{"total":20,"rows":[{"id":"2103.09762","title":"Gradient Projection Memory for Continual Learning","created":"2021-03-17","cited_by_count":348,"area":null},{"id":"2110.08458","title":"Controllable Semantic Parsing via Retrieval Augmentation","created":"2021-10-16","cited_by_count":35,"area":null},{"id":"2201.07705","title":"GEMEL: Model Merging for Memory-Efficient, Real-Time Video Analytics at the Edge","created":"2022-01-19","cited_by_count":32,"area":null},{"id":"2106.07035","title":"Deep Bayesian Unsupervised Lifelong Learning","created":"2021-06-13","cited_by_count":21,"area":null},{"id":"2309.01289","title":"Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning","created":"2023-09-03","cited_by_count":21,"area":null},{"id":"2110.04662","title":"Cognitively Inspired Learning of Incremental Drifting Concepts","created":"2021-10-09","cited_by_count":16,"area":null},{"id":"2403.14353","title":"DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics","created":"2024-03-21","cited_by_count":8,"area":null},{"id":"2104.06476","title":"Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer","created":"2021-04-13","cited_by_count":6,"area":null},{"id":"2107.11359","title":"Rethinking Hard-Parameter Sharing in Multi-Domain Learning","created":"2021-07-23","cited_by_count":6,"area":null},{"id":"2203.13321","title":"Addressing Client Drift in Federated Continual Learning with Adaptive Optimization","created":"2022-03-24","cited_by_count":5,"area":null},{"id":"2202.08700","title":"Detecting and Learning the Unknown in Semantic Segmentation","created":"2022-02-17","cited_by_count":4,"area":null},{"id":"2407.12188","title":"CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning","created":"2024-07-16","cited_by_count":4,"area":null},{"id":"2109.06440","title":"Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems","created":"2021-09-14","cited_by_count":2,"area":null},{"id":"2111.10857","title":"Accretionary Learning with Deep Neural Networks","created":"2021-11-21","cited_by_count":1,"area":null},{"id":"2302.00857","title":"Algorithm Design for Online Meta-Learning with Task Boundary Detection","created":"2023-02-02","cited_by_count":1,"area":null},{"id":"2306.13275","title":"On The Relationship Between Continual Learning and Long-Tailed Recognition","created":"2023-06-23","cited_by_count":1,"area":null},{"id":"2405.01558","title":"Configurable Holography: Towards Display and Scene Adaptation","created":"2024-03-24","cited_by_count":1,"area":null},{"id":"2509.17695","title":"Cluster Workload Allocation: A Predictive Approach Leveraging Machine Learning Efficiency","created":"2025-09-22","cited_by_count":1,"area":null},{"id":"2210.00713","title":"Efficient Meta-Learning for Continual Learning with Taylor Expansion Approximation","created":"2022-10-03","cited_by_count":0,"area":null},{"id":"2408.01331","title":"UnifiedNN: Efficient Neural Network Training on the Cloud","created":"2024-08-02","cited_by_count":0,"area":null}],"next_cursor":null}