Coalescence and translation: A language model for population genetics

Abstract

cxt is a language model for population genetics which introduces next-coalescence prediction as translation from observed mutations to coalescence times by modeling the coalescent with recombination as a conditional stochastic process. It learns implicit priors from stdpopsim and generalizes across both known and novel demographies. cxt generates millions of the most recent common ancestor estimates in minutes and samples well-calibrated posteriors for uncertainty quantification. A simple post hoc correction aligns predicted diversity with the species mutation rate, ensuring robustness to novel evolutionary scenarios. Keywords: language models, coalescent theory, uncertainty, stdpopsim, simulation-based inference