aicrowd/arc-whestbench-convergence-2026

该数据集记录了arc-whestbench-public-2026数据集中前100个多层感知机（MLP）的每个神经元累积平均激活值，采样预算从N=1到N=1,000,000,000，共860个对数间隔的样本点。这是一个针对v1-warmup的研究辅助数据集，旨在演示蒙特卡洛均值估计如何随着样本预算的增加而收敛。Per-neuron cumulative mean activations of the first 100 MLPs of aicrowd/arc-whestbench-public-2026 captured at 860 log-spaced sample budgets from N=1 to N=1,000,000,000. This is a research sidecar to v1-warmup. It demonstrates how Monte Carlo mean estimates of the activations converge as the sample budget grows.