most citedCellVerse: Do Large Language Models Really Understand Cell Biology?

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2025

NeuralOGCM: Differentiable Ocean Modeling with Learnable Physics

Hao Wu, Yuan Gao, Fan Xu +4

High-precision scientific simulation faces a long-standing trade-off between computational efficiency and physical fidelity. To address this challenge, we propose NeuralOGCM, an oc…

cs.LG2025

Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models

Hao Wu, Yuan Gao, Xingjian Shi +9

To address the dual challenges of inherent stochasticity and non-differentiable metrics in physical spatiotemporal forecasting, we propose Spatiotemporal Forecasting as Planning (S…

cs.LG2025

FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling

Haixin Wang, Jiashu Pan, Hao Wu +2

Modeling complex fluid systems, especially turbulence governed by partial differential equations (PDEs), remains a fundamental challenge in science and engineering. Recently, diffu…

q-bio.QM20251 cited

CellVerse: Do Large Language Models Really Understand Cell Biology?

Fan Zhang, Tianyu Liu, Zhihong Zhu +7

Recent studies have demonstrated the feasibility of modeling single-cell data as natural languages and the potential of leveraging powerful large language models (LLMs) for underst…

cs.LG2025

Advanced Long-term Earth System Forecasting

Hao Wu, Yuan Gao, Ruijian Gou +30

Reliable long-term forecasting of Earth system dynamics is fundamentally limited by instabilities in current artificial intelligence (AI) models during extended autoregressive simu…