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A General-Purpose Molecular Foundation Model Transfers Across Diverse Olfactory Tasks
Foundation models have transformed molecular property prediction, yet it remains unclear whether a molecular foundation model, fine-tuned on a single canonical olfactory prediction task, can learn representations that transfer across diverse machine olfaction problems. We investigate this question by fine-tuning Uni-Mol2 on the GS-LF benchmark for multi-label odor descriptor prediction and evaluating the resulting model, without additional deep-learning training, on four complementary downstream settings: cross-dataset odor descriptor prediction, odorous-versus-odorless classification, enantio
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T15:11:15.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.