{"total":41,"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":"2307.12730","title":"COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts","created":"2023-07-24","cited_by_count":34,"area":null},{"id":"2104.03841","title":"ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition","created":"2021-04-08","cited_by_count":29,"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":"2205.02708","title":"Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction","created":"2022-05-05","cited_by_count":21,"area":null},{"id":"2310.10971","title":"Context-Aware Meta-Learning","created":"2023-10-17","cited_by_count":21,"area":null},{"id":"2203.13465","title":"CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification","created":"2022-03-25","cited_by_count":9,"area":null},{"id":"2403.04492","title":"Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning","created":"2024-03-07","cited_by_count":7,"area":null},{"id":"2112.02814","title":"A Survey of Deep Learning for Low-Shot Object Detection","created":"2021-12-06","cited_by_count":6,"area":null},{"id":"2205.00895","title":"On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification","created":"2022-05-02","cited_by_count":5,"area":null},{"id":"2107.13093","title":"Automated Human Cell Classification in Sparse Datasets using Few-Shot Learning","created":"2021-07-27","cited_by_count":4,"area":null},{"id":"2201.05151","title":"Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning","created":"2022-01-13","cited_by_count":4,"area":null},{"id":"2202.09014","title":"How Well Do Self-Supervised Methods Perform in Cross-Domain Few-Shot Learning?","created":"2022-02-18","cited_by_count":4,"area":null},{"id":"2304.14281","title":"Adaptive manifold for imbalanced transductive few-shot learning","created":"2023-04-27","cited_by_count":4,"area":null},{"id":"2309.12814","title":"Domain Adaptive Few-Shot Open-Set Learning","created":"2023-09-22","cited_by_count":4,"area":null},{"id":"2403.16495","title":"LSTTN: A Long-Short Term Transformer-based Spatio-temporal Neural Network for Traffic Flow Forecasting","created":"2024-03-25","cited_by_count":4,"area":null},{"id":"2104.00619","title":"Modular Adaptation for Cross-Domain Few-Shot Learning","created":"2021-04-01","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":"2202.08149","title":"Self-Supervised Class-Cognizant Few-Shot Classification","created":"2022-02-15","cited_by_count":2,"area":null},{"id":"2107.06992","title":"Finding Significant Features for Few-Shot Learning using Dimensionality Reduction","created":"2021-07-06","cited_by_count":1,"area":null},{"id":"2109.02917","title":"Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand Hygiene","created":"2021-09-07","cited_by_count":1,"area":null},{"id":"2111.00007","title":"Domain Agnostic Few-Shot Learning For Document Intelligence","created":"2021-10-29","cited_by_count":1,"area":null},{"id":"2203.10454","title":"Partitioning Image Representation in Contrastive Learning","created":"2022-03-20","cited_by_count":1,"area":null},{"id":"2305.09062","title":"SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification","created":"2023-05-15","cited_by_count":1,"area":null},{"id":"2311.08995","title":"Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images","created":"2023-11-15","cited_by_count":1,"area":null},{"id":"2403.17530","title":"Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification","created":"2024-03-26","cited_by_count":1,"area":null},{"id":"2410.14242","title":"Pseudo-label Refinement for Improving Self-Supervised Learning Systems","created":"2024-10-18","cited_by_count":1,"area":null},{"id":"2112.12359","title":"Dual Path Structural Contrastive Embeddings for Learning Novel Objects","created":"2021-12-23","cited_by_count":0,"area":null},{"id":"2201.08951","title":"Visual Representation Learning with Self-Supervised Attention for Low-Label High-data Regime","created":"2022-01-22","cited_by_count":0,"area":null},{"id":"2208.08217","title":"How does the degree of novelty impacts semi-supervised representation learning for novel class retrieval?","created":"2022-08-17","cited_by_count":0,"area":null},{"id":"2209.01332","title":"Class-Specific Channel Attention for Few-Shot Learning","created":"2022-09-03","cited_by_count":0,"area":null},{"id":"2210.07076","title":"Few-Shot Visual Question Generation: A Novel Task and Benchmark Datasets","created":"2022-10-13","cited_by_count":0,"area":null},{"id":"2408.13774","title":"Extremely Fine-Grained Visual Classification over Resembling Glyphs in the Wild","created":"2024-08-25","cited_by_count":0,"area":null},{"id":"2501.13418","title":"Rethinking the Sample Relations for Few-Shot Classification","created":"2025-01-23","cited_by_count":0,"area":null},{"id":"2504.04017","title":"A Comprehensive Survey of Challenges and Opportunities of Few-Shot Learning Across Multiple Domains","created":"2025-04-05","cited_by_count":0,"area":null},{"id":"2508.20135","title":"Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads","created":"2025-08-26","cited_by_count":0,"area":null},{"id":"2512.17954","title":"SCS-SupCon: Sigmoid-based Common and Style Supervised Contrastive Learning with Adaptive Decision Boundaries","created":"2025-12-17","cited_by_count":0,"area":null},{"id":"2605.31068","title":"HQ-JEPA: Hybrid Quantum Joint-Embedding Predictive Architecture for Cross-Modal Remote Sensing Representation Learning","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2606.09245","title":"Proposal Refinement for Few-Shot Object Detection","created":"2026-06-08","cited_by_count":0,"area":null},{"id":"2606.11233","title":"OSCS-SupCon: Orthogonal Sigmoid-based Common and Style Supervised Contrastive Learning for Robust Feature Disentanglement","created":"2026-05-29","cited_by_count":0,"area":null}],"next_cursor":null}