Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PDE families, and stability under long autoregressive rollouts. Deterministic operators accumulate error geometrically, while existing probabilistic solvers are confined to a single PDE family or short horizons. We close this gap with the \textbf{Latent Generative Solver} (LGS), three coupled components: (i) a Physics VAE (PhyVAE) compressing twelve PDE families into a shared latent manifold; (ii) a Pyramidal Flow-Forcing Transformer (PFlowFT) that generates the next latent by flow matching, conditioned on a per-trajectory context updated on the model's own predictions; and (iii) input noising during training, for which we derive a sufficient-condition contraction bound explaining the observed long-horizon stability. Pretrained on a 2.5\,M-trajectory, 16-system corpus at $128^2$, LGS matches the strongest deterministic baseline at one step, wins on 15/16 systems at both 5- and 10-step rollout, cuts 20-step L2RE from $56.1\%$ to $\mathbf{30.2\%}$, and uses $\mathbf{13}$--$\mathbf{77\times}$ less recurrent dynamics-step compute. It also adapts efficiently to a $256^2$ Kolmogorov flow held out from the pretraining corpus, dropping 1-step L2RE from $0.398$ to $0.129$ in five finetune epochs against U-AFNO's $0.653{\to}0.343$. These empirical claims are limited to the evaluated 2D regular-grid systems and discrete horizons.
LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization
CNRS（法国国家科学研究中心）；Univ. Bordeaux（波尔多大学）；INRIA（法国国家信息与自动化研究所）；Bordeaux INP（波尔多国立高等工程技术学院）；Heriot-Watt University（赫瑞瓦特大学）；Maxwell Institute for Mathematical Sciences（麦克斯韦数学科学研究所）
A tutorial on discovering and quantifying the effect of latent causal sources of multimodal EHR data
Department of Biomedical Informatics Vanderbilt University Medical Center（生物医学信息学系范德堡大学医学中心）；Department of Biomedical Informatics University of Pittsburgh（生物医学信息学系匹兹堡大学）；Departments of Medicine & Biomedical Informatics Vanderbilt University Medical Center（医学与生物医学信息学系范德堡大学医学中心）；Departments of Biomedical Informatics & Computer Science Vanderbilt University Medical Center & Vanderbilt University（生物医学信息学与计算机科学系范德堡大学医学中心及范德堡大学）
Learning to Reduce Search Space for Generalizable Neural Routing Solver
School of Automation and Intelligent Manufacturing（自动化与智能制造学院）；Southern University of Science and Technology（南方科技大学）；School of Mathematics and Statistics（数学与统计学学院）；Xi'an Jiaotong University（西安交通大学）；Department of Computer Science（计算机科学系）；City University of Hong Kong（香港城市大学）
Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization
Université de Lorraine, CNRS, Inria, LORIA（洛林大学、国家科学研究中心、法国国家信息与自动化研究所、LORIA实验室）；University of California Santa Barbara（加州圣芭芭拉大学）；Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）
Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
School of Science, Harbin Institute of Technology, Shenzhen, China（哈尔滨工业大学深圳校区科学学院）；Department of Theoretical Physics（理论物理系）；Applied Mathematics, University of Cambridge, Cambridge, United Kingdom（应用数学系，剑桥大学，英国）
LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process
Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist University（科学技术学院，北京师范大学-香港 Baptist大学）；Department of Mathematics, Shanghai Normal University（上海师范大学数学系）；Department of Mathematics and Center for Computation and Technology, Louisiana State University（数学系和计算技术中心，路易斯安那州立大学）；School of Mathematical Sciences, Institute of Natural Sciences, and MOE-LSC, Shanghai Jiaotong University（数学科学学院，自然科学研究院，MOE-LSC，上海交通大学）；Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences（计算数学与科学/工程计算研究所，数学与系统科学学院，中国科学院）
Out-of-Distribution Generalization for Neural Physics Solvers
Centre for Frontier AI Research (CFAR)（前沿人工智能研究中心）；Agency for Science, Technology and Research (A*STAR)（科技研究局）；Institute of High Performance Computing (IHPC)（高性能计算研究所）；School of Mechanical Sciences（机械科学学院）；Indian Institute of Technology Goa（果阿印度理工学院）；College of Computing and Data Science（计算与数据科学学院）；Nanyang Technological University（南洋理工大学）
PatientWM: Towards Generalizable Clinical World Models via Unified Patient States
University of Science and Technology of China（中国科学技术大学）；University of Central Florida（中佛罗里达大学）；Princeton University（普林斯顿大学）；Nanyang Technological University（南洋理工大学）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）
Neuro-Symbolic Multitasking: A Unified Framework for Discovering Generalizable Solutions to PDE Families
Department of Artificial Intelligence, Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan, Ministry of Culture and Tourism, School of Informatics, Xiamen University, and Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（人工智能系，福建省和台湾非物质文化遗产数字化保护与智能处理重点实验室，文化部，信息学院，厦门大学，以及多媒体可信感知与高效计算重点实验室，教育部，厦门大学）
Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks
Southwestern University（西南大学）；Southern University of Science and Technology（南方科技大学）；Queen Mary University of London（伦敦玛丽女王大学）；IT University of Copenhagen（哥本哈根信息技术大学）
NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization
School of Mathematical Sciences（数学科学学院）；Peking University（北京大学）；DP Technology（DP科技）；College of Chemistry and Molecular Engineering（化学与分子工程学院）；Xiamen University（厦门大学）；AI for Science Institute（人工智能科学研究院）；Center for Machine Learning Research, Peking University（北京大学机器学习研究中心）
