Synthetic Data Evaluation

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22 papers in the last four weeks, up 100% on the four weeks before. 0.2% of all new papers.

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A Filtered Mixture-of-Generators for Fully Synthetic Survival Training
Jun 30, 2026Niccolò Maria Rizzi, Eugenio Lomurno, Alberto Archetti +1Survival Analysis Synthetic Data Generation
Politecnico di Milano, Milan, Italy
Towards Inclusive Mobility Modeling: Characterizing and Evaluating Elderly Trajectory Patterns in Urban Systems
Jun 30, 2026Zhengxuan Wang, Haohan He, Mengying ZhouSynthetic Data Evaluation
School of Computing and Artificial Intelligence, Shanghai University of Finance and Economics, Shanghai, China · MOE Key Laboratory of Interdisciplinary Research of Computation and Economics, Shanghai University of Finance and Economics, Shanghai, China · Center for Data Science, New York University, New York, USA
Towards Evaluating Data Priors for Tabular Foundation Models
Jun 28, 2026Zeynep Türkmen, Kürşat Kaya, Alexander Pfefferle +1Tabular Foundation Models Synthetic Data Evaluation
Department of Computer Science, University of Freiburg, Freiburg, Germany · Zuse School ELIZA, Hochschulstr. 10, 64289 Darmstadt · Prior Labs, Freiburg, Germany +1
A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation
Jun 27, 2026Xuanting Wu, Fan Zhanga, Fei Ma +3Synthetic Data Augmentation Data Augmentation
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China · Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, Beijing, 100854, China
ProfileFoundry: A Synthetic Person-Object Substrate for Privacy, Memory, and Tool-Use Evaluation in LLM Agent
Jun 24, 2026Sriram Selvam, Anneswa GhoshSynthetic Data Generation Synthetic Benchmark Generation
ERP Data Provisioning Financial Control Testing
Jun 23, 2026Anitha SamudralaSynthetic Tabular Data Generation Synthetic Data Evaluation
AMAZON CORPORATION
Benchmarking the Alignment of Data-Quality Metrics, Human Judgment and Land-Cover Segmentation Performance for Earth Observation
Jun 23, 2026Ümit Mert Çağlar, Alptekin TemizelSynthetic Data Augmentation Remote Sensing Image Segmentation
Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
Generating Public Health Responses using Survey-Augmented Large Language Models
Jun 20, 2026Leonardo Marciaga, Thuyen Pham, Julia Rezvani +4Synthetic Data Augmentation Synthetic Data Generation
Illinois Institute of Technology · University of Massachusetts Amherst · Portland State University +4
Understanding Latent Flow Models for Tabular Data Synthesis: Targets, Paths, and Sampling
Jun 18, 2026Bahrul Ilmi NasutionSynthetic Tabular Data Generation Continuous Normalizing Flows
Department of Social Statistics, The University of Manchester, UK
Training-Free Metrics for Synthetic Object Detection Data: A Proxy for Detector Performance
Jun 18, 2026Myeongseok Nam, Donghun Yeo, Seungwook KimDistribution Matching Object Detection
GenGenAI, South Korea
Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets?
Jun 16, 2026Trisha Mittal, Akshay Mehra, Joshua KimballTraining Data Selection Dataset Distillation
1Dolby Laboratory
Phantoms and Disclosures: a Causal Framework for Auditing Synthetic Data
Jun 15, 2026Kareem Amin, Rudrajit Das, Alessandro Epasto +4Privacy Auditing Membership Inference Attacks
1Google · University of Southern California
Not all Jensen-Shannon Divergence Estimators are Equal
Jun 15, 2026Alba Garrido, Alejandro Almodóvar, Mar Elizo +3Synthetic Data Evaluation
Information Processing and Telecommunications Center, ETSI Telecomunicación, Universidad Politécnica de Madrid, Spain
Causal-Privacy Audit Workflow for Synthetic and Distilled Data in Dropout Support
Jun 14, 2026Hanghang Zheng, Xiwei Zhuang, Zhong Wang +4Privacy Auditing Causal Effect Estimation
Central University of Finance and Economics, Beijing, PR China · China Development Bank, Beijing, PR China
Valid Inference with Synthetic Data via Task Exchangeability
Jun 11, 2026Lezhi Tan, Tijana ZrnicSynthetic Data Evaluation
Department of Management Science & Engineering Stanford University · Department of Statistics Stanford University
