{"total":18,"rows":[{"id":"2308.06767","title":"A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations","created":"2023-08-13","cited_by_count":202,"area":null},{"id":"2401.06426","title":"UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer","created":"2024-01-12","cited_by_count":9,"area":null},{"id":"2406.12837","title":"LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging","created":"2024-06-18","cited_by_count":7,"area":null},{"id":"2208.08562","title":"Restructurable Activation Networks","created":"2022-08-17","cited_by_count":6,"area":null},{"id":"2407.11681","title":"MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models","created":"2024-07-16","cited_by_count":5,"area":null},{"id":"2503.16916","title":"Temporal Action Detection Model Compression by Progressive Block Drop","created":"2025-03-21","cited_by_count":5,"area":null},{"id":"2304.13274","title":"Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference","created":"2023-04-26","cited_by_count":4,"area":null},{"id":"2404.08831","title":"Structured Model Pruning for Efficient Inference in Computational Pathology","created":"2024-04-12","cited_by_count":2,"area":null},{"id":"2301.12187","title":"Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming","created":"2023-01-28","cited_by_count":1,"area":null},{"id":"2303.10727","title":"ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement","created":"2023-03-19","cited_by_count":1,"area":null},{"id":"2305.05105","title":"TinyML Design Contest for Life-Threatening Ventricular Arrhythmia Detection","created":"2023-05-09","cited_by_count":1,"area":null},{"id":"2311.17943","title":"LayerCollapse: Adaptive compression of neural networks","created":"2023-11-29","cited_by_count":1,"area":null},{"id":"2607.03784","title":"Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective","created":"2026-07-04","cited_by_count":1,"area":null},{"id":"2411.14345","title":"Layer Pruning with Consensus: A Triple-Win Solution","created":"2024-11-21","cited_by_count":0,"area":null},{"id":"2501.16376","title":"SwiftPrune: Hessian-Free Weight Pruning for Large Language Models","created":"2025-01-24","cited_by_count":0,"area":null},{"id":"2504.19638","title":"LODAP: On-Device Incremental Learning Via Lightweight Operations and Data Pruning","created":"2025-04-28","cited_by_count":0,"area":null},{"id":"2509.08714","title":"Compressing CNN models for resource-constrained systems by channel and layer pruning","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2609.04881","title":"From Deep to Shallow: Unconstrained and Efficient Layer Merging Strategy","created":"2026-09-04","cited_by_count":0,"area":null}],"next_cursor":null}