Arcadia Science @arcadiascience.com · Jan 30 3/6 The model consistently upweights evolutionarily close sequences and downweights distant ones, despite never being trained on this. There's also a division of labor across layers: layer 11 acts as a strong phylogenetic filter, while others contribute more modestly.
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4/6 But surprisingly, encoding phylogeny ≠ leveraging it. Comparing learned weights against uniform averaging for contact prediction, the aggregate improvement was marginal. Per-MSA, uniform averaging outperformed learned weights about half the time, sometimes by a large margin.