Provenance-Grounded Gating and Adaptive Recovery in Synthetic Post-Training Data Curation
Jun 9, 2026Soham Bhattacharjee, Karun Sharma, Vinay Kumar Sankarapu +1Adaptive Sampling LLM Post-Training
Lexsi Labs
RealMath-Eval: Why SOTA Judges Struggle with Real Human Reasoning
Jun 8, 2026Yiteng Mao, Kenan Xu, Yijia Lyu +3Mathematical Reasoning Benchmarks LLM Evaluation
University of Wisconsin–Madison · East China Normal University · New York University +2
Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records
Jun 8, 2026Nicholas I-Hsien Kuo, Blanca Gallego, Louisa JormSynthetic Tabular Data Generation Electronic Health Records
Centre for Big Data Research in Health, the University of New South Wales, Sydney, Australia
Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining
Jun 6, 2026Aaryan Nagpal, Debdeep Sanyal, Murari Mandal +2Synthetic Data Pretraining Time Series Forecasting
Birla AI Labs, Mumbai, India · KIIT, Bhubaneswar, India · BITS Pilani, Pilani, India
The CIFAR Synthetic Evidence Corpus for Detecting AI-Generated Evidence
Jun 6, 2026Kelly McConvey, Jalehsadat Mahdavimoghaddam, Nima Jamali +8Digital Forensics Synthetic Benchmark Generation
University of Toronto · University of Waterloo · University of British Columbia +2
Beyond Individual Personas: Aligning Synthetic Dialogue to Population-Level Behavior Distributions
Jun 5, 2026Xinyi Liu, Rinat Khaziev, Hooshang Nayyeri +3Synthetic Data Generation Persona-Conditioned Generation
1Amazon · University of Illinois Urbana–Champaign · University College London
A Framework for Evaluating and Benchmarking Concept Drift Detection Methods
Jun 5, 2026Vitor Cerqueira, Heitor Murilo Gomes, Marco Heyden +2Concept Drift Synthetic Benchmark Generation
University of Coimbra · Victoria University of Wellington · Commerzbank +2
Impact of Synthetic Lesional MR Images in Automated Focal Cortical Dysplasia Detection in Low-Data Scenarios
Jun 5, 2026Prabhjot Kaur, Hakim Ouaalam, Sedat Kandemirli +2Synthetic Data Augmentation Medical Image Anomaly Detection
Computational Radiology Laboratory, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
Accelerating Reproducible Research in Synthetic EHR Generation
Jun 5, 2026Jalen Jiang, Chufan Gao, Ethan Rasmussen +2Synthetic Data Generation ML Reproducibility
University of Illinois Urbana-Champaign
From Vision to Text: A Compact Multimodal Approach for Robust, Cross-Domain Presentation Attack Detection on ID Cards
Jun 5, 2026Qingwen Zeng, Juan E. Tapia, Sneha Das +1Multimodal Robustness Domain Generalization
Technical University of Denmark (DTU), Denmark · da/sec-Biometrics and Security Research Group, Hochschule Darmstadt, Germany
An Expanded Synthetic Conversation Dataset for Multi-Turn Smishing Detection
Jun 5, 2026Carl Lochstampfor, Ayan RoyTransformer Synthetic Data Generation
Department of Computer Science Old Dominion University Norfolk, VA, USA · Department of Computer Science Christopher Newport University Newport News, VA, USA
Synthics: Synthetic Physics-like Datasets for Machine Learning
Jun 4, 2026Jari VepsäläinenSynthetic Data Generation Scientific ML
Mechatronics Department of Energy and Mechanical Engineering School of Engineering Aalto University Finland
Re-Centering Humans in LLM Personalization
Jun 4, 2026Lechen Zhang, Jiarui Liu, Tal AugustHuman Preference Evaluation LLM Evaluation
†University of Illinois Urbana-Champaign · ♯Carnegie Mellon University
Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
Jun 1, 2026Xinqi Bao, Jia Bi, Xin Chen +2Audio Diffusion Models Conditional Diffusion Models
Department of Information Science & Engineering, KTH Royal Institute of Technology, Stockholm, 114 28 Sweden · Karolinska Institutet (KI), Stockholm, Sweden · Rutherford Appleton Laboratory, United Kingdom +2
No Free Lunch for Synthetic Images under Data Scarcity Conditions
Jun 1, 2026Borja Arroyo Galende, Alejandro Almodóvar, Patricia A. Apellániz +3Synthetic Data Generation Generative Modeling
Information Processing and Telecommunications Center, Escuela Técnica Superior de Ingeniería de Telecomunicación, Universidad Politécnica de Madrid, Madrid, 28030, Spain · Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid, 28030, Spain
