Dragon Hatchling: A careful guide to BDH's graph-inspired state-space model

What the architecture changes, what the experiments establish, and where the brain analogy stops
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Dragon Hatchling connects a high-dimensional linear-attention state-space model to local graph dynamics. This guide explains the recurrence, the qualified relationship between BDH and BDH-GPU, the Europarl scaling results, and the limits of the paper's claims about interpretability, long context, model composition, and biological plausibility.

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