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Showing papers from Shanghai Academy of Artificial Intelligence for Science Show all papers

57%Worth a look
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NeurIPS 2026FudanShanghai Academy of Artificial ISpatio-temporal forecasting

AirMPA: A Meteorology-to-Pollution Adapter for Global Air Quality Forecasting

Yiheng Wang, kai zheng, Yuetan Lin, Fanglu Fan and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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1/20 AI panelreviewers recommend it

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026AntGroupShanghai Academy of Artificial IFudanGenomics & single-cell

Nüwa.RNA: An RNA Foundation Model for Unified Representation with Deep Structure Infusion

Kun Huang, Jiyang Li, Xin Guo, LIMEI HAN and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
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NeurIPS 2026SpotlightShanghai Academy of Artificial IKuaishou- 快手科技FudanXiamenMolecules & drug discovery

GOLD: Geometric Optimized Latent Diffusion for Structure-Aware RNA Inverse Folding

Qi Si, Xuyang Liu, Penglei Wang, Shuo Su and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
72%Highly rated
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NeurIPS 2026Shanghai Academy of Artificial IBeijing University of Post and TFlow matching

Flow Perturbation++: Multi-Step Unbiased Jacobian Estimation for High-Dimensional Boltzmann Sampling

Flow Perturbation++ performs multi-step unbiased Jacobian estimation for continuous normalizing flows, reducing variance to improve high-dimensional Boltzmann sampling.

xinpeng peng, Ang Gao

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 5/10
strict 0/5
78%Highly rated
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NeurIPS 2026Shanghai Academy of Artificial IXiamenSUN YAT-SEN UNIVERSITYnanjing universityFudanMolecules & drug discovery

Equivariant Spherical Transformer for Efficient Molecular Modeling

EST applies Transformers in Fourier spatial domains to boost equivariant GNN expressiveness, achieving state-of-the-art results on OC20 and QM9.

Junyi An, Xinyu Lu, Yun-Fei Shi, Peijia Lin and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 3/5
medium 8/10
strict 0/5