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Tsinghua University
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A unified framework reveals that the choice of tokenization and vocabulary topology can significantly influence the performance of discrete diffusion models, unlocking new avenues for optimization.
A new dual-ML framework, CycleChemist, accelerates organic photovoltaic discovery by jointly modeling donor-acceptor interactions and generating synthesizable candidates with reinforcement learning.