{"total":13,"rows":[{"id":"2104.08378","title":"Accelerating Sparse Deep Neural Networks","created":"2021-04-16","cited_by_count":223,"area":null},{"id":"2103.06460","title":"Recent Advances on Neural Network Pruning at Initialization","created":"2021-03-11","cited_by_count":41,"area":null},{"id":"2203.04248","title":"Dual Lottery Ticket Hypothesis","created":"2022-03-08","cited_by_count":27,"area":null},{"id":"2301.05219","title":"Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning","created":"2023-01-12","cited_by_count":16,"area":null},{"id":"2107.14444","title":"Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN","created":"2021-07-30","cited_by_count":9,"area":null},{"id":"2412.00143","title":"Is Oracle Pruning the True Oracle?","created":"2024-11-28","cited_by_count":7,"area":null},{"id":"2403.07688","title":"Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons","created":"2024-03-12","cited_by_count":6,"area":null},{"id":"2303.09736","title":"Dynamic Structure Pruning for Compressing CNNs","created":"2023-03-17","cited_by_count":5,"area":null},{"id":"2105.01064","title":"Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems","created":"2021-05-04","cited_by_count":3,"area":null},{"id":"2105.05916","title":"Dynamical Isometry: The Missing Ingredient for Neural Network Pruning","created":"2021-05-12","cited_by_count":2,"area":null},{"id":"2501.13439","title":"One-Cycle Structured Pruning via Stability-Driven Subnetwork Search","created":"2025-01-23","cited_by_count":1,"area":null},{"id":"2310.03424","title":"Neural Language Model Pruning for Automatic Speech Recognition","created":"2023-10-05","cited_by_count":0,"area":null},{"id":"2507.14170","title":"Catalyst: a Novel Regularizer for Structured Pruning with Auxiliary Extension of Parameter Space","created":"2025-07-10","cited_by_count":0,"area":null}],"next_cursor":null}