{"total":24,"rows":[{"id":"2103.01315","title":"Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning","created":"2021-03-01","cited_by_count":56,"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":"2101.09499","title":"Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning","created":"2021-01-23","cited_by_count":15,"area":null},{"id":"2110.03572","title":"Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling","created":"2021-10-07","cited_by_count":13,"area":null},{"id":"2109.15317","title":"Unsupervised Few-Shot Action Recognition via Action-Appearance Aligned Meta-Adaptation","created":"2021-09-30","cited_by_count":11,"area":null},{"id":"2408.17059","title":"A Survey of the Self Supervised Learning Mechanisms for Vision Transformers","created":"2024-08-30","cited_by_count":9,"area":null},{"id":"2107.14035","title":"ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback","created":"2021-07-23","cited_by_count":8,"area":null},{"id":"2203.14205","title":"Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison","created":"2022-03-27","cited_by_count":8,"area":null},{"id":"2211.00868","title":"tSF: Transformer-based Semantic Filter for Few-Shot Learning","created":"2022-11-02","cited_by_count":6,"area":null},{"id":"2402.02444","title":"BECLR: Batch Enhanced Contrastive Few-Shot Learning","created":"2024-02-04","cited_by_count":6,"area":null},{"id":"2204.08226","title":"Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey","created":"2022-04-18","cited_by_count":5,"area":null},{"id":"2109.05675","title":"Online Unsupervised Learning of Visual Representations and Categories","created":"2021-09-13","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":"2210.06339","title":"Self-Attention Message Passing for Contrastive Few-Shot Learning","created":"2022-10-12","cited_by_count":4,"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":"2209.13635","title":"Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning","created":"2022-09-27","cited_by_count":3,"area":null},{"id":"2211.00890","title":"Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective","created":"2022-11-02","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":"2202.08149","title":"Self-Supervised Class-Cognizant Few-Shot Classification","created":"2022-02-15","cited_by_count":2,"area":null},{"id":"2212.01302","title":"DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model","created":"2022-12-02","cited_by_count":2,"area":null},{"id":"2106.15467","title":"Few-Shot Electronic Health Record Coding through Graph Contrastive Learning","created":"2021-06-29","cited_by_count":1,"area":null},{"id":"2306.13804","title":"Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers","created":"2023-06-23","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":"2309.06046","title":"BatMan-CLR: Making Few-shots Meta-Learners Resilient Against Label Noise","created":"2023-09-12","cited_by_count":0,"area":null}],"next_cursor":null}