{"total":73,"rows":[{"id":"2205.06743","title":"A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities","created":"2022-05-13","cited_by_count":163,"area":null},{"id":"2204.07305","title":"Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference","created":"2022-04-15","cited_by_count":126,"area":null},{"id":"2302.09309","title":"StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning","created":"2023-02-18","cited_by_count":53,"area":null},{"id":"2106.07807","title":"Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data","created":"2021-06-14","cited_by_count":50,"area":null},{"id":"2107.11978","title":"Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data","created":"2021-07-26","cited_by_count":48,"area":null},{"id":"2203.15882","title":"Learning to Detect Mobile Objects from LiDAR Scans Without Labels","created":"2022-03-29","cited_by_count":44,"area":null},{"id":"2202.01339","title":"Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty","created":"2022-02-01","cited_by_count":37,"area":null},{"id":"2112.00260","title":"Ranking Distance Calibration for Cross-Domain Few-Shot Learning","created":"2021-12-01","cited_by_count":27,"area":null},{"id":"2203.07656","title":"Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning","created":"2022-03-15","cited_by_count":23,"area":null},{"id":"2310.10971","title":"Context-Aware Meta-Learning","created":"2023-10-17","cited_by_count":21,"area":null},{"id":"2206.00092","title":"FHIST: A Benchmark for Few-shot Classification of Histological Images","created":"2022-05-31","cited_by_count":20,"area":null},{"id":"2207.09176","title":"Self-Supervision Can Be a Good Few-Shot Learner","created":"2022-07-19","cited_by_count":19,"area":null},{"id":"2210.05311","title":"CD-FSOD: A Benchmark for Cross-domain Few-shot Object Detection","created":"2022-10-11","cited_by_count":17,"area":null},{"id":"2104.02638","title":"Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark","created":"2021-04-06","cited_by_count":16,"area":null},{"id":"2210.05392","title":"TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning","created":"2022-10-11","cited_by_count":16,"area":null},{"id":"2110.05076","title":"A Closer Look at Prototype Classifier for Few-shot Image Classification","created":"2021-10-11","cited_by_count":15,"area":null},{"id":"2206.04679","title":"POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples","created":"2022-06-08","cited_by_count":15,"area":null},{"id":"2306.10511","title":"Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning","created":"2023-06-18","cited_by_count":15,"area":null},{"id":"2109.09883","title":"On the Importance of Distractors for Few-Shot Classification","created":"2021-09-20","cited_by_count":14,"area":null},{"id":"2112.08181","title":"Hierarchical Variational Memory for Few-shot Learning Across Domains","created":"2021-12-15","cited_by_count":14,"area":null},{"id":"2303.08557","title":"Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey","created":"2023-03-15","cited_by_count":14,"area":null},{"id":"2309.03989","title":"CDFSL-V: Cross-Domain Few-Shot Learning for Videos","created":"2023-09-07","cited_by_count":13,"area":null},{"id":"2403.01966","title":"Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning","created":"2024-03-04","cited_by_count":13,"area":null},{"id":"2405.12368","title":"Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)","created":"2024-05-20","cited_by_count":13,"area":null},{"id":"2412.00767","title":"Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting","created":"2024-12-01","cited_by_count":10,"area":null},{"id":"2210.05280","title":"ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning","created":"2022-10-11","cited_by_count":9,"area":null},{"id":"2310.14390","title":"Cross-Domain HAR: Few Shot Transfer Learning for Human Activity Recognition","created":"2023-10-22","cited_by_count":9,"area":null},{"id":"2406.16422","title":"Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting","created":"2024-06-24","cited_by_count":9,"area":null},{"id":"2110.02529","title":"On the Importance of Firth Bias Reduction in Few-Shot Classification","created":"2021-10-06","cited_by_count":7,"area":null},{"id":"2307.14709","title":"Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation","created":"2023-07-27","cited_by_count":7,"area":null},{"id":"2401.13987","title":"Cross-Domain Few-Shot Learning via Adaptive Transformer Networks","created":"2024-01-25","cited_by_count":7,"area":null},{"id":"2110.09510","title":"Unsupervised Finetuning","created":"2021-10-18","cited_by_count":6,"area":null},{"id":"2205.05282","title":"ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning","created":"2022-05-11","cited_by_count":6,"area":null},{"id":"2205.07874","title":"How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation","created":"2022-05-13","cited_by_count":6,"area":null},{"id":"2304.04858","title":"Simulated Annealing in Early Layers Leads to Better Generalization","created":"2023-04-10","cited_by_count":6,"area":null},{"id":"2207.07826","title":"Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations","created":"2022-07-16","cited_by_count":5,"area":null},{"id":"2207.07973","title":"Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition","created":"2022-07-16","cited_by_count":5,"area":null},{"id":"2210.06295","title":"Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond","created":"2022-10-03","cited_by_count":5,"area":null},{"id":"2408.09722","title":"Towards