arXiv cs.LGPaper
Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference
Scale plus a prior-fitted model for in-context prediction is a sensible combination for data-starved drug discovery tasks, and the pairwise statistical comparison framework is a good methodological choice that most molecular ML papers skip. This is squarely for computational chemistry and drug discovery teams evaluating foundation models for lead optimization, not a general AI signal. Worth benchmarking against your existing MFM if you're doing bioassay prediction work.