Generative Modeling

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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. Generative Frontiers: Why Evaluation Matters for Diffusion Language Models

    Apr 3, 2026Patrick Pynadath, Jiaxin Shi, Ruqi ZhangDiffusion Language Model BenchmarkingLanguage Model Generation Evaluation

    Department of Computer Science, Purdue University West Lafayette, Indiana, 47906, USA

  2. SEDGE: Structural Extrapolated Data Generation

    Apr 2, 2026Kun Zhang, Jiaqi Sun, Yiqing Li +3Synthetic Data GenerationGenerative Modeling

    Mohamed bin Zayed University of Artificial Intelligence · Carnegie Mellon University

  3. Generative models on phase space

    Apr 2, 2026Zachary Bogorad, Ibrahim Elsharkawy, Yonatan Kahn +2Generative ModelingConstrained Generative Modeling

    Theory Division, Fermi National Accelerator Laboratory, Batavia, IL, USA · Department of Physics, University of Toronto and Vector Institute, Toronto, ON, Canada and NERSC, Lawrence Berkeley National Laboratory, Berkeley, California, USA · Department of Physics, University of Toronto and Vector Institute, Toronto, ON, Canada +2

  4. Bridging the Simulation-to-Experiment Gap with Generative Models using Adversarial Distribution Alignment

    Apr 1, 2026Kai Nelson, Tobias Kreiman, Sergey Levine +1Generative ModelingSynthetic-to-Real Domain Adaptation

    University of California, Berkeley · Lawrence Berkeley National Laboratory (LBNL)

  5. SYNTHONY: A Stress-Aware, Intent-Conditioned Agent for Deep Tabular Generative Models Selection

    Mar 31, 2026Hochan Son, Xiaofeng Lin, Jason Ni +1Synthetic Data SelectionTabular Data Synthesis

    Department of Statistics, University of California, Los Angeles · Department of Mathematics, University of California, Los Angeles

  6. AMShortcut: An Inference- and Training-Efficient Inverse Design Model for Amorphous Materials

    Mar 31, 2026Yan Lin, Jonas A. Finkler, Tao Du +2Inverse DesignGenerative Modeling

    Aalborg University · The Hong Kong Polytechnic University · East China Normal University

  7. "I Just Need GPT to Refine My Prompts": Rethinking Onboarding and Help-Seeking with Generative 3D Modeling Tools

    Mar 31, 2026Kanak Gautam, Poorvi Bhatia, Parmit K. ChilanaHuman-AI InteractionLLM Prompting

    Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada

  8. Unrestrained Simplex Denoising for Discrete Data. A Non-Markovian Approach Applied to Graph Generation

    Mar 30, 2026Yoann Boget, Alexandros KalousisGenerative ModelingDiffusion Models

    Department of Computer Science, University of Geneva, Switzerland · DMML Group, Geneva School for Business administration HES-SO, Switzerland

  9. Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute

    Mar 30, 2026Kieran Didi, Zuobai Zhang, Guoqing Zhou +11Protein Binder DesignProtein Design

    NVIDIA · University of Oxford · Mila - Québec AI Institute +8

  10. Test-Time Instance-Specific Parameter Composition: A New Paradigm for Adaptive Generative Modeling

    Mar 29, 2026Minh-Tuan Tran, Xuan-May Le, Quan Hung Tran +3Generative ModelingTest-Time Adaptation

    Monash University · The University of Melbourne · Meta Inc

  11. Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism

    Mar 28, 2026Antheas Kapenekakis, Bent Thomsen, Katja Hose +1Synthetic Tabular Data GenerationGenerative Modeling

    Aalborg University, Aalborg, Denmark · TU Wien, Vienna, Austria

  12. Generalizable Foundation Models for Calorimetry via Mixtures-of-Experts and Parameter Efficient Fine Tuning

    Mar 27, 2026Carlos Cardona-Giraldo, Cristiano Fanelli, James Giroux +3Generative ModelingPhysics-Based Simulation

    RNET Technologies Inc., Dayton, OH 45429 · William & Mary, Department of Data Science, Williamsburg, VA 23185, USA · Fundamental Physics Directorate, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA +1

  13. Generative Modeling in Protein Design: Neural Representations, Conditional Generation, and Evaluation Standards

    Mar 27, 2026Senura Hansaja Wanasekara, Minh-Duong Nguyen, Xiaochen Liu +2Generative ModelingProtein Design

    Biomedical Engineering, The University of Sydney, Darlington, NSW 2006, Australia. · the College of Engineering and Computer Science, VinUniversity, Vietnam. · School of Computer Science and School, The University of Sydney, Darlington, NSW 2006, Australia.

