Data Augmentation

CVPR 2024arXiv:2405.14881

#2

DiffuseMix: Label-Preserving Data Augmentation with Diffusion Models

Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood et al.

diffusion modelsdata augmentationlabel preservationconditional generation+3

90

ICML 2024arXiv:2312.12112

#3

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes

Nabeel Seedat, Nicolas Huynh, Boris van Breugel et al.

low-data regimestabular data augmentationsynthetic data generationlarge language models+4

51

ICLR 2024arXiv:2310.10402

#4

Real-Fake: Effective Training Data Synthesis Through Distribution Matching

Jianhao Yuan, Jie Zhang, Shuyang Sun et al.

training data synthesisdistribution matchingimage classificationsynthetic data augmentation+3

45

ICML 2024arXiv:2210.05021

#5

The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

Chi-Heng Lin, Chiraag Kaushik, Eva Dyer et al.

data augmentationspectral regularizationcovariance matrix eigenvaluesoverparameterized linear models+4

43

ICLR 2024arXiv:2403.12448

#6

Do Generated Data Always Help Contrastive Learning?

Yifei Wang, Jizhe Zhang, Yisen Wang

contrastive learningdata inflationdiffusion modelsunsupervised representation learning+3

35

ICLR 2024arXiv:2403.10834

#7

SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation

Uiwon Hwang, Jonghyun Lee, Juhyeon Shin et al.

27

ICLR 2024arXiv:2402.10434

#8

Parametric Augmentation for Time Series Contrastive Learning

Xu Zheng, Tianchun Wang, Wei Cheng et al.

26

ICLR 2024arXiv:2310.12972

#9

CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning

Liyiming Ke, Yunchu Zhang, Abhay Deshpande et al.

25

CVPR 2024arXiv:2403.01944

#10

Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification

Mei Vaish, Shunxin Wang, Nicola Strisciuglio

21

CVPR 2024arXiv:2403.10073

#11

Revisiting Adversarial Training Under Long-Tailed Distributions

Xinli Yue, Ningping Mou, Qian Wang et al.

18

ECCV 2024arXiv:2406.08249

#12

Dataset Enhancement with Instance-Level Augmentations

Orest Kupyn, Christian Rupprecht

latent diffusion modelsinstance-level augmentationdata anonymizationsalient object detection+4

18

CVPR 2025arXiv:2306.09363

#13

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning

Yunlu Yan, Huazhu Fu, Yuexiang Li et al.

17

ICML 2024arXiv:2212.11237

#14

Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators

Jianhao Yuan, Francesco Pinto, Adam Davies et al.

text-to-image generationsingle domain generalizationspurious feature reductioninterventional data augmentation+4

17

AAAI 2024arXiv:2312.11276

#15

Compositional Generalization for Multi-Label Text Classification: A Data-Augmentation Approach

Yuyang Chai, Zhuang Li, Jiahui Liu et al.

multi-label text classificationcompositional generalizationdata augmentationtext generation models+2

16

AAAI 2024arXiv:2308.15068

#16

A Comprehensive Augmentation Framework for Anomaly Detection

Lin Jiang, Yaping Yan

anomaly detectiondata augmentationreconstruction-based approachsimulated anomalies+4

16

ECCV 2024arXiv:2408.00350

#17

A Simple Background Augmentation Method for Object Detection with Diffusion Model

YUHANG LI, Xin Dong, Chen Chen et al.

object detectioninstance segmentationdata augmentationdiffusion models+4

16

ICLR 2025arXiv:2410.01524

#18

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models

Seanie Lee, Haebin Seong, Dong Bok Lee et al.

knowledge distillationsafety guard modelsdata augmentationlarge language models+3

15

CVPR 2024arXiv:2405.10185

#19

DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data

Chengxiang Fan, Muzhi Zhu, Hao Chen et al.

15

ECCV 2024arXiv:2310.09739

#20

Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning

Binwu Wang, Pengkun Wang, Wei Xu et al.

AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation

Yangchao Wu, Tian Yu Liu, Hyoungseob Park et al.

monocular depth completionunsupervised depth estimationgeometric augmentationsdepth map warping+3

15

ECCV 2024arXiv:2409.06290

#22

EntAugment: Entropy-Driven Adaptive Data Augmentation Framework for Image Classification

Suorong Yang, Furao Shen, Jian Zhao

data augmentationimage classificationentropy regularizationadaptive augmentation+2

14

CVPR 2024arXiv:2404.04960

#23

PairAug: What Can Augmented Image-Text Pairs Do for Radiology?

Yutong Xie, Qi Chen, Sinuo Wang et al.

12

ICLR 2025arXiv:2410.08896

#24

11293 Cross-Class Feature Augmentation for Class Incremental Learning

Taehoon Kim, JaeYoo Park, Bohyung Han

MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL

Claas Voelcker, Marcel Hussing, ERIC EATON et al.

ICML 2024arXiv:2405.18917

#26

Causal Action Influence Aware Counterfactual Data Augmentation

Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.

causal influence quantificationcounterfactual data augmentationoffline reinforcement learningrobustness to distributional shift+3

ICML 2024arXiv:2309.07909

#27

DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation

Zelin Zang, Hao Luo, Kai Wang et al.

contrastive learningdiffusion modelsdata augmentationunsupervised representation learning+4

CVPR 2025arXiv:2411.19946

#28

DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation

Zhiqiang Shen, Ammar Sherif, Zeyuan Yin et al.

dataset distillationbatch-to-batch matchingbatch-to-global matchingdiversity enhancement+3

ECCV 2024arXiv:2312.04763

#29

Enhancing Recipe Retrieval with Foundation Models: A Data Augmentation Perspective

Fangzhou Song, Bin Zhu, Yanbin Hao et al.

cross-modal retrievalrecipe retrievaldata augmentationfoundation models+3

10

AAAI 2025arXiv:2412.15657

#30

Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class

Annie D'souza, Swetha M, Sunita Sarawagi

9

ICLR 2025arXiv:2410.02056

#31

Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data

Sreyan Ghosh, Sonal Kumar, Zhifeng Kong et al.

8

ICLR 2024arXiv:2402.12181

#32

Revisiting Data Augmentation in Deep Reinforcement Learning

Jianshu Hu, Yunpeng Jiang, Paul Weng

8

ICLR 2025arXiv:2502.18195

#33

Multi-Perspective Data Augmentation for Few-shot Object Detection

Anh-Khoa Nguyen Vu, Quoc Truong Truong, Vinh-Tiep Nguyen et al.

few-shot object detectiondata augmentationdiffusion modelsobject synthesis+4

ECCV 2024arXiv:2409.07307

#34

Data Augmentation via Latent Diffusion for Saliency Prediction

Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang et al.

saliency predictionlatent diffusion modelsdata augmentationsaliency-guided cross-attention+3

CVPR 2025arXiv:2408.16266

#35

Inversion Circle Interpolation: Diffusion-based Image Augmentation for Data-scarce Classification

Yanghao Wang, Long Chen

diffusion-based image augmentationdata-scarce classificationfew-shot classificationlong-tailed classification+4

NEURIPS 2025arXiv:2406.01899

#36

Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models

Wenzhuo Tang, Haitao Mao, Danial Dervovic et al.

graph structure augmentationdiffusion modelscross-domain graphsgraph pre-training+2

CVPR 2025arXiv:2505.12745

#37

PEER Pressure: Model-to-Model Regularization for Single Source Domain Generalization

Dongkyu Cho, Inwoo Hwang, Sanghack Lee

ICLR 2024arXiv:2310.17786

#38

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates

Nicholas Corrado, Josiah Hanna

AAAI 2025arXiv:2412.11807

#39

PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection

Xiaoran Xu, Jiangang Yang, Wenhui Shi et al.

single-domain generalizationobject detectiondata augmentationphysical model+4

AAAI 2025arXiv:2412.08300

#40

Augmenting Sequential Recommendation with Balanced Relevance and Diversity

Yizhou Dang, Jiahui Zhang, Yuting Liu et al.

