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R2S-Eval reveals that automated evaluation can outperform manual success counting by capturing nuanced differences in robot behavior quality.
Achieving near-zero gravity violations and a 77% street-channel recall reveals how physics-informed models can drastically improve urban flood predictions while maintaining physical realism.