{"total":35,"rows":[{"id":"2212.14453","title":"Learning Multimodal Data Augmentation in Feature Space","created":"2022-12-29","cited_by_count":18,"area":null},{"id":"2403.01944","title":"Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification","created":"2024-03-04","cited_by_count":18,"area":null},{"id":"2309.04747","title":"When to Learn What: Model-Adaptive Data Augmentation Curriculum","created":"2023-09-09","cited_by_count":13,"area":null},{"id":"2409.06290","title":"EntAugment: Entropy-Driven Adaptive Data Augmentation Framework for Image Classification","created":"2024-09-10","cited_by_count":13,"area":null},{"id":"2407.07805","title":"SUMix: Mixup with Semantic and Uncertain Information","created":"2024-07-10","cited_by_count":12,"area":null},{"id":"2305.16379","title":"Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning","created":"2023-05-25","cited_by_count":8,"area":null},{"id":"2210.16117","title":"Improving the Transferability of Adversarial Attacks on Face Recognition with Beneficial Perturbation Feature Augmentation","created":"2022-10-28","cited_by_count":7,"area":null},{"id":"2405.11467","title":"AdaAugment: A Tuning-Free and Adaptive Approach to Enhance Data Augmentation","created":"2024-05-19","cited_by_count":7,"area":null},{"id":"2306.09998","title":"SLACK: Stable Learning of Augmentations with Cold-start and KL regularization","created":"2023-06-16","cited_by_count":6,"area":null},{"id":"2204.12143","title":"Deeper Insights into the Robustness of ViTs towards Common Corruptions","created":"2022-04-26","cited_by_count":5,"area":null},{"id":"2310.06670","title":"Domain Generalization by Rejecting Extreme Augmentations","created":"2023-10-10","cited_by_count":5,"area":null},{"id":"2503.09206","title":"Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients","created":"2025-03-12","cited_by_count":5,"area":null},{"id":"2508.08004","title":"Sample-aware RandAugment: Search-free Automatic Data Augmentation for Effective Image Recognition","created":"2025-08-11","cited_by_count":5,"area":null},{"id":"2411.15555","title":"Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation","created":"2024-11-23","cited_by_count":4,"area":null},{"id":"2205.12606","title":"ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation","created":"2022-05-25","cited_by_count":3,"area":null},{"id":"2312.10586","title":"Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI","created":"2023-12-17","cited_by_count":3,"area":null},{"id":"2409.04820","title":"FreeAugment: Data Augmentation Search Across All Degrees of Freedom","created":"2024-09-07","cited_by_count":3,"area":null},{"id":"2508.17843","title":"SCOUT: Semi-supervised Camouflaged Object Detection by Utilizing Text and Adaptive Data Selection","created":"2025-08-25","cited_by_count":3,"area":null},{"id":"2402.14789","title":"Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning","created":"2024-02-22","cited_by_count":2,"area":null},{"id":"2410.12955","title":"Long-Tailed Backdoor Attack Using Dynamic Data Augmentation Operations","created":"2024-10-16","cited_by_count":2,"area":null},{"id":"2210.08458","title":"Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers","created":"2022-10-16","cited_by_count":1,"area":null},{"id":"2305.03259","title":"Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation","created":"2023-05-05","cited_by_count":1,"area":null},{"id":"2305.04628","title":"Target-driven One-Shot Unsupervised Domain Adaptation","created":"2023-05-08","cited_by_count":1,"area":null},{"id":"2310.02201","title":"Learnable Data Augmentation for One-Shot Unsupervised Domain Adaptation","created":"2023-10-03","cited_by_count":1,"area":null},{"id":"2310.08139","title":"DualAug: Exploiting Additional Heavy Augmentation with OOD Data Rejection","created":"2023-10-12","cited_by_count":1,"area":null},{"id":"2403.08352","title":"Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods","created":"2024-03-13","cited_by_count":1,"area":null},{"id":"2403.10782","title":"Bidirectional Multi-Step Domain Generalization for Visible-Infrared Person Re-Identification","created":"2024-03-16","cited_by_count":1,"area":null},{"id":"2404.00898","title":"CAAP: Class-Dependent Automatic Data Augmentation Based On Adaptive Policies For Time Series","created":"2024-04-01","cited_by_count":1,"area":null},{"id":"2508.07723","title":"Enhancing Small-Scale Dataset Expansion with Triplet-Connection-based Sample Re-Weighting","created":"2025-08-11","cited_by_count":1,"area":null},{"id":"2510.00434","title":"On-the-Fly Data Augmentation via Gradient-Guided and Sample-Aware Influence Estimation","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2211.07859","title":"Local Magnification for Data and Feature Augmentation","created":"2022-11-15","cited_by_count":0,"area":null},{"id":"2305.13232","title":"Revisiting Data Augmentation in Model Compression: An Empirical and Comprehensive Study","created":"2023-05-22","cited_by_count":0,"area":null},{"id":"2502.09944","title":"Self-Supervised Learning for Neural Topic Models with Variance-Invariance-Covariance Regularization","created":"2025-02-14","cited_by_count":0,"area":null},{"id":"2607.02271","title":"AGVBench: A Reliability-Oriented Benchmark of Data Augmentation for Vein Recognition","created":"2026-07-02","cited_by_count":0,"area":null},{"id":"2608.18907","title":"Learning-State-Aware Dynamic Generative Data Augmentation on Small-Scale Datasets","created":"2026-08-19","cited_by_count":0,"area":null}],"next_cursor":null}