Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling
This work investigates whether LLMs can learn molecular design strategies from cheaper synthetic tasks that generalize to expensive molecular lead optimization settings and suggests that scaling post-training using synthetic tasks is an effective strategy for adapting LLMs to high-cost experimental scenarios that are t...
Frank Hu, Shriram Chennakesavalu, Zi-Cheng Wang et al.
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