{"total":64,"rows":[{"id":"2104.09415","title":"Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation","created":"2021-04-19","cited_by_count":67,"area":null},{"id":"2103.13575","title":"MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation","created":"2021-03-25","cited_by_count":54,"area":null},{"id":"2107.00085","title":"CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation","created":"2021-06-30","cited_by_count":52,"area":null},{"id":"2102.07121","title":"Multi-Objective Meta Learning","created":"2021-02-14","cited_by_count":39,"area":null},{"id":"2204.02811","title":"BMD: A General Class-balanced Multicentric Dynamic Prototype Strategy for Source-free Domain Adaptation","created":"2022-04-06","cited_by_count":39,"area":null},{"id":"2307.05014","title":"Test-Time Training on Video Streams","created":"2023-07-11","cited_by_count":37,"area":null},{"id":"2310.04723","title":"Subspace Identification for Multi-Source Domain Adaptation","created":"2023-10-07","cited_by_count":37,"area":null},{"id":"2207.09763","title":"GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":35,"area":null},{"id":"2106.10812","title":"ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation","created":"2021-06-21","cited_by_count":33,"area":null},{"id":"2104.09136","title":"ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation","created":"2021-04-19","cited_by_count":31,"area":null},{"id":"2103.10583","title":"Dynamic Transfer for Multi-Source Domain Adaptation","created":"2021-03-19","cited_by_count":29,"area":null},{"id":"2110.03143","title":"Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning","created":"2021-10-07","cited_by_count":25,"area":null},{"id":"2111.14353","title":"Semi-supervised Domain Adaptation via Sample-to-Sample Self-Distillation","created":"2021-11-29","cited_by_count":23,"area":"distill"},{"id":"2106.15793","title":"Multi-Source Domain Adaptation for Object Detection","created":"2021-06-30","cited_by_count":21,"area":null},{"id":"2205.04066","title":"Multi-level Consistency Learning for Semi-supervised Domain Adaptation","created":"2022-05-09","cited_by_count":20,"area":null},{"id":"2101.12727","title":"Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency","created":"2021-01-29","cited_by_count":19,"area":null},{"id":"2109.08901","title":"S$^3$VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation","created":"2021-09-18","cited_by_count":19,"area":null},{"id":"2111.13353","title":"Contrastive Vicinal Space for Unsupervised Domain Adaptation","created":"2021-11-26","cited_by_count":14,"area":null},{"id":"2311.05241","title":"When Meta-Learning Meets Online and Continual Learning: A Survey","created":"2023-11-09","cited_by_count":12,"area":null},{"id":"2402.00904","title":"Graph Domain Adaptation: Challenges, Progress and Prospects","created":"2024-02-01","cited_by_count":11,"area":null},{"id":"2401.11453","title":"Inter-Domain Mixup for Semi-Supervised Domain Adaptation","created":"2024-01-21","cited_by_count":10,"area":null},{"id":"2106.11756","title":"Trinity: A No-Code AI platform for complex spatial datasets","created":"2021-06-21","cited_by_count":9,"area":null},{"id":"2401.11448","title":"Adaptive Betweenness Clustering for Semi-Supervised Domain Adaptation","created":"2024-01-21","cited_by_count":9,"area":null},{"id":"2405.00749","title":"More is Better: Deep Domain Adaptation with Multiple Sources","created":"2024-05-01","cited_by_count":9,"area":null},{"id":"2101.02375","title":"Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation","created":"2021-01-07","cited_by_count":8,"area":null},{"id":"2106.09890","title":"Gradual Domain Adaptation via Self-Training of Auxiliary Models","created":"2021-06-18","cited_by_count":8,"area":null},{"id":"2104.13057","title":"Graphical Modeling for Multi-Source Domain Adaptation","created":"2021-04-27","cited_by_count":7,"area":null},{"id":"2108.10840","title":"Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark","created":"2021-08-24","cited_by_count":7,"area":null},{"id":"2111.06021","title":"Probabilistic Contrastive Learning for Domain Adaptation","created":"2021-11-11","cited_by_count":7,"area":null},{"id":"2111.10602","title":"Unsupervised Domain Adaptation for RF-based Gesture Recognition","created":"2021-11-20","cited_by_count":7,"area":null},{"id":"2107.06735","title":"Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation","created":"2021-07-14","cited_by_count":6,"area":null},{"id":"2203.10395","title":"Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-Learning","created":"2022-03-19","cited_by_count":6,"area":null},{"id":"2305.14986","title":"Non-adversarial Robustness of Deep Learning Methods for Computer