Few-Shot Learning in the Open World: A Review and Beyond","created":"2024-08-19","cited_by_count":5,"area":null},{"id":"2411.10070","title":"Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning","created":"2024-11-15","cited_by_count":5,"area":null},{"id":"2207.09767","title":"Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition","created":"2022-07-20","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":"2304.12314","title":"Distilling from Similar Tasks for Transfer Learning on a Budget","created":"2023-04-24","cited_by_count":4,"area":null},{"id":"2309.01342","title":"Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification","created":"2023-09-04","cited_by_count":4,"area":null},{"id":"2402.12706","title":"Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition","created":"2024-02-20","cited_by_count":4,"area":null},{"id":"2404.05139","title":"Better Monocular 3D Detectors with LiDAR from the Past","created":"2024-04-08","cited_by_count":4,"area":null},{"id":"2407.05657","title":"DMSD-CDFSAR: Distillation from Mixed-Source Domain for Cross-Domain Few-shot Action Recognition","created":"2024-07-08","cited_by_count":4,"area":null},{"id":"2411.19041","title":"TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition","created":"2024-11-28","cited_by_count":4,"area":null},{"id":"2104.03309","title":"Streaming Self-Training via Domain-Agnostic Unlabeled Images","created":"2021-04-07","cited_by_count":3,"area":null},{"id":"2112.06320","title":"Anomaly Crossing: New Horizons for Video Anomaly Detection as Cross-domain Few-shot Learning","created":"2021-12-12","cited_by_count":3,"area":null},{"id":"2207.01072","title":"Dynamic Sub-Cluster-Aware Network for Few-Shot Skin Disease Classification","created":"2022-07-03","cited_by_count":3,"area":null},{"id":"2208.14686","title":"NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results","created":"2022-08-31","cited_by_count":3,"area":null},{"id":"2303.09253","title":"A Survey of Deep Visual Cross-Domain Few-Shot Learning","created":"2023-03-16","cited_by_count":3,"area":null},{"id":"2311.02392","title":"Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification","created":"2023-11-04","cited_by_count":3,"area":null},{"id":"2312.11260","title":"Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning","created":"2023-12-18","cited_by_count":3,"area":null},{"id":"2506.03110","title":"Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning","created":"2025-06-03","cited_by_count":3,"area":null},{"id":"2406.01073","title":"Understanding the Cross-Domain Capabilities of Video-Based Few-Shot Action Recognition Models","created":"2024-06-03","cited_by_count":2,"area":null},{"id":"2504.15323","title":"HyperFlow: Gradient-Free Emulation of Few-Shot Fine-Tuning","created":"2025-04-21","cited_by_count":2,"area":null},{"id":"2511.14279","title":"Free Lunch to Meet the Gap: Intermediate Domain Reconstruction for Cross-Domain Few-Shot Learning","created":"2025-11-18","cited_by_count":2,"area":null},{"id":"2107.11056","title":"Improving the Generalization of Meta-learning on Unseen Domains via Adversarial Shift","created":"2021-07-23","cited_by_count":1,"area":null},{"id":"2205.03817","title":"PGADA: Perturbation-Guided Adversarial Alignment for Few-shot Learning Under the Support-Query Shift","created":"2022-05-08","cited_by_count":1,"area":null},{"id":"2309.02088","title":"Dual Adversarial Alignment for Realistic Support-Query Shift Few-shot Learning","created":"2023-09-05","cited_by_count":1,"area":null},{"id":"2403.03535","title":"Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications","created":"2024-03-06","cited_by_count":1,"area":null},{"id":"2508.20530","title":"Enhancing Pseudo-Boxes via Data-Level LiDAR-Camera Fusion for Unsupervised 3D Object Detection","created":"2025-08-28","cited_by_count":1,"area":null},{"id":"2110.11190","title":"On Hard Episodes in Meta-Learning","created":"2021-10-21","cited_by_count":0,"area":null},{"id":"2203.02270","title":"Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification","created":"2022-03-04","cited_by_count":0,"area":null},{"id":"2302.02224","title":"TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality","created":"2023-02-04","cited_by_count":0,"area":null},{"id":"2401.13693","title":"Challenge design roadmap","created":"2024-01-15","cited_by_count":0,"area":null},{"id":"2504.06608","title":"A Cross-Domain Few-Shot Learning Method Based on Domain Knowledge Mapping","created":"2025-04-09","cited_by_count":0,"area":null},{"id":"2507.20511","title":"Beyond Class Tokens: LLM-guided Dominant Property Mining for Few-shot Classification","created":"2025-07-28","cited_by_count":0,"area":null},{"id":"2511.06648","title":"FreqGRL: Suppressing Low-Frequency Bias and Mining High-Frequency Knowledge for Cross-Domain Few-Shot Learning","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2607.21004","title":"AUCH-Net: Action Unit-Based Consistency-Aware Hypergraph Network for Cross-Domain Few-Shot Facial Expression Recognition","created":"2026-07-23","cited_by_count":0,"area":null},{"id":"2610.18209","title":"Closing the Estimation Gap: Training-Free Transductive Inference for Cross-Domain Few-Shot Action Recognition","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}