Generative Modeling

Ask about this topic

Overview

Generative modeling studies how to learn the structure and variability of data so a model can produce new samples, fill in missing information, or propose designs. Major approaches include variational autoencoders, generative adversarial networks, autoregressive models, normalizing flows, energy-based models, and diffusion, score-based, and flow-matching methods. Researchers evaluate these methods on tasks such as image and video synthesis, text generation, molecular design, and scientific simulation, using measures of fidelity, diversity, coverage, and downstream usefulness. Current work seeks faster, more controllable generation that respects constraints and data geometry, while addressing trade-offs among quality, diversity, reliability, compute cost, and memorization.

Latest papers

CardsList

509 papers68 papers in the last four weeks, up 100% on the four weeks before. 0.4% of all new papers.

  1. Localizing Concepts in Visual Autoregressive Models

    Oct 29, 2026Nanxiang Jiang, Yang Liu, Yuanhao Wang +1Visual Autoregressive ModelsGenerative Modeling

    University of California, Los Angeles · Carnegie Mellon University

  2. Geometric Time Score Estimators: Bridging Self-Predictive Representations and Generative Occupancy Models For Reinforcement Learning

    Oct 28, 2026Aravind Venugopal, Grace Liu, Jeff Schneider +1Predictive Representation LearningGenerative Modeling

    Carnegie Mellon University · Princeton University

  3. Generative modeling for fusion: a large-scale benchmark of stellarator fast-ion simulations

    Oct 27, 2026Misha Padidar, Teresa Huang, Mark Goldstein +2Generative ModelingSurrogate Modeling

    Center for Computational Mathematics, Flatiron Institute · Department of Statistics and Data Science, Cornell University

  4. An end-to-end framework for uncertainty-aware validation of generative models

    Oct 27, 2026Giada Badaracco, Sean Benevedes, Christina Reissel +2Uncertainty QuantificationGenerative Modeling

    ETH Zürich, Zürich, CH · NSF AI Institute for Artificial Intelligence and Fundamental Interactions, Cambridge, MA, USA · School of Physics, Georgia Institute of Technology, Atlanta, GA, USA +2

  5. Generative AI in Turbulence: Foundations, Applications, Validations and Benchmarks

    Oct 26, 2026Luca Biferale, Michele BuzzicottiGenerative ModelingGenerative AI Evaluation

    Department of Physics and INFN, University of Rome Tor Vergata, Rome, Italy

  6. Sparse Reconstruction by Direct Measurement-to-Field Generation in Function Space

    Oct 26, 2026Linzheng Wang, Jason Chen, Nicolas Tricard +3Sparse RecoveryInverse Problems

    Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Civil, Environmental and Geomatic Engineering, University College London, London WC1E 6BT, UK · Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK

  7. Intrinsic Gradient Barriers in Pushforward Deep Generative Models

    Oct 25, 2026Edric Tam, Qingyang Liu, Barbara Engelhardt +1Generative ModelingOptimal Transport

    Department of Biomedical Data Science, Stanford University · Department of Statistical Sciences, Wake Forest University · Department of Statistics, George Mason University

  8. Interpretable and Steerable Molecular Graph Generation using Concept Bottlenecks

    Oct 25, 2026Sarabeshwar Balaji, Ritesh Kumar, Lav R. VarshneyMolecular Graph GenerationMolecular Generation

    Indian Institute of Science Education and Research Bhopal, India · CSIR-Central Scientific Instruments Organisation, Chandigarh, India · Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India +1

  9. How Geometry Shapes Generative Model Evaluation on Riemannian Manifolds

    Oct 24, 2026Misha Oberski, Valentijn Oldenburg, Xanthos Kekkos +6Generative AI EvaluationWasserstein Distance

    University of Amsterdam · Independent Researcher · AMLab, University of Amsterdam

  10. Variational Atlas Autoencoders and Self-Supervised Chart Selection

    Oct 24, 2026Arno Coomans, Merlin Nimier-David, Eugene d'Eon +1Variational AutoencodersManifold Learning

    NVIDIA · Graz University of Technology, Austria

  11. Flow Mesh: A Velocity-Regularized Flow Matching Framework for Stable Distributional Modeling of Physical Fields on Unstructured Meshes

    Oct 23, 2026Siddharth Verma, Jaewan Park, Jay Phil Yoo +3Generative ModelingFlow-Based Generative Modeling

    Department of Mechanical Engineering, Indian Institute of Technology Bombay, Mumbai, India · National Center for Supercomputing Applications, Urbana, IL, USA · Grainger College of Engineering, Mechanical Science & Engineering Department, University of Illinois Urbana-Champaign, Urbana, IL, USA +3

  12. Generative Modeling via Nonlinear Schrödinger Bridges and Branching Diffusions

    Oct 21, 2026Mathias Grau, Pierre Henry-LabordèreGenerative ModelingSchrödinger Bridges

    †Qube Research & Technologies, Paris, France.

