DTG-FF reaches 91.8% on CIFAR-10 and 49.4% on ImageNet-100 224x224 but BP baselines beat it by 2.4-5.93 pp with gaps widening by class count on real data while reversing the synthetic trend.
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, and Yuxiong He
4 Pith papers cite this work. Polarity classification is still indexing.
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NLRΔ applied to 50 primary measures from five cognitive task families on public test-retest data yields median -0.138 nats with zero cells passing the headline rule across a 24-specification multiverse.
Applies causal inference to PCs from MD trajectories of two proteins to construct directed influence networks complementary to PCA and TICA.
Kernel ridge regression combined with mRMR feature selection improves prediction of full benchmark scores from question subsets over existing efficient benchmarking techniques.
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Synthetic Benchmarks Overstate Forward-Forward Scaling: Real-Data Limits of Layer-Local Training
DTG-FF reaches 91.8% on CIFAR-10 and 49.4% on ImageNet-100 224x224 but BP baselines beat it by 2.4-5.93 pp with gaps widening by class count on real data while reversing the synthetic trend.