Vision","created":"2023-05-24","cited_by_count":6,"area":null},{"id":"2107.03008","title":"Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer","created":"2021-07-07","cited_by_count":5,"area":null},{"id":"2207.13340","title":"PointFix: Learning to Fix Domain Bias for Robust Online Stereo Adaptation","created":"2022-07-27","cited_by_count":5,"area":null},{"id":"2210.09922","title":"Few-Shot Learning of Compact Models via Task-Specific Meta Distillation","created":"2022-10-18","cited_by_count":5,"area":null},{"id":"2103.15973","title":"Adaptive Pseudo-Label Refinement by Negative Ensemble Learning for Source-Free Unsupervised Domain Adaptation","created":"2021-03-29","cited_by_count":4,"area":null},{"id":"2107.06707","title":"Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data","created":"2021-07-14","cited_by_count":4,"area":null},{"id":"2202.00263","title":"Fully Online Meta-Learning Without Task Boundaries","created":"2022-02-01","cited_by_count":4,"area":null},{"id":"2202.02802","title":"Low-confidence Samples Matter for Domain Adaptation","created":"2022-02-06","cited_by_count":4,"area":null},{"id":"2208.08015","title":"Cross-Domain Few-Shot Classification via Inter-Source Stylization","created":"2022-08-17","cited_by_count":4,"area":null},{"id":"2210.09486","title":"Semi-Supervised Domain Adaptation with Auto-Encoder via Simultaneous Learning","created":"2022-10-18","cited_by_count":4,"area":null},{"id":"2112.10474","title":"Reciprocal Normalization for Domain Adaptation","created":"2021-12-20","cited_by_count":3,"area":null},{"id":"2311.05088","title":"Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces","created":"2023-11-09","cited_by_count":3,"area":null},{"id":"2403.11234","title":"Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias","created":"2024-03-17","cited_by_count":3,"area":null},{"id":"2101.01400","title":"Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation","created":"2021-01-05","cited_by_count":2,"area":null},{"id":"2107.08653","title":"Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap","created":"2021-07-19","cited_by_count":2,"area":null},{"id":"2305.17373","title":"Zero- and Few-Shot Event Detection via Prompt-Based Meta Learning","created":"2023-05-27","cited_by_count":2,"area":null},{"id":"2309.15176","title":"Robust Stance Detection: Understanding Public Perceptions in Social Media","created":"2023-09-26","cited_by_count":2,"area":null},{"id":"2304.07374","title":"Continual Source-Free Unsupervised Domain Adaptation","created":"2023-04-14","cited_by_count":1,"area":null},{"id":"2307.03449","title":"Universal Semi-supervised Model Adaptation via Collaborative Consistency Training","created":"2023-07-07","cited_by_count":1,"area":null},{"id":"2310.16573","title":"Adapt Anything: Tailor Any Image Classifiers across Domains And Categories Using Text-to-Image Diffusion Models","created":"2023-10-25","cited_by_count":1,"area":"diffusion"},{"id":"2205.13508","title":"Pick up the PACE: Fast and Simple Domain Adaptation via Ensemble Pseudo-Labeling","created":"2022-05-26","cited_by_count":0,"area":null},{"id":"2303.17526","title":"CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation","created":"2023-03-30","cited_by_count":0,"area":null},{"id":"2304.10762","title":"Towards Realizing the Value of Labeled Target Samples: a Two-Stage Approach for Semi-Supervised Domain Adaptation","created":"2023-04-21","cited_by_count":0,"area":null},{"id":"2305.16823","title":"HUB: Guiding Learned Optimizers with Continuous Prompt Tuning","created":"2023-05-26","cited_by_count":0,"area":null},{"id":"2308.10205","title":"GeT: Generative Target Structure Debiasing for Domain Adaptation","created":"2023-08-20","cited_by_count":0,"area":null},{"id":"2411.13152","title":"AGLP: A Graph Learning Perspective for Semi-supervised Domain Adaptation","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2501.13052","title":"One-Class Domain Adaptation via Meta-Learning","created":"2025-01-22","cited_by_count":0,"area":null},{"id":"2509.12081","title":"Deceptive Risk Minimization: Out-of-Distribution Generalization by Deceiving Distribution Shift Detectors","created":"2025-09-15","cited_by_count":0,"area":null},{"id":"2603.09419","title":"MetaDAT: Generalizable Trajectory Prediction via Meta Pre-training and Data-Adaptive Test-Time Updating","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2604.09576","title":"AHC: Meta-Learned Adaptive Compression for Continual Object Detection on Memory-Constrained Microcontrollers","created":"2026-02-24","cited_by_count":0,"area":null},{"id":"2608.04917","title":"An active-learning framework for real-time depth perception from monocular vision streams","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.13039","title":"Transfer Learning for Evolving Domains","created":"2026-09-11","cited_by_count":0,"area":null}],"next_cursor":null}