Zhi Song

PertMind reveals that leveraging cellular perturbation data can significantly enhance LLMs' biological reasoning capabilities without extensive task-specific retraining.

Hard-assigned predictors in MoP-JEPA enable accurate planning in stochastic environments, achieving up to 42 times better performance than traditional methods.