2 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
PerturbCellRL: Aligning Distributions and Grounding Biology via Post-Training Perturbation Generators
Dongxia Wu, Mingyu Li, Yuhui Zhang +4
Single-cell perturbation models can reduce costly wet-lab screening by predicting how cells respond transcriptionally to interventions. Recent advances in flow-matching have enable…
CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning
Dongxia Wu, Shiye Su, Yuhui Zhang +4
Building virtual cells with generative models to simulate cellular behavior in silico is emerging as a promising paradigm for accelerating drug discovery. However, prior image-base…
Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging
Dongxia Wu, Yuhui Zhang, Serena Yeung-Levy +2
Distribution-to-distribution generative models support scientific imaging tasks ranging from modeling cellular perturbation responses to translating medical images across condition…
PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR
James Burgess, Jan N. Hansen, Duo Peng +5
Search agents are language models (LMs) that reason and search knowledge bases (or the web) to answer questions; recent methods supervise only the final answer accuracy using reinf…