ICML 2024arXiv:2406.10914

#41

First-Order Manifold Data Augmentation for Regression Learning

Ilya Kaufman, Omri Azencot

data augmentationregression learningdomain-independent augmentationtangent plane sampling+3

ICML 2024arXiv:2402.03325

#42

Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations

Helen Qu, Sang Michael Xie

domain adaptationout-of-distribution robustnesstargeted data augmentationself-supervised pretraining+4

5

AAAI 2025arXiv:2412.10029

#43

Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples

Yeyuan Wang, Dehong Gao, Lei Yi et al.

vision-language pretrainingfine-grained understandingnegative augmented samplesvisual dictionary+4

4

AAAI 2024arXiv:2312.07951

#44

Semantic-Aware Data Augmentation for Text-to-Image Synthesis

Zhaorui Tan, Xi Yang, Kaizhu Huang

text-to-image synthesissemantic data augmentationattention mechanismcontrastive learning+4

4

ECCV 2024arXiv:2409.04820

#45

GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data

Zhiteng Li, Lele Chen, Jerone Andrews et al.

FreeAugment: Data Augmentation Search Across All Degrees of Freedom

Tom Bekor, Niv Nayman, Lihi Zelnik-Manor

data augmentation searchautomatic image transformationsdifferentiable optimizationtransformation magnitude learning+2

3

ICML 2024arXiv:2408.15399

#47

A Statistical Framework for Data-dependent Retrieval-Augmented Models

Soumya Basu, Ankit Singh Rawat, Manzil Zaheer

retrieval-augmented modelsdata-dependent retrievalend-to-end trainingexcess risk bounds+2

2

AAAI 2025arXiv:2405.14115

#48

Representation Space Augmentation for Effective Self-Supervised Learning on Tabular Data

Moonjung Eo, Kyungeun Lee, Hye-Seung Cho et al.

Configuring Data Augmentations to Reduce Variance Shift in Positional Embedding of Vision Transformers

Bum Jun Kim, Sang Woo Kim

vision transformerspositional embeddingdata augmentationsvariance shift+4

2

ICLR 2025arXiv:2402.06855

#50

For Better or For Worse? Learning Minimum Variance Features With Label Augmentation

Muthu Chidambaram, Rong Ge

2

NEURIPS 2025arXiv:2510.24262

#51

UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation

Jiyu Guo, Shuo Yang, Yiming Huang et al.

generative data augmentationtask-specific utilitydual-level optimizationweight allocation network+4

ICLR 2024arXiv:2410.02512

#52

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation

Mucong Ding, Bang An, Yuancheng Xu et al.

AAAI 2025arXiv:2502.18249

#53

Iterative Counterfactual Data Augmentation

Mitchell Plyler, Min Chi

AAAI 2025arXiv:2405.18880

#54

EventZoom: A Progressive Approach to Event-Based Data Augmentation for Enhanced Neuromorphic Vision

Yiting Dong, Xiang He, Guobin Shen et al.

ICML 2025arXiv:2505.19659

#55

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP

ICML 2025arXiv:2505.22196

#56

An Augmentation-Aware Theory for Self-Supervised Contrastive Learning

Jingyi Cui, Hongwei Wen, Yisen Wang

NEURIPS 2025arXiv:2503.11544

#57

AugGen: Synthetic Augmentation using Diffusion Models Can Improve Recognition

Parsa Rahimi, Damien Teney, Sébastien Marcel

NEURIPS 2025arXiv:2510.15194

#58

Split-and-Combine: Enhancing Style Augmentation for Single Domain Generalization

Zhen Zhang, Zhen Zhang, Qianlong Dang et al.

Salient Concept-Aware Generative Data Augmentation

Tianchen Zhao, Xuanbai Chen, Zhihua Li et al.

generative data augmentationdiffusion modelsmodel distillationadversarial alignment+4

#60

ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation

Yuewen Sun, Erli Wang, Biwei Huang et al.

Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting

Ruyi An, haicheng huang, Huangjie Zheng et al.

