Papers by Pramod Sharma

1 papers
Multilingual Molecular Representation Learning via Contrastive Pre-training (2022.acl-long)

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Challenge: Molecular representation learning is an essential role in cheminformatics, but language model-based approaches focus on local features, hence they may not capture global information.
Approach: They propose a multilingual molecular embedding generation approach that uses two different languages to train a given molecule.
Outcome: The proposed approach is pre-trained using SMILES and IUPAC as two different languages on large-scale molecules.

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