Conditional Generative Modeling

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Overview

Conditional generative modeling studies how to generate plausible data given information such as labels, text, images, measurements, or physical parameters. Common approaches include conditional GANs and VAEs, normalizing flows, diffusion and score-based models, flow matching, and autoregressive or masked models. These methods support tasks such as image reconstruction, time-series forecasting, molecular design, and scientific inverse problems, where many possible outputs may fit the same input. A central challenge is balancing fidelity to the condition and output diversity with fast sampling, reliable uncertainty, and generalization to unseen conditions.

Latest papers

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393 papers53 papers in the last four weeks, up 39% on the four weeks before. 0.3% of all new papers.

  1. TacticGen: Grounding Adaptable and Scalable Generation of Football Tactics

    Apr 20, 2026Sheng Xu, Guiliang Liu, Tarak Kharrat +12Conditional Generative ModelingSoccer Analytics

    School of Data Science, The Chinese University of Hong Kong, Shenzhen, China · Real Analytics, London, UK · Birmingham City Football Club, Birmingham, UK +3

  2. A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations

    Apr 19, 2026Marcin Kostrzewa, Maciej Zięba, Jerzy StefanowskiCounterfactual ExplanationsConditional Generative Modeling

    Wrocław University of Science and Technology, Wrocław 50-347, Poland · Tooploox, Wrocław 53-601, Poland · Poznań University of Technology, Poznań 61-131, Poland

  3. SAVE: A Generalizable Framework for Multi-Condition Single-Cell Generation with Gene Block Attention

    Apr 18, 2026Jiahao Li, Jiayi Dong, Peng Ye +3Single-Cell Perturbation ModelingConditional Generative Modeling

    College of Computer Science and Artificial Intelligence, Fudan University · Shanghai Key Laboratory of Intelligent Information Processing, Fudan University

  4. Global Attention with Linear Complexity for Exascale Generative Data Assimilation in Earth System Prediction

    Apr 17, 2026Xiao Wang, Zezhong Zhang, Isaac Lyngaas +10Climate ScienceHigh-Performance Computing

    Oak Ridge National Laboratory, Oak Ridge, TN, USA · Auburn University, Auburn, AL, USA · Florida State University, Tallahassee, FL, USA +2

  5. Synthetic data in cryptocurrencies using generative models

    Apr 17, 2026André Saimon S. Sousa, Otto Pires, Frank Acasiete +3Synthetic Data GenerationTime Series Generation

    Universidade SENAI CIMATEC Salvador, Brazil · CoFi, Universidad Jorge Tadeo Lozano Bogotá, Colombia · Universidade do Estado da Bahia - UNEB Salvador, Brazil

  6. Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction

    Apr 17, 2026Jingyuan Li, Xiaoyi Jiang, Fukang Wen +5Markov ModelsDiffusion Language Models

    2Beijing Institute of Mathematical Sciences and Applications · 3Wuhan University · 4MathonAI +1

  7. DALM: A Domain-Algebraic Language Model via Three-Phase Structured Generation

    Apr 17, 2026Chao LiConstrained Generative ModelingKnowledge Conflicts in Language Models

  8. DRG-Font: Dynamic Reference-Guided Few-shot Font Generation via Contrastive Style-Content Disentanglement

    Apr 15, 2026Rejoy Chakraborty, Prasun Roy, Saumik Bhattacharya +1Few-Shot LearningConditional Generative Modeling

    Indian Statistical Institute Kolkata · Indian Institute of Technology Kharagpur

  9. EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

    Apr 15, 2026Boxuan Jiang, Chenyun Dai, Can HanSynthetic Data AugmentationConditional Generative Modeling

    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

  10. Polyformer: a generative framework for thermodynamic modeling of polymeric molecules

    Apr 15, 2026Alessio Valentini, David Pekker, Chungwen Liang +2Protein Structure GenerationProtein Structure Prediction

    PsiDagger, San Diego, CA · Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA · Department of Chemistry and The PULSE Institute, Stanford University, Stanford, CA +1

  11. Conflated Inverse Modeling to Generate Diverse and Temperature-Change Inducing Urban Vegetation Patterns

    Apr 14, 2026Baris Sarper Tezcan, Hrishikesh Viswanath, Rubab Saher +1Inverse DesignConstrained Generative Modeling

    Computer Science Purdue University, West Lafayette, IN, USA · Forestry and Natural Resources Purdue University, West Lafayette, IN, USA

  12. AbdomenGen: Sequential Volume-Conditioned Diffusion Framework for Abdominal Anatomy Generation

    Apr 14, 2026Yubraj Bhandari, Lavsen Dahal, Paul Segars +1Medical Image SynthesisControllable Image Generation

    Center for Virtual Imaging Trials, Dept. of Radiology, Duke University School of Medicine · Dept. of Physics, Trinity School of Arts and Sciences, Duke University · Dept. of Electrical and Computer Engineering, Pratt School of Engineering, Duke University

  13. SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation

    Apr 14, 2026Yexiong Lin, Jia Shi, Shanshan Ye +3Flow MatchingFlow-Based Generative Modeling

    Sydney AI Centre, The University of Sydney, Sydney, NSW, Australia · School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China · Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, NSW, Australia +1

  14. Beyond Sequential Prediction: Learning Financial Market Dynamics in Volatile and Non-Stationary Environments through Sentiment-Conditioned Generative Modelling

    Apr 13, 2026Alexis Lazanas, Spyridon KarpouzisTime Series ForecastingNon-Stationary Time Series Forecasting

