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. 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

  2. Property-Guided Molecular Generation and Optimization via Latent Flows

    Mar 27, 2026Alexander Arjun Lobo, Urvi Awasthi, Leonid ZhukovMolecular GenerationMolecular Optimization

    BCG X AI Science Institute

  3. MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation

    Mar 27, 2026Syed Rameez Naqvi, Lu PengMolecular Graph GenerationQuantum Generative Modeling

    Department of Computer Science, Tulane University, New Orleans, LA, USA.

  4. 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.

  5. Calorimeter Shower Superresolution with Conditional Normalizing Flows: Implementation and Statistical Evaluation

    Mar 26, 2026Andrea CossoHigh-Energy PhysicsImage Super-Resolution

    Università degli Studi di Genova Scuola di Scienze Matematiche, Fisiche e Naturali Laurea Magistrale in Fisica

  6. ORACLE: Orchestrate NPC Daily Activities using Contrastive Learning with Transformer-CVAE

    Mar 25, 2026Seong-Eun Hong, JuYeong Hwang, RyunHa Lee +1Conditional Generative Modeling

    Korea University, Seoul, South Korea

  7. SM-Net: Learning a Continuous Spectral Manifold from Multiple Stellar Libraries

    Mar 25, 2026Omar Anwar, Aaron S. G. Robotham, Luca Cortese +1AstrophysicsNeural Surrogate Modeling

    International Centre for Radio Astronomy Research (ICRAR) The University of Western Australia (UWA), 35 Stirling Hwy, Crawley WA 6009, Australia

  8. Generative Inversion of Spectroscopic Data for Amorphous Structure Elucidation

    Mar 24, 2026Jiawei Guo, Daniel Schwalbe-KodaMaterials ScienceConditional Generative Modeling

    Department of Materials Science and Engineering, University of California, Los Angeles, CA, USA

  9. Conditioning Protein Generation via Hopfield Pattern Multiplicity

    Mar 20, 2026Jeffrey D. VarnerConditional Generative ModelingConditional Generation

    Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell University, Ithaca, NY 14850

  10. Graph2TS: Structure-Controlled Time Series Generation via Quantile-Graph VAEs

    Mar 20, 2026Shaoshuai Du, Joze M. Rozanec, Andy Pimentel +1Time Series GenerationConditional Generative Modeling

    Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands · Computer Architecture for Embedded Systems, University of Twente, Enschede, The Netherlands · Laboratory of Artificial Intelligence, Institute Jozef Stedan, Ljubljana, Slovenia

  11. Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression Generation from Histology Images

    Mar 20, 2026Donghai Fang, Yongheng Li, Zhen Wang +2Gene Expression Prediction from Histopathology ImagesSpatial Transcriptomics

    Sun Yat-sen University, China · Yunnan University, China · Chongqing University, China

  12. Conditional Rectified Flow-based End-to-End Rapid Seismic Inversion Method

    Mar 16, 2026Haofei Xu, Wei Cheng, Sizhe Li +1Inverse ProblemsConditional Generative Modeling

    School of Electronic lnformation and Electrical Engineering, Yangtze UniversityJingzhou, Hubei 434023, PR.China

  13. PGcGAN: Pathological Gait-Conditioned GAN for Human Gait Synthesis

    Mar 15, 2026Mritula Chandrasekaran, Sanket Kachole, Jarek Francik +1Human Motion GenerationGait Analysis

    Kingston University, Kingston Upon Thames, London, UK · Indiana University Health, Indianapolis, Indiana

  14. AS-Bridge: A Bidirectional Generative Framework Bridging Next-Generation Astronomical Surveys

    Mar 12, 2026Dichang Zhang, Yixuan Shao, Simon Birrer +1Conditional Generative ModelingImage-to-Image Translation

    Stony Brook University, Stony Brook, NY, USA

  15. Deep Generative Transformers for Probabilistic Time Series and Spatiotemporal Forecasting

    Mar 12, 2026Rajdeep Pathak, Rahul Goswami, Madhurima Panja +2Probabilistic Time Series ForecastingMultivariate Time Series Forecasting

    SAFIR, Sorbonne University Abu Dhabi, United Arab Emirates. · SCAI, Sorbonne Universit´e, Paris, France. · Indian Institute of Technology Guwahati, Assam, India.

  16. Gen-Fab: A Variation-Aware Generative Model for Predicting Fabrication Variations in Nanophotonic Devices

    Mar 12, 2026Rambod Azimi, Yuri Grinberg, Dan-Xia Xu +1ManufacturingDigital Twins

    Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada. · Digital Technologies Research Center, National Research Council of Canada, Ottawa, ON, Canada. · Quantum and Nanotechnologies Research Center, National Research Council of Canada, Ottawa, ON, Canada.

