{"total":27,"rows":[{"id":"2303.10158","title":"Data-centric Artificial Intelligence: A Survey","created":"2023-03-17","cited_by_count":203,"area":null},{"id":"2106.07499","title":"An Empirical Survey of Data Augmentation for Limited Data Learning in NLP","created":"2021-06-14","cited_by_count":101,"area":null},{"id":"2206.13508","title":"Data Augmentation techniques in time series domain: A survey and taxonomy","created":"2022-06-25","cited_by_count":41,"area":null},{"id":"2105.00026","title":"Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder","created":"2021-04-30","cited_by_count":27,"area":null},{"id":"2104.01616","title":"Towards Lifelong Learning of End-to-end ASR","created":"2021-04-04","cited_by_count":21,"area":null},{"id":"2307.12168","title":"Hallucination Improves the Performance of Unsupervised Visual Representation Learning","created":"2023-07-22","cited_by_count":16,"area":null},{"id":"2205.06153","title":"TreeMix: Compositional Constituency-based Data Augmentation for Natural Language Understanding","created":"2022-05-12","cited_by_count":15,"area":null},{"id":"2304.09607","title":"CB-Conformer: Contextual biasing Conformer for biased word recognition","created":"2023-04-19","cited_by_count":11,"area":null},{"id":"2206.09783","title":"Boosting Cross-Domain Speech Recognition with Self-Supervision","created":"2022-06-20","cited_by_count":10,"area":null},{"id":"2102.06237","title":"An Investigation of End-to-End Models for Robust Speech Recognition","created":"2021-02-11","cited_by_count":9,"area":null},{"id":"2310.10060","title":"Data Augmentation for Time-Series Classification: An Extensive Empirical Study and Comprehensive Survey","created":"2023-10-16","cited_by_count":9,"area":null},{"id":"2210.16584","title":"Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images","created":"2022-10-29","cited_by_count":8,"area":null},{"id":"2405.14161","title":"Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models","created":"2024-05-23","cited_by_count":8,"area":null},{"id":"2310.09505","title":"Advancing Test-Time Adaptation in Wild Acoustic Test Settings","created":"2023-10-14","cited_by_count":7,"area":null},{"id":"2209.12043","title":"Unsupervised domain adaptation for speech recognition with unsupervised error correction","created":"2022-09-24","cited_by_count":5,"area":null},{"id":"2106.11892","title":"Making Invisible Visible: Data-Driven Seismic Inversion with Spatio-temporally Constrained Data Augmentation","created":"2021-06-22","cited_by_count":4,"area":null},{"id":"2111.01740","title":"Personalized One-Shot Lipreading for an ALS Patient","created":"2021-11-02","cited_by_count":4,"area":null},{"id":"2411.02075","title":"Towards certification: A complete statistical validation pipeline for supervised learning in industry","created":"2024-11-04","cited_by_count":4,"area":null},{"id":"2407.17162","title":"Context-aware Multi-task Learning for Pedestrian Intent and Trajectory Prediction","created":"2024-07-24","cited_by_count":3,"area":null},{"id":"2408.05769","title":"LI-TTA: Language Informed Test-Time Adaptation for Automatic Speech Recognition","created":"2024-08-11","cited_by_count":3,"area":null},{"id":"2208.10718","title":"String-based Molecule Generation via Multi-decoder VAE","created":"2022-08-23","cited_by_count":2,"area":null},{"id":"2204.11286","title":"Improved far-field speech recognition using Joint Variational Autoencoder","created":"2022-04-24","cited_by_count":0,"area":null},{"id":"2506.10653","title":"Robust Unsupervised Adaptation of a Speech Recogniser Using Entropy Minimisation and Speaker Codes","created":"2025-06-12","cited_by_count":0,"area":null},{"id":"2507.04665","title":"Hybrid Adversarial Spectral Loss Conditional Generative Adversarial Networks for Signal Data Augmentation in Ultra-precision Machining Surface Roughness Prediction","created":"2025-07-07","cited_by_count":0,"area":null},{"id":"2604.13988","title":"Unsupervised domain transfer: Overcoming signal degradation in sleep monitoring by increasing scoring realism","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2604.18035","title":"Variational Autoencoder Domain Adaptation for Cross-System Generalization in ML-Based SOP Monitoring","created":"2026-04-20","cited_by_count":0,"area":null},{"id":"2608.29012","title":"Frequency Selective Neural Networks as a Foundation Architecture for Time Series Learning","created":"2026-08-29","cited_by_count":0,"area":null}],"next_cursor":null}