{"total":25,"rows":[{"id":"2303.15991","title":"Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks","created":"2023-03-26","cited_by_count":95,"area":null},{"id":"2310.09130","title":"Split-and-Denoise: Protect large language model inference with local differential privacy","created":"2023-10-13","cited_by_count":32,"area":null},{"id":"2304.01829","title":"A Survey on Vertical Federated Learning: From a Layered Perspective","created":"2023-04-04","cited_by_count":30,"area":null},{"id":"2207.09611","title":"Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions","created":"2022-07-20","cited_by_count":14,"area":null},{"id":"2405.17495","title":"Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey","created":"2024-05-25","cited_by_count":14,"area":null},{"id":"2210.15986","title":"Differentially Private CutMix for Split Learning with Vision Transformer","created":"2022-10-28","cited_by_count":13,"area":null},{"id":"2209.15635","title":"Vertical Semi-Federated Learning for Efficient Online Advertising","created":"2022-09-30","cited_by_count":12,"area":null},{"id":"2410.10759","title":"SplitLLM: Collaborative Inference of LLMs for Model Placement and Throughput Optimization","created":"2024-10-14","cited_by_count":11,"area":null},{"id":"2301.07284","title":"Label Inference Attack against Split Learning under Regression Setting","created":"2023-01-18","cited_by_count":8,"area":null},{"id":"2310.09827","title":"VFLAIR: A Research Library and Benchmark for Vertical Federated Learning","created":"2023-10-15","cited_by_count":8,"area":null},{"id":"2311.05739","title":"Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency","created":"2023-11-09","cited_by_count":8,"area":null},{"id":"2402.03688","title":"A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2501.06650","title":"SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)","created":"2025-01-11","cited_by_count":7,"area":null},{"id":"2205.15987","title":"VFed-SSD: Towards Practical Vertical Federated Advertising","created":"2022-05-31","cited_by_count":5,"area":null},{"id":"2302.08618","title":"SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection","created":"2023-02-16","cited_by_count":4,"area":null},{"id":"2303.10624","title":"PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients","created":"2023-03-19","cited_by_count":3,"area":null},{"id":"2409.01661","title":"$S^2$NeRF: Privacy-preserving Training Framework for NeRF","created":"2024-09-03","cited_by_count":2,"area":null},{"id":"2405.17042","title":"LabObf: A Label Protection Scheme for Vertical Federated Learning Through Label Obfuscation","created":"2024-05-27","cited_by_count":1,"area":null},{"id":"2508.10598","title":"Oops!... They Stole it Again: Attacks on Split Learning","created":"2025-08-14","cited_by_count":1,"area":null},{"id":"2606.16801","title":"The Art of Mixology: Mixup-based Obfuscation for Privacy-Preserving Split Learning in Large Language Models","created":"2026-06-15","cited_by_count":1,"area":null},{"id":"2302.02245","title":"GAN-based Vertical Federated Learning for Label Protection in Binary Classification","created":"2023-02-04","cited_by_count":0,"area":null},{"id":"2406.01085","title":"FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation","created":"2024-06-03","cited_by_count":0,"area":null},{"id":"2411.05750","title":"On Differentially Private String Distances","created":"2024-11-08","cited_by_count":0,"area":null},{"id":"2509.14603","title":"Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2604.24468","title":"A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations","created":"2026-04-27","cited_by_count":0,"area":null}],"next_cursor":null}