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Tatsuya Sagawa, Ryosuke Kojima · 2023 · arXiv 2311.06708

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cs.CL 1

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2026 1

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UNVERDICTED 1

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Augmenting Molecular Language Models with Local $n$-gram Memory

cs.CL · 2026-06-10 · unverdicted · novelty 7.0

MolGram integrates a conditional n-gram memory module into molecular language models to address locality gaps in SMILES tokenization, improving performance on generation, forward prediction, and retrosynthesis while outperforming 3x larger baselines.

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  • Augmenting Molecular Language Models with Local $n$-gram Memory cs.CL · 2026-06-10 · unverdicted · none · ref 63

    MolGram integrates a conditional n-gram memory module into molecular language models to address locality gaps in SMILES tokenization, improving performance on generation, forward prediction, and retrosynthesis while outperforming 3x larger baselines.