{"total":18,"rows":[{"id":"2104.02324","title":"Multiple instance active learning for object detection","created":"2021-04-06","cited_by_count":77,"area":null},{"id":"2107.14153","title":"Semi-Supervised Active Learning with Temporal Output Discrepancy","created":"2021-07-29","cited_by_count":50,"area":null},{"id":"2206.12569","title":"Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels","created":"2022-06-25","cited_by_count":25,"area":null},{"id":"2407.12212","title":"Generalized Coverage for More Robust Low-Budget Active Learning","created":"2024-07-16","cited_by_count":16,"area":null},{"id":"2412.20644","title":"Uncertainty Herding: One Active Learning Method for All Label Budgets","created":"2024-12-30","cited_by_count":15,"area":null},{"id":"2211.14819","title":"Deep Active Learning for Computer Vision: Past and Future","created":"2022-11-27","cited_by_count":7,"area":null},{"id":"2407.14720","title":"Downstream-Pretext Domain Knowledge Traceback for Active Learning","created":"2024-07-20","cited_by_count":3,"area":null},{"id":"2212.10613","title":"Temporal Output Discrepancy for Loss Estimation-based Active Learning","created":"2022-12-20","cited_by_count":2,"area":null},{"id":"2501.01118","title":"Pruning-based Data Selection and Network Fusion for Efficient Deep Learning","created":"2025-01-02","cited_by_count":2,"area":null},{"id":"2203.06215","title":"Can I see an Example? Active Learning the Long Tail of Attributes and Relations","created":"2022-03-11","cited_by_count":1,"area":null},{"id":"2302.00098","title":"Does Deep Active Learning Work in the Wild?","created":"2023-01-31","cited_by_count":1,"area":null},{"id":"2308.08476","title":"Classification Committee for Active Deep Object Detection","created":"2023-08-16","cited_by_count":1,"area":null},{"id":"2309.16139","title":"Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling","created":"2023-09-28","cited_by_count":1,"area":null},{"id":"2311.02879","title":"Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling","created":"2023-11-06","cited_by_count":1,"area":null},{"id":"2110.11778","title":"Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity","created":"2021-10-22","cited_by_count":0,"area":null},{"id":"2409.15565","title":"Critic Loss for Image Classification","created":"2024-09-23","cited_by_count":0,"area":null},{"id":"2510.22229","title":"Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation","created":"2025-10-25","cited_by_count":0,"area":null},{"id":"2603.26138","title":"PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion","created":"2026-03-27","cited_by_count":0,"area":null}],"next_cursor":null}