Superposition Yields Robust Neural Scaling

Uses a toy model of overlapping features to investigate scaling laws. Geometric analysis and language-model measurements connect representation dimension, superposition strength, and prediction loss.

Uses a toy model of overlapping features to investigate scaling laws. Geometric analysis and language-model measurements connect representation dimension, superposition strength, and prediction loss.

When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.

Uses a toy model of overlapping features to investigate scaling laws. Geometric analysis and language-model measurements connect representation dimension, superposition strength, and prediction loss.

Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.