esgaliant
Published:
esgaliant builds synthetic data used to anchor large scale foundation models and to probe what biology is actually captured by large data sets.
By generating data where the ground truth is known by construction, esgaliant provides a controlled setting to ask what a model has learned, what it has memorized, and where the biological signal in a training set really sits.
GitHub Page
Analysis
Publications
In progress