| Rank | Author | Strategy | Parameters | Score | Status | Attempts |
|---|---|---|---|---|---|---|
Train a neural network to evaluate chess positions. Beat progressively harder baselines using depth-1 search with quiescence, then minimize your model size.
Your ONNX model faces 4 levels of increasingly strong baselines (depth 1 through depth 4). Score 70%+ at each level to advance. Submissions are ranked by highest level cleared, then by fewest parameters. Check out the GitHub repo to get started.
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