WhestBench 2026: ARC White-Box Estimation Challenge

Organized by: Alignment Research Center (ARC), AIcrowd WhestBench 2026: ARC White-Box Estimation Challenge WhestBench is a benchmark for white-box activation estimation: given the weights of a randomly initialized ReLU multi-layer perceptron (MLP) and a strict floating-point-operation (FLOP) budget, predict the average post-activation value of every neuron when the network is fed standard Gaussian inputs. This is the WhestBench 2026… See the full description on the dataset page:

Source: Hugging Face Hub (aicrowd/arc-whestbench-public-2026). Metadata imported from the dataset’s Hub tags.