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Last-layer embeddings in protein language models often underperform, with shallow layers proving more effective for specific datasets like deep mutational scans.
Pre-training boosts CLMs' molecular structure awareness, but surprisingly, even randomly initialized models excel at encoding ring structures from the first layer.