Train, Test, Re-evaluate: Schedule-Sensitive Evaluation of Generative Data for Hand Detection
Jun 1, 2026Atmika Bhardwaj, Silvia Vock, Nico SteckhanSynthetic-to-Real Domain Adaptation Synthetic Data Augmentation
Federal Institute for Occupational Safety and Health (BAuA), Germany
ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?
Jun 1, 2026Peihan Liu, Lucas Rosenblatt, Weiwei Kong +7Privacy-Preserving Language Models Synthetic Benchmark Generation
Columbia University · Work done as a Student Researcher at Google · NYU +4
LLM-as-a-Discriminator: When Synthetic Tables Still Look Real
Jun 1, 2026Manel Slokom, Malek Slokom, Thierno KantePrivacy Auditing Tabular Data Synthesis
Vrije Universiteit, Amsterdam · Equativ, Paris · EDICIA, Nantes
Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection
May 27, 2026Vijeta Deshpande, Tootiya Giyahchi, Veena Padmanabhan +2Synthetic Data Generation Synthetic Data Generation for Language Models
UMass Lowell · Amazon · Amazon, CMU +1
A Controlled Synthetic Benchmark for Educational Aspect-Based Sentiment Analysis
May 25, 2026Yehudit Aperstein, Alexander ApartsinEducational Technology Synthetic Benchmark Generation
Intelligent Systems, Afeka Academic College of Engineering, Tel Aviv, Israel · School of Computer Science, Faculty of Sciences, Holon Institute of Technology, Holon, Israel
When Does Synthetic Patent Data Help? Volume-Fidelity Trade-offs in Low-Resource Multi-Label Classification
May 22, 2026Amirhossein Yousefiramandi, Ciaran CooneySynthetic Data Augmentation Multi-Label Classification
Clarivate, Intellectual Property · Barcelona, Spain 08025
AvalancheBench: Evaluating Enterprise Data Agents Through Latent World Recovery
May 22, 2026Darek Kleczek, Fuheng Zhao, Alexander W. Lee +4AI Agent Evaluation AI Agent Benchmarks
Snowflake · Brown University and Snowflake
Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025
May 21, 2026José Rafael Noriega CedeñoSynthetic Data Augmentation Medical Image Classification
Faculty of Applied Sciences and Technology
SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations
May 21, 2026Shuaiqi Wang, Aadyaa Maddi, Zinan Lin +1Tool-Use Evaluation LLM Agent Evaluation
Carnegie Mellon University · Microsoft Research
SADGE: Structure and Appearance Domain Gap Estimation of Synthetic and Real Data
May 21, 2026Patryk Bartkowiak, Bartosz Kotrys, Dominik Michels +2Domain Adaptation Sim-to-Real Transfer
Adam Mickiewicz University · ArtCollect · KAUST +1
Making the Discrete Continuous: Synthetic RAW Augmentations for Fine-Grained Evaluation of Person Detection Performance in Low Light
May 21, 2026Valeria Pais, Malena Mendilaharzu, Daniele Faccio +3Synthetic Data Augmentation Autonomous Driving Perception
University of Glasgow · Chapel Ln, Glasgow G11 6EW, UK · Dotphoton +2
HyperBench: Standardizing and Scaling Synthetic Evaluation for Hyperspectral Super-Resolution
May 20, 2026Ritik Shah, Marco F. DuarteBenchmark Design Remote Sensing Image Super-Resolution
University of Massachusetts Amherst, MA 01003
Physics-informed simulation framework for realistic sonar image generation and statistical validation
May 19, 2026Kamal Basha S, Athira NambiarUnderwater Imaging Synthetic Data Generation
Department of Computational Intelligence, SRM Institute of Science and Technology, Chennai, India
What Makes Synthetic Data Effective in Image Segmentation
May 19, 2026Jinjin Zhang, Xiefan Guo, Yizhou Jin +2Synthetic Data Augmentation Image Segmentation
State Key Laboratory of Complex and Critical Software Environment, Beihang University, Beijing 100191, China · School of Computer Science and Engineering, Beihang University, Beijing 100191, China
Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note Scale
May 18, 2026Jinghui Liu, Sarvesh Soni, Anthony NguyenSynthetic Data Augmentation Automated Medical Coding
Australian e-Health Research Centre, CSIRO, Australia · National Library of Medicine, National Institutes of Health, USA
Memisis: Orchestrating and Evaluating Synthetic Data for Tabular Health Datasets