NEURIPS 2025

NEURIPS 2025arXiv:2506.02689

#62

Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation

Jian Bi, Qianliang Wu, Xiang Li et al.

MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching

Liang Yue, Yihong Tang, Kehai Chen et al.

domain adaptationdistribution shiftdata acquisitioncross-distribution generalization+3

#64

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian et al.

ICML 2024

ICML 2025arXiv:2506.06853

#65

Curvature Enhanced Data Augmentation for Regression

Ilya Kaufman, Omri Azencot

test-time augmentationmetamorphic relationscombinatorial problemsgraph neural networks+3

#66

Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems

Siwei Wei, Xudong Zhang, Zhiyang Zhou et al.

ICML 2024

domain adaptationvision-language modelstext-guided augmentationunseen domains+2

#67

Generalizing to Unseen Domains via Text-guided Augmentation

Daiqing Qi, Handong Zhao, Aidong Zhang et al.

ECCV 2024

ICML 2025arXiv:2504.05250

#68

When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration

Suorong Yang, Peng Ye, Furao Shen et al.

PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity

Mustafa Burak Gurbuz, Xingyu Zheng, Constantine Dovrolis

CVPR 2024arXiv:2403.15194

#70

Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusion

Sofia Casarin, Cynthia Ugwu, Sergio Escalera et al.

differentiable augmentation searchimage classificationsemantic segmentationautomatic data augmentation+3

long-tail instance segmentationgenerative data augmentationdiffusion modelssample efficiency+4

#71

Diffusion-Guided Graph Data Augmentation

Maria Marrium, Arif Mahmood, Muhammad Haris Khan et al.

Sample-Efficient Multi-Round Generative Data Augmentation for Long-Tail Instance Segmentation

Byunghyun Kim, Minyoung Bae, Jae-Gil Lee

NEURIPS 2025

dynamic graph neural networksgraph data augmentationtemporal consistencygraph rationalization+3

#73

PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs

Seungyoo Lee, Giung Nam, Moonseok Choi et al.

Adversity-aware Few-shot Named Entity Recognition via Augmentation Learning

Li Huang, Haowen Liu, Qiang Gao et al.

Domain Gap Embeddings for Generative Dataset Augmentation

Yinong Oliver Wang, Younjoon Chung, Chen Henry Wu et al.

On Trajectory Augmentations for Off-Policy Evaluation

Ge Gao, Qitong Gao, Xi Yang et al.

Data Augmentation for Instruction Following Policies via Trajectory Segmentation

Niklas Hoepner, Ilaria Tiddi, Herke van Hoof

Scaling and Taming Adversarial Training with Synthetic Data

Juntao Wu, Xianting Huang, Yu Chen et al.

Progressive Distribution Bridging: Unsupervised Adaptation for Large-scale Pre-trained Models via Adaptive Auxiliary Data

Weinan He, Yixin Zhang, Zilei Wang

Prototype-based Contrastive Learning with Stage-wise Progressive Augmentation for Self-Supervised Fine-Grained Learning

BaoFeng Tan, Xiu-Shen Wei, Lin Zhao

GNN-Transformer Task Planning Enhanced with Semantic-Driven Data Augmentation

Soojin Jeong, Seongwan Byeon, Sangwoo Kim et al.

Sparse Enhanced Network: An Adversarial Generation Method for Robust Augmentation in Sequential Recommendation

Junyang Chen, Guoxuan Zou, Pan Zhou et al.

ADD: Attribution-Driven Data Augmentation Framework for Boosting Image Super-Resolution

Zeyu Mi, Yu-Bin Yang

Rationalizing and Augmenting Dynamic Graph Neural Networks

Guibin Zhang, Yiyan Qi, Ziyang Cheng et al.

ICLR 2025

#85

Generative Hard Example Augmentation for Semantic Point Cloud Segmentation

Qi Zhang, Jibin Peng, Zhao Huang et al.

Instruct Where the Model Fails: Generative Data Augmentation via Guided Self-contrastive Fine-tuning

Weijian Ma, Ruoxin Chen, Keyue Zhang et al.

AAAI 2025