Synthetic Data Generation

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43 papers in the last four weeks, up 59% on the four weeks before. 0.4% of all new papers.

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Latest papers 417

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CodeAlchemy: Synthetic Code Rewriting at Scale
Jun 8, 2026Ankit Gupta, Aditya Prasad, Rameswar PandaSynthetic Data Pretraining Synthetic Data Generation
MIT-IBM Watson AI Lab, IBM Research
Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan
Jun 8, 2026Alexander Chulzhanov, Soeren Eberhardt, Arjun MukherjeeSynthetic Data Generation Low-Resource MT
University of Houston, Houston TX 77004, USA · MasterWord Services, Inc., Houston TX 77079, USA · University of Washington, Seattle WA 98195, USA
Streaming Interventions: Can Video Large Language Models Correct Mistakes as They Occur?
Jun 8, 2026Apratim Bhattacharyya, Shweta Mahajan, Sanjay Haresh +5LLM Fine-Tuning Synthetic Data Generation
Qualcomm AI Research · York University · Vector Institute for AI
Symbolic and Abstractive Reasoning with Complex Visual Queries
Jun 8, 2026Yichi Zhang, Jingdian Lu, Zhuo Chen +4Visual Reasoning Synthetic Data Generation
Zhejiang University · Nanjing University · Ant Group
DynaOD: Dynamic Origin-Destination Flow Generation with Discrete-to-Continuous Temporal Semantic Modeling
Jun 8, 2026Jie Zhao, Xianqi Dai, Jie Feng +2Intelligent Transportation Systems Synthetic Data Generation
Department of Electronic Engineering, BNRist, Tsinghua University · Tsinghua Shenzhen International Graduate School · Zhongguancun Academy
Differentially Private Synthetic Data via APIs 4: Tabular Data
Jun 6, 2026Toan Tran, Arturs Backurs, Zinan Lin +3Synthetic Data Generation Synthetic Tabular Data Generation
Emory University · Microsoft Research
SSR: Can Simulated Patients Learn to Stigmatize Themselves? Modeling Self-Stigma through Internal Monologue
Jun 6, 2026Kunyao Lan, Bingrui Jin, Zichen Zhu +1Human Behavior Simulation Mental Health
X-LANCE Lab, Dept. of Computer Science and Engineering MoE Key Lab of Artificial Intelligence, AI Institute Shanghai Jiao Tong University, China
Balancing Real and Synthetic Data for CNN-based Masonry Crack Detection
Jun 6, 2026Mattia Forlesi, Alfonso Esposito, Ivan Zyrianoff +2Synthetic Data Augmentation Synthetic Data Generation
Department of Computer Science and Engineering, University of Bologna, Bologna, Italy · Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy
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
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
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
StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset
Jun 4, 2026Zhengqian Wu, Zhixian Liu, Aodong Chen +6Video Understanding Synthetic Data Generation
School of Computer Science, Wuhan University, Wuhan, 430072, Hubei, China. · 2National Engineering Research Center for Multimedia Software, China. · 3Hubei Key Laboratory of Multimedia and Network Communication Engineering, China.
LLM-Conditioned Synthesis of Pathological Gaits via Structured Gait-Language Representations
Jun 4, 2026Mritula Chandrasekaran, Sanket Kachole, Jarek Francik +1Synthetic Data Augmentation Synthetic Data Generation
School of Computer Science and Mathematics, Kingston University, London, United Kingdom
Diff2SP: Diffusion Models for Correlated Scenario Generation in Stochastic Programming
Jun 4, 2026Haixiang Sun, Andrew LiuStochastic Optimization Synthetic Data Generation
Purdue University
Synthetic Contrastive Reasoning for Multi-Table Q&A
Jun 3, 2026Ankit Pratap Singh, Xin Su, Phillip HowardTable QA Synthetic Data Generation
Iowa State University · Thoughtworks
Reconstructing Unobservable Temperature Fields via Simulation-Aided Intelligent Sensing
Jun 3, 2026Monika Stipsitz, Hèlios Sanchis-Alepuz, Jacob Reynvaan +1Synthetic Data Generation Scientific ML
Embedded Systems Silicon Austria Labs GmbH Graz, Austria
Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers
Jun 3, 2026Biao Qian, Yang Wang, Yong Wu +1Vision Transformer Synthetic Data Generation
Department of Automation, Tsinghua University, China. · School of Computer Science and Information Engineering, Hefei University of Technology, China. · Li Auto, China.
Synthesize and Reward -- Reinforcement Learning for Multi-Step Tool Use in Live Environments
Jun 2, 2026Ibrahim Abdelaziz, Asim Munawar, Kinjal Basu +4Synthetic Data Generation Reinforcement Learning with Verifiable Rewards
IBM Research
MariData: One-Step Unpaired Image Translation for Maritime Environments
Jun 2, 2026Santeri Henriksson, Mehdi Asadi, Amin Majd +1Image-to-Image Translation Synthetic Data Generation
AIS Lab, Turku University of Applied Sciences, Turku, Finland
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
Scaling Agentic Capabilities via Grounded Interaction Synthesis
Jun 1, 2026Wenhang Shi, Jinhao Dong, Yiren Chen +4Synthetic Data Generation LLM Agent Training
Renmin University of China · Peking University · Tencent
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
When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval
May 31, 2026Zhicheng Zhang, Jiwei Tang, Kuicai Dong +9Contrastive Learning Hard Negative Mining
Shenzhen International Graduate School, Tsinghua University Shenzhen, China · Huawei Technologies Co., Ltd. Shenzhen, China · City University of Hong Kong Hong Kong SAR, China +4
Efficient Synthetic Network Generation via Latent Embedding Reconstruction
May 31, 2026Feifan Jiang, Yinan Bu, Shihao Wu +2Graph Generation Synthetic Data Generation
Department of Statistics, University of Michigan, Ann Arbor, Michigan, USA.
Ryze: Evidence-Enriched Data Synthesis from Biomedical Papers
May 30, 2026Yeqi Huang, Yue Chen, Yanwei Ye +2VLM Adaptation Synthetic Data Generation
University of Edinburgh, United Kingdom
Statistical Testing on Directed Graphs by Surrogate Data Generation
May 30, 2026Chun Hei Michael Chan, Alexandre Cionca, Dimitri Van De VilleGraph Signal Processing Synthetic Data Generation
Neuro-X Institute, Ecole polytechnique f´ed´erale de Lausanne, and the Department of Radiology and Medical Informatics, University of Geneva, Switzerland
State Machine Guided Multi-Relational Synthetic Data from Logs for Anomaly Detection
May 30, 2026Aja Khanal, Apurva NarayanSynthetic Data Augmentation Online Anomaly Detection
University of Western Ontario London, Canada
Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems
May 29, 2026Xiangyu Wang, Yawen He, Shivendra Pratap Singh +12Synthetic Data Augmentation Synthetic Data Generation
Meta
SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics
May 29, 2026Eric LiangSynthetic Data Generation Retrieval Robustness
Oracle

