CellRFT: Reinforcement Fine-Tuning for Single-Cell Perturbation Modeling
Comprehensive experiments demonstrate CellRFT's applicability across different pretrained models and effectiveness in improving perturbation prediction, reveal that optimizing one biological criterion can help or hinder others, and show that complementary rewards can improve criteria beyond those directly optimized.
Jie Yan, Li Liu, Han-Ze Guo et al.
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