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Evolutionary context from MSAs dramatically improves protein-to-DNA translation, boosting native codon recovery by nearly 18% and capturing subtle biological nuances missed by isolated sequence models.
Protein language models, despite borrowing NLP architectures, distribute information across layers very differently, but a simple early-exit strategy can exploit this to boost both accuracy and efficiency.