Jun 8, 2026, cs.CLJ/K move · Enter open · S save

CodeAlchemy: Synthetic Code Rewriting at Scale

Ankit Gupta, Aditya Prasad, Rameswar Panda

MIT-IBM Watson AI Lab, IBM Research

Synthetic Data Pretraining Synthetic Data Generation Code Language Models Code Generation Benchmarks

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Pre-training on raw code teaches syntax but provides sparse signal for diverse real-world task formats. While synthetic data has proven transformative for language models, code remains largely unexplored beyond limited quality improvements. We present CodeAlchemy, a synthetic data generation framework that transforms publicly sourced code into semantically-rich training data through 5 strategies: CodeEnhance (quality-aware rewriting), CodeQA (template-based problems), CodeDev (developer tasks), CodeDialogue (multi-turn conversations), and CodeTrace (execution traces). We process 3 corpora across 15 languages to generate 500B+ tokens of synthetic data plus 350B reasoning tokens, orders of magnitude more than prior efforts. CodeTrace instruments and executes 1.3M+ files across 14 languages and 5K libraries, capturing control flow, state tracking, and library knowledge. We introduce DevEval (developer tasks) and TraceEval (execution prediction) benchmarks; frontier models like Claude Sonnet 4.5 achieve only 5.6% exact match on TraceEval, revealing critical gaps in semantic understanding. Our 3B models achieve 83.5% on HumanEval, 63.2% on MBPP, 8.09% win rate on DevEval, and 15.36 ROUGE-2 on TraceEval, outperforming frontier models 10x the size including 27B Gemma-3 and 32B Granite-4.0.

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Latest papers 417