{"total":17,"rows":[{"id":"2508.17677","title":"TiKMiX: Take Data Influence into Dynamic Mixture for Language Model Pre-training","created":"2025-08-25","cited_by_count":6,"area":null},{"id":"2509.11265","title":"SelectMix: Enhancing Label Noise Robustness through Targeted Sample Mixing","created":"2025-09-14","cited_by_count":5,"area":null},{"id":"2601.21315","title":"Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation","created":"2026-01-29","cited_by_count":4,"area":null},{"id":"2509.18987","title":"DTW-Align: Bridging the Modality Gap in End-to-End Speech Translation with Dynamic Time Warping Alignment","created":"2025-09-23","cited_by_count":2,"area":null},{"id":"2606.25784","title":"$S^{2}$-FracMix: Label-Preserving Self-Saliency Mixup Augmentation","created":"2026-06-24","cited_by_count":2,"area":null},{"id":"2502.13825","title":"Mixup Regularization: A Probabilistic Perspective","created":"2025-02-19","cited_by_count":1,"area":null},{"id":"2606.09049","title":"Data augmented bootstrap: Unifying confidence interval construction by approximate invariance","created":"2026-06-08","cited_by_count":1,"area":null},{"id":"2607.19324","title":"InstructMixup: Instruction-Guided Salient Patch Editing for Robust Data Augmentation","created":"2026-07-21","cited_by_count":1,"area":null},{"id":"2502.15245","title":"Steganographic Embeddings as an Effective Data Augmentation","created":"2025-02-21","cited_by_count":0,"area":null},{"id":"2504.01737","title":"Enlightenment Period Improving DNN Performance","created":"2025-04-02","cited_by_count":0,"area":null},{"id":"2508.10147","title":"rETF-semiSL: Semi-Supervised Learning for Neural Collapse in Temporal Data","created":"2025-08-13","cited_by_count":0,"area":null},{"id":"2510.11579","title":"MS-Mix: Sentiment-Guided Adaptive Augmentation for Multimodal Sentiment Analysis","created":"2025-10-13","cited_by_count":0,"area":null},{"id":"2601.09121","title":"Beyond Seen Bounds: Class-Centric Polarization for Single-Domain Generalized Deep Metric Learning","created":"2026-01-14","cited_by_count":0,"area":null},{"id":"2601.23131","title":"Regularisation in neural networks: a survey and empirical analysis of approaches","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2606.08712","title":"SNR-ST-Mix: Sample-specific Neighborhood Regression Mixup for Augmented Spatial Transcriptomics Imputation with Deep Neural Network","created":"2026-06-07","cited_by_count":0,"area":null},{"id":"2606.22307","title":"Enhancing Protein Representation Learning via Manifold Restore Mixing","created":"2026-06-21","cited_by_count":0,"area":null},{"id":"2610.06146","title":"Impact of Data Augmentation on Confidence Calibration in Melanoma Classification","created":"2026-10-05","cited_by_count":0,"area":null}],"next_cursor":null}