{"total":19,"rows":[{"id":"2405.01745","title":"Large Language Models for UAVs: Current State and Pathways to the Future","created":"2024-05-02","cited_by_count":33,"area":null},{"id":"2309.07438","title":"Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges","created":"2023-09-14","cited_by_count":14,"area":null},{"id":"2308.11223","title":"LDP-Feat: Image Features with Local Differential Privacy","created":"2023-08-22","cited_by_count":10,"area":null},{"id":"2110.02329","title":"Task-aware Privacy Preservation for Multi-dimensional Data","created":"2021-10-05","cited_by_count":5,"area":null},{"id":"2204.12064","title":"PP-MARL: Efficient Privacy-Preserving Multi-Agent Reinforcement Learning for Cooperative Intelligence in Communications","created":"2022-04-26","cited_by_count":3,"area":null},{"id":"2111.14789","title":"Dynamic Network-Assisted D2D-Aided Coded Distributed Learning","created":"2021-11-26","cited_by_count":2,"area":null},{"id":"2207.13741","title":"Differentially Private Learning of Hawkes Processes","created":"2022-07-27","cited_by_count":1,"area":null},{"id":"2308.09902","title":"DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning","created":"2023-08-19","cited_by_count":1,"area":null},{"id":"2410.03546","title":"Multidimensional Human Activity Recognition With Large Language Model: A Conceptual Framework","created":"2024-09-16","cited_by_count":1,"area":null},{"id":"2410.06878","title":"Noise is All You Need: Private Second-Order Convergence of Noisy SGD","created":"2024-10-09","cited_by_count":1,"area":null},{"id":"2502.10552","title":"Synthesis of Dynamic Masks for Information-Theoretic Opacity in Stochastic Systems","created":"2025-02-14","cited_by_count":1,"area":null},{"id":"2505.19119","title":"CloneShield: A Framework for Universal Perturbation Against Zero-Shot Voice Cloning","created":"2025-05-25","cited_by_count":1,"area":null},{"id":"2202.08309","title":"Contextualize differential privacy in image database: a lightweight image differential privacy approach based on principle component analysis inverse","created":"2022-02-16","cited_by_count":0,"area":null},{"id":"2205.09453","title":"Differential Privacy: What is all the noise about?","created":"2022-05-19","cited_by_count":0,"area":null},{"id":"2211.00735","title":"TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments","created":"2022-11-01","cited_by_count":0,"area":null},{"id":"2306.15865","title":"Differentially Private Distributed Estimation and Learning","created":"2023-06-28","cited_by_count":0,"area":null},{"id":"2312.02400","title":"DP-SGD-Global-Adapt-V2-S: Triad Improvements of Privacy, Accuracy and Fairness via Step Decay Noise Multiplier and Step Decay Upper Clipping Threshold","created":"2023-12-05","cited_by_count":0,"area":null},{"id":"2407.15868","title":"A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research","created":"2024-07-18","cited_by_count":0,"area":null},{"id":"2602.13529","title":"SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs","created":"2026-02-13","cited_by_count":0,"area":null}],"next_cursor":null}