PertMind: Eliciting Emergent Biological Reasoning in LLM via Reinforcement Learning on Cellular Perturbation Data
It is shown that cellular perturbation atlases can instead become reinforcement-learning environments, where measured gene responses provide computable rewards for biological reasoning, and introduces PertMind, which combines trusted-trajectory supervised initialization with gene-, pathway-, and format-level reinforcem...
Zhen-Chao Tang, Xiao-Gang Xu, Jia-Fei Wu et al.
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