  14. PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models

    Mar 27, 2026Jiyuan An, Jiachen Zhao, Fan Chen +6Text-to-CAD GenerationGenerative Modeling

    National Language Resources Monitoring and Research Center for Print Media, Beijing Language and Culture University, China · School of Information Science, Beijing Language and Culture University, China · School of Computer Science and Technology, Beijing Jiaotong University, China +3

  15. Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation

    Mar 24, 2026Michal Balcerak, Suprosanna Shit, Chinmay Prabhakar +4Generative ModelingEnergy-Based Models

    University of Zurich · Harvard University · Kempner Institute

  16. DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models

    Mar 24, 2026Donya Jafari, Farzan FarniaLLM RoutingContextual Bandits

    Sharif University of Technology · The Chinese University of Hong Kong

  17. Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging

    Mar 23, 2026Dongxia Wu, Yuhui Zhang, Serena Yeung-Levy +2Generative ModelingFlow Matching

    Stanford University Stanford, CA

  18. Mixture-Greedy for Online Generative Model Selection: Is UCB Necessary in Diversity-Aware Multi-Armed Bandits?

    Mar 23, 2026Bahar Dibaei Nia, Farzan FarniaMulti-Armed BanditsExploration-Exploitation Tradeoff

    Department of Computer Science and Engineering, Chinese University of Hong Kong.

  19. SARe: Structure-Aware Generative 3D Fragment Reassembly

    Mar 23, 2026Hanze Jia, Chunshi Wang, Yuxiao Yang +4Generative Modeling3D Reconstruction

    State Key Lab of CAD&CG, Zhejiang University · School of Software Technology, Zhejiang University · Laboratory of Art and Archaeology Image, Zhejiang University

  20. Uni-Classifier: Leveraging Video Diffusion Priors for Universal Guidance Classifier

    Mar 20, 2026Yujie Zhou, Pengyang Ling, Jiazi Bu +2Generative ModelingDiffusion Model Guidance

    Shanghai Jiao Tong University · University of Science and Technology of China

  21. Kolmogorov-Arnold causal generative models

    Mar 20, 2026Alejandro Almodóvar, Mar Elizo, Patricia A. Apellániz +2Generative ModelingStructural Causal Models

  22. SetFlow: Generating Structured Sets of Representations for Multiple Instance Learning

    Mar 20, 2026Nikola Jovišić, Milica Škipina, Vanja ŠvendaGenerative ModelingSynthetic Data Augmentation

    Institute for Artificial Intelligence R&D of Serbia Novi Sad, Serbia

  23. Diminishing Returns in Expanding Generative Models and Godel-Tarski-Lob Limits

    Mar 20, 2026Angshul MajumdarGenerative ModelingScaling Laws

    Indraprastha Institute of Information Technology, Delhi

  24. Depictions of Depression in Generative AI Video Models: A Preliminary Study of OpenAI's Sora 2

    Mar 19, 2026Matthew Flathers, Griffin Smith, Julian Herpertz +2Generative ModelingT2V Generation

    Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA · Rhode Island School of Design, Providence, RI, USA · Department of Psychiatry and Neuroscience, Charité Berlin University Medicine, Campus Benjamin Franklin, Berlin, Germany +2

  25. Teaching an Agent to Sketch One Part at a Time

    Mar 19, 2026Xiaodan Du, Ruize Xu, David Yunis +2Generative ModelingLLM Agent Training

    TTI-Chicago · University of Chicago · MIT CSAIL

  26. Foundations of Schrödinger Bridges for Generative Modeling

    Mar 19, 2026Sophia TangSchrödinger BridgesGenerative Modeling

    Department of Computer and Information Science University of Pennsylvania

  27. Seasoning Generative Models for a Generalization Aftertaste

    Mar 19, 2026Hisham Husain, Valentin De Bortoli, Richard NockGenerative ModelingGeneralization Bounds

    Google Research · Google DeepMind

  28. Mathematical Foundations of Deep Learning

    Mar 19, 2026Xiaojing YeNeural Network Approximation TheoryGenerative Modeling

  29. Epistemic Generative Adversarial Networks

    Mar 18, 2026Muhammad Mubashar, Fabio CuzzolinGenerative ModelingGenerative Adversarial Networks

    School of Engineering, Computing and Mathematics, Oxford Brookes University, UK.

  30. The Causal Uncertainty Principle: Manifold Tearing and the Topological Limits of Counterfactual Interventions

    Mar 18, 2026Rui Wu, Hong Xie, Yongjun LiCausal InterventionCausal Inference

    School of Management, University of Science and Technology of China 96 Jinzhai Road, Hefei, 230026, Anhui, China · School of Computer Science and Engineering, University of Science and Technology of China 96 Jinzhai Road, Hefei, 230026, Anhui, China