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Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning

AAAI 2020 · Vision-language and multimodal › Human and embodied modeling · approach: Abstract visual reasoning benchmarks · 23 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add geometric context information to symbolic searchPure Symbolic Search · MNSaccuracy: 52.15% -> 56.70%Helped
Add geometric context information to symbolic searchPure Symbolic Search · Combination holisticaccuracy: 62.98% -> 64.38%Helped
Add geometric context information to symbolic searchPure Symbolic Search · Combination analyticaccuracy: 56.83% -> 56.08%Hurt
Add geometric context information to symbolic searchPure Symbolic Search · Composition holisticaccuracy: 22.17% -> 29.81%Helped
Add geometric context information to symbolic searchPure Symbolic Search · Composition analyticaccuracy: 53.73% -> 61.84%Helped
Add geometric context information to symbolic searchPure Symbolic Search · Partition holisticaccuracy: 51.29% -> 59.70%Helped
Add geometric context information to symbolic searchPure Symbolic Search · Partition analyticaccuracy: 71.60% -> 67.59%Hurt
Use a ResNet-18 visual backbone rather than the other tested neural-network modelsNeural-network baselines · MNSaccuracy: 25.29%Helped

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