  17. SNPgen: Phenotype-Supervised Genotype Representation and Synthetic Data Generation via Latent Diffusion

    Mar 11, 2026Andrea Lampis, Michela Carlotta Massi, Nicola Pirastu +3Synthetic Data GenerationGenomics

    DEIB, Politecnico di Milano, Milan 20133, Italy · Health Data Science Centre, Human Technopole, Milan 20157, Italy · Genomics Research Centre, Human Technopole, Milan 20157, Italy +2

  18. ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning

    Mar 11, 2026Xiaofeng Lin, Seungbae Kim, Zhuoya Li +3Synthetic Tabular Data GenerationTabular Data Synthesis

    University of California, Los Angeles, USA · University of South Florida, USA · Cisco, USA +1

  19. Generative Adversarial Regression (GAR): Learning Conditional Risk Scenarios

    Mar 9, 2026Saeed Asadi, Jonathan Yu-Meng LiAdversarial Scenario GenerationConditional Generative Modeling

    Telfer School of Management University of Ottawa

  20. Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma

    Mar 9, 2026Selena Huisman, Nordin Belkacemi, Vera C. Keil +2Medical Image SynthesisConditional Generative Modeling

    Amsterdam UMC, Department of Radiation Oncology, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands · Cancer Center Amsterdam, Imaging and Biomarkers, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands · Department of Radiology and Nuclear Medicine, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands +1

  21. PureCC: Pure Learning for Text-to-Image Concept Customization

    Mar 8, 2026Zhichao Liao, Xiaole Xian, Qingyu Li +7Subject-Driven Image GenerationDiffusion Model Fine-Tuning

    Tsinghua University · School of Computer Science & Software Engineering, Shenzhen University · Kling Team, Kuaishou Technology +3

  22. Variational Flow Maps: Make Some Noise for One-Step Conditional Generation

    Mar 7, 2026Abbas Mammadov, So Takao, Bohan Chen +4Conditional Generative ModelingOne-Step Generative Modeling

    Department of Statistics, University of Oxford · California Institute of Technology · University of Toronto +1

  23. Conditional Unbalanced Optimal Transport Maps: An Outlier-Robust Framework for Conditional Generative Modeling

    Mar 7, 2026Jiwoo Yoon, Kyumin Choi, Jaewoong ChoiOptimal TransportConditional Generative Modeling

    Department of Statistics, Sungkyunkwan University · Department of Applied Artificial Intelligence, Sungkyunkwan University

  24. Stochastic Attention via Langevin Dynamics on the Modern Hopfield Energy

    Mar 6, 2026Abdulrahman Alswaidan, Jeffrey D. VarnerHopfield NetworksEnergy-Based Models

    R.F. Smith School of Chemical and Biomolecular Engineering Cornell University, Ithaca, NY 14850

  25. Learning Adaptive and Visually Aligned Conditions for Generative Zero-Shot Learning

    Mar 6, 2026Haojie Pu, Zhuoming Li, Yongbiao Gao +3Zero-Shot LearningVision-Language Alignment

    School of Computer Science and Engineering, Southeast University, Nanjing, China

  26. Longitudinal NSCLC Treatment Progression via Multimodal Generative Models

    Mar 6, 2026Massimiliano Mantegna, Elena Mulero Ayllón, Alice Natalina Caragliano +10Medical Image SynthesisLongitudinal Medical Image Analysis

    Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma, Italy · Multi-Specialist Clinical Institute for Orthopaedic Trauma Care (COT), Messina, Italy · Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Sweden +4

  27. Semi-Supervised Generative Learning via Latent Space Distribution Matching

    Mar 4, 2026Kwong Yu Chong, Long FengConditional Generative ModelingSemi-Supervised Learning

    School of Computing & Data Science, University of Hong Kong

  28. Lang2Str: Two-Stage Crystal Structure Generation with LLMs and Continuous Flow Models

    Mar 4, 2026Cong Liu, Chengyue Gong, Zhenyu Liu +2Crystal Structure GenerationComputational Materials Science

    AMLab, AI4Science Lab University of Amsterdam

  29. Controllable Generative Sandbox for Causal Inference

    Mar 3, 2026Qi Zhang, Harsh Parikh, Ashley Naimi +3Synthetic Data GenerationCausal Inference

    Emory University · Yale University · Amgen

  30. Learning Demographic-Conditioned Mobility Trajectories with Aggregate Supervision

    Mar 3, 2026Jessie Z. Li, Zhiqing Hong, Toru Shirakawa +1Trajectory GenerationConditional Generative Modeling

    University of California, Berkeley · Hong Kong University of Science and Technology (Guangzhou)