5 papers
Generative Molecular Design with Steerable and Granular Synthesizability Control
Jeff Guo, VÃctor Sabanza-Gil, Olha Semenenko +20
Designing molecules that are both property-optimal and readily synthesizable is a central challenge in drug discovery. Existing works that do consider synthesizability can jointly…
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong +4
Retrosynthesis, the process of breaking down a target molecule into simpler precursors through a series of valid reactions, stands at the core of organic chemistry and drug develop…
Evaluating Large Language Models in Scientific Discovery
Zhangde Song, Jieyu Lu, Yuanqi Du +53
Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…
Accelerating inverse materials design using generative diffusion models with reinforcement learning
Junwu Chen, Jeff Guo, Edvin Fako +1
Diffusion models promise to accelerate material design by directly generating novel structures with desired properties, but existing approaches typically require expensive and subs…
KL-Regularized Reinforcement Learning is Designed to Mode Collapse
Anthony GX-Chen, Jatin Prakash, Jeff Guo +2
It is commonly believed that optimizing the reverse KL divergence results in "mode seeking", while optimizing forward KL results in "mass covering", with the latter being preferred…