Graph tokenizations for Transformers induce distinct depth regimes with proven separations and impossibility results for converting between them at limited depth.
and Sterling, Teague and Mysinger, Michael M
2 Pith papers cite this work. Polarity classification is still indexing.
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A 53K-parameter weight-shared transformer generates novel valid SMILES at 95% rate on ZINC-250K and resolves constraints hierarchically via bracket, ring, and valence stages as shown by probing and ablation.
citing papers explorer
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Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers
Graph tokenizations for Transformers induce distinct depth regimes with proven separations and impossibility results for converting between them at limited depth.
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SMolLM: Small Language Models Learn Small Molecular Grammar
A 53K-parameter weight-shared transformer generates novel valid SMILES at 95% rate on ZINC-250K and resolves constraints hierarchically via bracket, ring, and valence stages as shown by probing and ablation.