MolTailor: Tailoring Chemical Molecular Representation to Specific Tasks via Text Prompts

arXiv:2401.11403v2 Announce Type: replace
Abstract: Deep learning is now widely used in drug discovery, providing significant acceleration and cost reduction. As the most fundamental building block, molecular representation is essential for predicting molecular properties to enable various downstream applications. Most existing methods attempt to incorporate more information to learn better representations. However, not all features are equally important for a specific task. Ignoring this would potentially compromise the training efficiency and predictive accuracy. To address this issue, we propose a …

arxiv cs.cl cs.lg prompts q-bio.bm representation specific tasks tasks text type via