    Department of Mechanical Engineering and Aeronautics, University of Patras, Rion-Patras, Greece · FICC Market Risk, BNP Paribas CIB, London, United Kingdom

  15. Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching

    Apr 13, 2026Nicole Rogalla, Yuzhen Qin, Mario Senden +2Functional Magnetic Resonance ImagingProbabilistic Time Series Forecasting

    Department of Machine Learning and Neural Computing, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands · Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands · Maastricht Brain Imaging Center, Maastricht University, Maastricht, the Netherlands

  16. GIF: A Conditional Multimodal Generative Framework for IR Drop Imaging in Chip Layouts

    Apr 11, 2026Kiran Thorat, Nicole Meng, Mostafa Karami +3Electronic Design AutomationConditional Generative Modeling

    University of Connecticut, USA · Tufts University, USA · University of Minnesota Twin Cities, USA

  17. HAFM: Hierarchical Autoregressive Foundation Model for Music Accompaniment Generation

    Apr 10, 2026Jian Zhu, Jianwei Cui, Yunlong Xue +4Controllable Music GenerationMusic Generation

    Zhejiang Lab · University of Science and Technology of China · Zhejiang International Studies University

  18. Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics

    Apr 9, 2026Ying Shen, Jerry Xiong, Tianjiao Yu +1Physical Consistency in Video GenerationPhysics-Informed Generative Modeling

    University of Illinois Urbana-Champaign

  19. Exploring Temporal Representation in Neural Processes for Multimodal Action Prediction

    Apr 9, 2026Marco Gabriele Fedozzi, Yukie Nagai, Francesco Rea +1Temporal Representation LearningRobotics

    DIBRIS Department, University of Genoa, Via All’Opera Pia 13 16145 Genoa, Italy · CONTACT Unit, Italian Institute of Technology, Via Enrico Melen 83, 16152 Genoa, Italy · International Research Center for Neurointelligence, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

  20. Unified Vector Floorplan Generation via Markup Representation

    Apr 6, 2026Kaede Shiohara, Toshihiko YamasakiFloor Plan GenerationConditional Generative Modeling

    The University of Tokyo

  21. CPT: Controllable and Editable Design Variations with Language Models

    Apr 6, 2026Karthik Suresh, Amine Ben Khalifa, Li Zhang +4Conditional Generative Modeling

    Adobe · Atta

  22. Conditional Sampling via Wasserstein Autoencoders and Triangular Transport

    Apr 3, 2026Mohammad Al-Jarrah, Michele Martino, Marcus Yim +2Conditional Generative ModelingOptimal Transport

    Department of Aeronautics & Astronautics, University of Washington, Seattle · Department of Applied Mathematics, University of Washington, Seattle · Department of Mathematics, University of Washington, Seattle

  23. BoundInk: Boundary-Aware Online Handwriting Generation

    Apr 2, 2026Jinsu Shin, Sungeun Hong, JinYeong BakConditional Generative Modeling

    Sungkyunkwan University, Suwon, Korea

  24. Multi-Mode Quantum Annealing for Generative Representation Learning with Boltzmann Priors

    Apr 1, 2026Gilhan Kim, Daniel K. ParkQuantum Generative ModelingVariational Autoencoders

    Department of Statistics and Data Science, Yonsei University, Seoul 03722, Republic of Korea · Department of Applied Statistics, Yonsei University, Seoul 03722, Republic of Korea · Department of Quantum Information, Yonsei University, Seoul 03722, Republic of Korea

  25. SAGE: Subsurface AI-driven Geostatistical Extraction with proxy posterior

    Mar 31, 2026Huseyin Tuna Erdinc, Ipsita Bhar, Rafael Orozco +2SeismologyConditional Generative Modeling

    Georgia Institute of Technology · Oxy · Huber Engineered Materials

  26. 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

  27. Generating Key Postures of Bharatanatyam Adavus with Pose Estimation

    Mar 31, 2026Jagadish Kashinath Kamble, Jayanta Mukhopadhyay, Debaditya Roy +1Human Motion GenerationConditional Generative Modeling

    Indian Institute of Technology Kharagpur, West Bengal, INDIA · Ashoka University Sonipat, Haryana, INDIA

  28. Capturing Multivariate Dependencies of EV Charging Events: From Parametric Copulas to Neural Density Estimation

    Mar 31, 2026Martin Výboh, Gabriela GrmanováElectric Vehicle ChargingCopula Models

    Kempelen Institute of Intelligent Technologies, Bratislava, Slovakia

  29. LDDMM stochastic interpolants: an application to domain uncertainty quantification in hemodynamics

    Mar 30, 2026Sarah Katz, Francesco Romor, Jia-Jie Zhu +13D Shape GenerationConditional Generative Modeling

    WIAS, Weierstrass Institute for Applied Analysis and Stochastics, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Germany. · KTH Royal Institute of Technology, Lindstedtsvägen 25, 114 28 Stockholm, Sweden.

  30. FluidFlow: a flow-matching generative model for fluid dynamics surrogates on unstructured meshes

    Mar 30, 2026David Ramos, Lucas Lacasa, Fermín Gutiérrez +2PDE Surrogate ModelingComputational Fluid Dynamics

    ETSIAE-UPM-School of Aeronautics, Universidad Politécnica de Madrid, Plaza Cardenal Cisneros 3, E-28040 Madrid, Spain · Institute for Cross-Disciplinary Physics and Complex Systems (IFISC, CSIC-UIB), 07122 Palma de Mallorca (Spain) · Center for Computational Simulation, Universidad Politécnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28660 Madrid, Spain