Across three real-world mRNA datasets spanning two orders of magnitude in size, RNAGenScape increases median property gain by up to 148% and success rate by up to 30% while ensuring biological viability of generated sequences, and achieves competitive inference efficiency relative to existing generative approaches.
Dan-Qi Liao, Chen Liu, Xing-Zhi Sun et al.· arXiv.org· 2 citations
Predicting cellular responses to perturbation requires resolving coordinated changes across molecular layers, yet most single-cell perturbation models focus on transcriptional responses alone. Here we present MultiFlow, a coupled flow-matching framework that unifies generation and perturbation prediction of paired gene...
RegFM emerges as a scalable and interpretable framework for modeling human transcriptional regulation and provides insights into context-dependent gene regulatory programs.
Zijing Gao, Yining Sun, Hao-Chen Wang et al.· bioRxiv· 0 citations
This work studies low-budget black-box optimization, where unaided language models remain well below strong classical optimizers and attains the lowest regret on a sealed YouTube reward-tuning production benchmark.
Yi Wu, Zheng Ren, Zhi-Yu Hu et al.· 1 citation
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