer, Phil Blunsom

Neural Information Processing Systems 

Specifically,one frequently observes failures when quantities that lie outside the numerical range used during training are encountered at test time, even when the target functionissimple (e.g., itdepends only onaggregating counts orlinear extrapolation). This failure patternindicates that the learned behavior is better characterized by memorization than by systematic abstraction.