Synthetic Data Generation

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Overview

Synthetic data generation studies how to create artificial examples that reproduce useful features of real data or provide exact, controllable labels. Common approaches include procedural simulators and domain randomization, generative models such as GANs, variational autoencoders and diffusion models, and large language models or agents that synthesize text, dialogues, and tool-use trajectories. These methods are used to address scarce or sensitive data, cover rare cases, and build controlled training and evaluation sets, with quality often measured by fidelity, privacy, downstream performance, and transfer to real benchmarks. A central open tension is that realism or strong benchmark scores do not guarantee representative, unbiased, causally valid data or reliable performance in real settings.

Latest papers

CardsList

629 papers69 papers in the last four weeks, up 1% on the four weeks before. 0.4% of all new papers.

  1. Tide: A Customisable Dataset Generator for Anti-Money Laundering Research

    Mar 2, 2026Montijn van den Beukel, Jože Martin Rožanec, Ana-Lucia VarbanescuAnti-Money Laundering DetectionSynthetic Data Generation

    University of Amsterdam, The Netherlands · Jožef Stefan Institute, Slovenia · University of Amsterdam/University of Twente, The Netherlands

  2. Autoregressive Synthesis of Sparse and Semi-Structured Mixed-Type Data

    Mar 2, 2026Thomas Rückstieß, Robin VujanicSynthetic Data GenerationAutoregressive Generation

    Independent Researcher, Melbourne, Australia · MongoDB, Sydney, Australia

  3. Data-driven Synthesis of Magnetic Resonance Spectroscopy Data using a Variational Autoencoder

    Feb 28, 2026Dennis M. J. van de Sande, Julian P. Merkofer, Sina Amirrajab +4Magnetic Resonance SpectroscopySynthetic Data Generation

    Department of Biomedical Engineering Eindhoven University of Technology Eindhoven, The Netherlands · Department of Electrical Engineering Eindhoven University of Technology Eindhoven, The Netherlands · Department of Radiology & Nuclear Medicine Maastricht University Medical Center Maastricht, The Netherlands

  4. Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation

    Feb 28, 2026Zeyu Chen, Huanjin Yao, Ziwang Zhao +1LLM EvaluationLLM-as-a-Judge

  5. LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks

    Feb 28, 2026Yucheng Zeng, Weipeng Lu, Linyun Liu +9Synthetic Data Generation for LLM AgentsLLM Agent Trajectory Synthesis

    Baidu Inc. · Tsinghua University

  6. SesaHand: Enhancing 3D Hand Reconstruction via Controllable Generation with Semantic and Structural Alignment

    Feb 28, 2026Zhuoran Zhao, Xianghao Kong, Linlin Yang +33D Hand ReconstructionSynthetic Data Generation

    The Hong Kong University of Science and Technology (Guangzhou) · The Hong Kong University of Science and Technology · Communication University of China

  7. MMKG-RDS: Reasoning Data Synthesis via Deep Mining of Multimodal Knowledge Graphs

    Feb 27, 2026Lun Zhan, Feng Xiong, Huanyong Liu +2Synthetic Data GenerationSynthetic Data Generation for Language Models

    AI Research Institute, Qihoo 360

  8. MAPLE: Metadata Augmented Private Language Evolution

    Feb 26, 2026Eli Chien, Yuzheng Hu, Ryan McKenna +3Privacy-Preserving Language ModelsDifferentially Private Synthetic Data Generation

    National Taiwan University · University of Illinois Urbana-Champaign · Google Research +1

  9. From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models

    Feb 26, 2026Hongrui Jia, Chaoya Jiang, Yongrui Heng +2Multimodal Large Language ModelsContinual Learning for VLMs

    Peking University · Shandong University

  10. DocDjinn: Controllable Synthetic Document Generation with VLMs and Handwriting Diffusion

    Feb 25, 2026Marcel Lamott, Saifullah Saifullah, Nauman Riaz +11Synthetic Data GenerationSynthetic Data Augmentation

    RheinMain University of Applied Sciences, Wiesbaden, Germany · German Research Center for Artificial Intelligence, Kaiserslautern, Germany · DeepReader GmbH, Kaiserslautern, Germany +2

  11. SynthRender and I-AsSET: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception

    Feb 24, 2026Jose Moises Araya-Martinez, Thushar Tom, Adrián Sanchis Reig +3Sim-to-Real TransferSynthetic-to-Real Domain Adaptation

    Technical University Berlin, Industrial Automation Technology, Berlin, Germany · Mercedes-Benz AG, Future Manufacturing Technologies, Sindelfingen, Germany · Technical University Braunschweig, Institute for Cognitive Robotics, Braunschweig, Germany

  12. Object-Scene-Camera Decomposition and Recomposition for Data-Efficient Monocular 3D Object Detection

    Feb 24, 2026Zhaonian Kuang, Rui Ding, Meng Yang +2Monocular 3D Object DetectionData Augmentation

    Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, P.R.China · Intelligent Transportation Thrust of the Systems Hub, Hong Kong University of Science and Technology (GZ), Guangzhou, P.R.China · Amazon Alexa AI, Bellevue, Washington, United States

  13. CaDrift: A Time-dependent Causal Generator of Drifting Data Streams

    Feb 23, 2026Eduardo V. L. Barboza, Jean Paul Barddal, Robert Sabourin +1Synthetic Data GenerationSynthetic Benchmark Generation