  13. LOB-Impact Benchmark: Emergent Market Impact in Generative Limit Order Book Models

    Oct 19, 2026George Nigmatulin, Valentin Mohl, Sascha Frey +6Limit Order Book ModelingGenerative Modeling

    British Open-ended Learning and Discovery Lab (BOLD), Department of Engineering Science, University of Oxford, Oxford, United Kingdom · British Open-ended Learning and Discovery Lab (BOLD), Department of Computer Science, University of Oxford, Oxford, United Kingdom · British Open-ended Learning and Discovery Lab (BOLD), Department of Statistics, University of Oxford, Oxford, United Kingdom +2

  14. Trajectory Replay: Continuous-Time Mixture Transport for Lifelong Generative Models

    Oct 19, 2026Alessandro Palma, Charles Jones, Tristan Cinquin +2Generative ModelingGenerative Replay

    Helmholtz Munich · Technical University of Munich · Munich Center for Machine Learning +3

  15. Distribution-Based Regularization for Reward Fine-Tuning Diffusion and Flow Models

    Oct 17, 2026Romeo Passaro, Jeongjae Lee, Jong Chul Ye +4Generative ModelingDiffusion Model Alignment

    University of Oxford · AITHYRA · KAIST +2

  16. On the Selectivity of Generative Models in Structure-Based Drug Design

    Oct 16, 2026Ella Miray Rajaonson, Jungyoon Lee, William Chau +5Structure-Based Drug DesignDrug Discovery

    University of Toronto · Vector Institute · Université de Montréal +6

  17. DeDiCa: A Scalable Deconfounding Discrete Causal Generative Model

    Oct 16, 2026Kunchangtai Liang, Adrián Javaloy, Antonio Vergari +1Causal InferenceCausal Effect Estimation

    Department of Computer Science, Saarland University, Saarbrücken, Germany · Department of Computer Science, University of Bath, Bath, United Kingdom · School of Informatics, University of Edinburgh, Edinburgh, United Kingdom

  18. ADT: All-Atom Diffusion Tokenizer for 3D Molecular Structures

    Oct 16, 2026Xuantuo Huang, Encheng Su, Aoran Wang +6Protein Structure Generation3D Molecular Generation

    Peking University · University of Science and Technology of China · Shanghai AI Laboratory +1

  19. OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling

    Oct 15, 2026Bowei Liu, Xinchen Zhang, Xuhuan Li +10Multimodal Model EvaluationVision-Language Model-as-a-Judge

    Tsinghua University · Amap, Alibaba Group · Peking University +1

  20. Mine, Sample, Render: Test-Time Diversity Alignment Of Generative Models

    Oct 15, 2026Kostas Triaridis, Morris E. Sharp, Nebojsa JojicGenerative ModelingDiversity-Aware Sampling

    Stony Brook University · Microsoft

  21. Defining and Generating Compositional Structure

    Oct 14, 2026Eric Elmoznino, Tejas Kasetty, Blaise Agüera y Arcas +2Compositional Image GenerationGenerative Modeling

    Mila – Quebec AI Institute · Université de Montréal · Google Paradigms of Intelligence Team +1

  22. Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion

    Oct 14, 2026Huixuan Cheng, Bike Zhang, Shankar Sastry +1Generative ModelingHumanoid Robot Control

    The authors are with the University of California, Berkeley.

  23. Discriminative Score Function: Turning Pretrained Models into Functional Generative Priors

    Oct 14, 2026Junhoo Lee, Hyeonjin Kim, Sangbum Han +1Generative ModelingImage Generation

    Seoul National University

  24. Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes

    Oct 13, 2026Ethan Baron, Alan N. Amin, Andrew Gordon WilsonPhylogenetic InferenceGenerative Modeling

    New York University

  25. MaskSense: Confronting the Visual Exploration Trap in Masked Image Generation

    Oct 12, 2026Yawen Shao, Jie Xiao, Kai Zhu +6Generative ModelingRL for Image Generation

    University of Science and Technology of China · Tongyi Lab, Alibaba Group · Northeastern University

  26. TabGift: A Context-Efficient Foundation Model for Tabular Data Generation

    Oct 12, 2026Yu-Sheng Li, Jun-Peng Jiang, Han-Jia YeSynthetic Tabular Data GenerationGenerative Modeling

    School of Artificial Intelligence, Nanjing University, China · National Key Laboratory for Novel Software Technology, Nanjing University, China

  27. NFMap: Topographic 2D Manifold Learning with Invertible Normalizing Flows

    Oct 12, 2026Héléna Alexandra GasparDimensionality ReductionManifold Learning

    LovingScience 124 City Road, London EC1V 2NX

  28. OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows

    Oct 12, 2026Yu-Tong Jin, Yi-Yang Tian, Qiwei Ye +13D Molecular GenerationGenerative Modeling

    Peking University · Beijing Academy of Artificial Intelligence

  29. Self-Verifier Capture in Unified Visual Generators: Diagnosing and Repairing Closed-Loop Self-Reward

    Oct 12, 2026Binyan Chen, Tong PanReward HackingGenerative Modeling

    University of Science and Technology of China

  30. DeTac: Dual-branch Decoupling of Texture and Force Signals in Vision-Based Tactile Sensors

    Oct 12, 2026Zhirui Zhang, Yunkai Tang, Jiahang Li +6Vision-Based Tactile SensingRepresentation Disentanglement

    State Key Laboratory of Multimedia Information Processing, National Engineering Research Center of Visual Technology, and PKU-AI2 Robotics Joint Lab of Embodied AI, School of Computer Science, Peking University · AI2 Robotics · State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, and also with Shanghai Key Laboratory of Intelligent Robotics, Shanghai Jiao Tong University, Shanghai