AlphaEvolve BenchmarksΒΆ
BLADE includes benchmark instances inspired by the Google DeepMind AlphaEvolve paper. These instances are available in two complementary forms:
run_benchmarks/provides standalone reference scripts for running each task directly.iohblade/benchmarkspackages the same tasks for programmatic use in experiments and pipelines.
The packaged benchmarks are grouped by domain:
Analysis (auto-correlation inequalities)
Combinatorics (Erdos min-overlap)
Geometry (Heilbronn problems, kissing number, and distance ratios)
Matrix multiplication
Number theory (sums vs differences)
Packing (rectangle, hexagon, and unit square packing)
Fourier (uncertainty inequalities)
Each domain folder contains a README with task-specific details and citations to the original sources.