May 18, 2026Nitish Nagesh, Pengbao Zhou, Atchuth Naveen Chilaparasetti +8Healthcare Synthetic Tabular Data Generation
University of California, Irvine, CA, USA · PathAI, USA
TextClusterLab: An Integrated Framework for Reliable Text Clustering Studies
May 17, 2026Daoming Wan, Yizheng Huang, Jimmy X. HuangClustering Synthetic Data Generation
Information Retrieval and Knowledge Management Research Lab, York University Toronto, Ontario, Canada
CasualSynth: Generating Structurally Sound Synthetic Data
May 17, 2026Zehua Cheng, Wei Dai, Jiahao Sun +1Structural Causal Models Synthetic Data Generation
Department of Computer Science, University of Oxford · FLock.io United Kingdom · Institute of Logic and Computation, TU Wien
On Applicability of Synthetic Datasets for Facial Expression Recognition
May 17, 2026Ali Azmoudeh, Erdi Sarıtaş, Ömer Yıldırım +1Class-Imbalanced Learning Synthetic Data Generation
Department of Computer Engineering, Istanbul Technical University, Istanbul, Türkiye · Department of Informatics, University of Zurich, Zurich, Switzerland · Division of Engineering, NYU Abu Dhabi, Abu Dhabi, UAE
Marginal Alignment Does Not Guarantee Joint-Distribution Fidelity: An Official-Reference Audit of Nemotron-Personas-Korea with Cross-Locale Replication
May 15, 2026Joonhyung BaeDistribution Matching Synthetic Data Evaluation
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
ReMIA: a Powerful and Efficient Alternative to Membership Inference Attacks against Synthetic Data Generators
May 14, 2026Davide Scassola, Andrea Coser, Sebastiano SaccaniMembership Inference Attacks Synthetic Tabular Data Generation
Aindo SpA Trieste, Italy
How to Evaluate and Refine your CAM
May 14, 2026Luca Domeniconi, Alessandra Stramiglio, Michele Lombardi +1Feature Attribution Explainability Evaluation
University of Bologna, Bologna, Italy
NodeSynth: Socially Aligned Synthetic Data for AI Evaluation
May 14, 2026Qazi Mamunur Rashid, Xuan Yang, Zhengzhe Yang +5Language Model Generation Evaluation Language Model Safety Evaluation
Google Research · Google · Google Deepmind
Template-as-Ontology: Configurable Synthetic Data Infrastructure for Cross-Domain Manufacturing AI Validation
May 11, 2026Grama ChethanManufacturing Synthetic Data Generation
Siemens Digital Industries Software, Plano, TX 75024, United States
Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation
May 11, 2026George PanagopoulosCounterfactual Evaluation Causal Effect Estimation
Department of Computer Science University of Luxembourg 2 Av. de l’Universite, 4365 Belval Esch-sur-Alzette
Generating synthetic electronic health record data using agent-based models to evaluate machine learning robustness under mass casualty incidents
May 11, 2026Roben Delos Reyes, Daniel Capurro, Nicholas GeardDistribution Shift Robustness Synthetic Data Generation
School of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, Australia · Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
Discriminative Span as a Predictor of Synthetic Data Utility via Classifier Reconstruction
May 10, 2026Radhika Amar Desai, Modigari NarendraSynthetic Data Augmentation Binary Classification
School Of Computer Science Vellore Institute of Technology Chennai
On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
May 7, 2026Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy +5Data Leakage Membership Inference Attacks
Vector Institute · McMaster University · University of Toronto +1
Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Models
May 7, 2026Alex O. Davies, Telmo de Menezes e Silva Filho, Nirav AjmeriSynthetic Data Pretraining Synthetic-to-Real Domain Adaptation
School of Geographical Sciences University of Bristol, UK · School of Engineering Mathematics and Technology University of Bristol, UK · School of Computer Science University of Bristol, UK
Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters
May 7, 2026Hugo Cazaux, Eyjólfur Ingi Ásgeirsson, Hlynur StefánssonSynthetic Data Augmentation Synthetic Data Generation
Department of Engineering Reykjavík University Iceland, Menntavegur 1, 102