    LIVIA, École de Technologie Supérieure (ÉTS), Université du Québec, Montreal, QC, Canada · Graduate Program in Informatics (PPGIa), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, PR, Brazil

  14. When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators

    Feb 23, 2026Krzysztof Adamkiewicz, Brian Bernhard Moser, Stanislav Frolov +3Synthetic-to-Real Domain AdaptationDistribution Shift

    1RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany · 2German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

  15. Multimodal Dataset Distillation Made Simple by Prototype-Guided Data Synthesis

    Feb 23, 2026Junhyeok Choi, Sangwoo Mo, Minwoo ChaeDataset DistillationMultimodal Dataset

    Department of Industrial and Management Engineering, Pohang University of Science and Technology

  16. IDperturb: Enhancing Variation in Synthetic Face Generation via Angular Perturbation

    Feb 21, 2026Fadi Boutros, Eduarda Caldeira, Tahar Chettaoui +1Synthetic Data GenerationFace Recognition

    Fraunhofer Institute for Computer Graphics Research IGD, Germany · TU Darmstadt, Germany

  17. Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code

    Feb 21, 2026Haobo Lin, Tianyi Bai, Chen Chen +4Multimodal ReasoningSynthetic Data Generation

    HKUST · JLU · USTC +1

  18. RadioGen3D: 3D Radio Map Generation via Adversarial Learning on Large-Scale Synthetic Data

    Feb 21, 2026Junshen Chen, Angzi Xu, Zezhong Zhang +3Radio Propagation ModelingSynthetic Data Generation

    School of Science and Engineering (SSE), the Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen), and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, the Chinese University of Hong Kong at Shenzhen, China, 518066 · School of Advanced Engineering, Great Bay University, Dongguan, China, 523000

  19. Subtle Motion Blur Detection and Segmentation from Static Image Artworks

    Feb 21, 2026Ganesh Samarth, Sibendu Paul, Solale Tabarestani +1Image SegmentationImage Quality Assessment

    Amazon Prime Video

  20. Generative Model via Quantile Assignment

    Feb 20, 2026Georgi Hrusanov, Oliver Y. Chén, Julien S. BodeletGenerative ModelingSynthetic Data Generation

    University of Lausanne, Lausanne, Switzerland · Lausanne University Hospital (CHUV), Lausanne, Switzerland · Department of Statistics, Stanford University, Stanford, USA

  21. LAND: A Longitudinal Analysis of Neuromorphic Datasets

    Feb 17, 2026Gregory Cohen, Alexandre MarcireauNeuromorphic ComputingSynthetic Data Evaluation

    International Centre for Neuromorphic Systems (ICNS) Western Sydney University Sydney, Australia · International Centre for Neuromorphic Systems (ICNS) The University of Manchester Manchester, United Kingdom

  22. Developing AI Agents with Simulated Data: Why, what, and how?

    Feb 17, 2026Xiaoran Liu, Istvan DavidSynthetic Data Generation

    McMaster University, Canada · McSCert, McMaster University, Canada

  23. LLM-to-Speech: A Synthetic Data Pipeline for Training Dialectal Text-to-Speech Models

    Feb 17, 2026Ahmed Khaled Khamis, Hesham AliTTS SynthesisLow-Resource TTS Synthesis

    Georgia Institute of Technology · Nile University

  24. Enhancing Diversity and Feasibility: Joint Population Synthesis from Multi-source Data Using Generative Models

    Feb 17, 2026Farbod Abbasi, Zachary Patterson, Bilal FarooqSynthetic Population GenerationData Fusion

    Concordia University, Montreal, QC, Canada · Concordia Institute for Information Systems Engineering, Concordia University, Montreal, QC, Canada · Toronto Metropolitan University, Toronto, ON, Canada

  25. Synthetic Interaction Data for Scalable Personalization in Large Language Models

    Feb 12, 2026Yuchen Ma, Yue Huang, Wenjie Wang +3RL for Language ModelsLLM Personalization

    Munich Center for Machine Learning & LMU Munich · University of Notre Dame · Sichuan University

  26. Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

    Feb 10, 2026Jason Miklian, Kristian Hoelscher, John E. KatsosHuman Behavior SimulationSynthetic Data Generation

    University of Oslo · Peace Research Institute Oslo · American University of Sharjah

  27. PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

    Feb 3, 2026Vignesh Kothapalli, Rishabh Ranjan, Valter Hudovernik +4Relational Foundation ModelsSynthetic Data Pretraining

    1Stanford University · 2Kumo AI · 3SAP Labs LLC

  28. ProofVerifier: A Scalable, Diversity-Driven Framework for Natural-Language Proof Verification

    Feb 2, 2026Haotong Yang, Zitong Wang, Shijia Kang +7Synthetic Data GenerationMathematical Reasoning

    Peking University, Beijing, China · Tencent

  29. Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis

    Jan 31, 2026Zicheng Kong, Dehua Ma, Zhenbo Xu +9Reward ModelingRL for Language Models

    Beijing University of Posts and Telecommunications, Beijing, P.R. China · ShiFang Technology Inc., Hangzhou, P.R. China · Tsinghua University, Beijing, P.R. China +1

  30. FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale

    Jan 29, 2026Ajay Patel, Colin Raffel, Chris Callison-BurchLanguage Model PretrainingSynthetic Data Pretraining

    University of Pennsylvania · University of Toronto · Vector Institute +1