Compositional Attention Networks for Machine Reasoning

ICLR 2018 Drew A. HudsonChristopher D. Manning

We present the MAC network, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning. MAC moves away from monolithic black-box neural architectures towards a design that encourages both transparency and versatility... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Visual Question Answering CLEVR MAC Overall Accuracy 98.9 # 1

Methods used in the Paper


METHOD TYPE
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