Jun 30, 2026, cs.LGJ/K move · Enter open · S save

A Filtered Mixture-of-Generators for Fully Synthetic Survival Training

Niccolò Maria Rizzi, Eugenio Lomurno, Alberto Archetti, Matteo Matteucci

Politecnico di Milano, Milan, Italy

Survival Analysis Synthetic Data Generation Synthetic Data Evaluation Synthetic Data Selection

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Survival analysis models time-to-event data, but in clinical settings training data are costly and scarce: events accrue over years of follow-up, cohorts are small, and privacy regulations restrict sharing across institutions. Tabular generative models promise augmentation and privacy-preserving cohort sharing, yet are themselves data-hungry -- on the small cohorts typical of survival analysis, a single generator rarely characterizes the population well enough for downstream models trained on its output to match real-data performance. FoGS (Filtered Mixture-of-Generators for Survival analysis) reframes synthetic-data construction as sample selection rather than generation. A candidate pool is drawn from four architecturally distinct tabular generators, and each sample is scored by an ensemble of seven survival models trained on real data, using proper scoring rules as a per-sample plausibility proxy. A two-level pipeline optimizes, in its outer loop, a selection policy -- generator quotas, scorer weights, a random complement, and stratified balancing on event time and censoring -- against held-out downstream performance, while an inner loop tunes the downstream model (XGBoost-Cox). On 16 public datasets under train-on-synthetic, test-on-real (C-index and IBS,

0

100

scale), FoGS yields mean improvements of

+2.17

in C-index and

+0.67

in IBS, improving both metrics on 9 of 16 datasets and at least one on 13 (one-sided Wilcoxon

p=0.039

and

p=0.035

). It matches or exceeds real-data training on most cohorts, with no significant change in nearest-neighbour privacy margin relative to unfiltered sampling. Sample filtering over a heterogeneous generator pool is thus a viable substitute for real-data training in privacy-restricted clinical settings.

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