1 citations · 3 across the 12 of their papers we have counts for
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Monkey King Bang: A Unified Scientific Multimodal Foundation Model
Hesen Chen, Xinyu Su, Xiaomeng Yang +11
Scientific discovery is increasingly shifting from isolated disciplines to multi-domain reasoning, and AI for science faces a similar transition. Existing systems are either specia…
Nested Spatio-Temporal Time Series Forecasting
Yinghao Ai, Yukai Zhou, Ruoxi Jiang +8
Spatiotemporal forecasting is critical for real-world applications like traffic management, yet capturing reliable interactions remains challenging under noisy and non-stationary c…
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
Qi Si, Penglei Wang, Yushuai Wu +5
Predicting spatial gene expression from routine H\&E enables large-scale molecular profiling, yet current models treat this as isolated pointwise tasks, thereby overlooking essenti…
Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation
Junyi An, Chao Qu, Yun-Fei Shi +3
Recent 3D molecular generation methods primarily use asynchronous auto-regressive or synchronous diffusion models. While auto-regressive models build molecules sequentially, they'r…
A Pre-trained Reaction Embedding Descriptor Capturing Bond Transformation Patterns
Weiqi Liu, Fenglei Cao, Yuan Qi +1
With the rise of data-driven reaction prediction models, effective reaction descriptors are crucial for bridging the gap between real-world chemistry and digital representations. H…
Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation
Zhijian Zhou, Junyi An, Zongkai Liu +5
Generating physically realistic 3D molecular structures remains a core challenge in molecular generative modeling. While diffusion models equipped with equivariant neural networks…