{"total":58,"rows":[{"id":"2205.00329","title":"Continual Learning with Foundation Models: An Empirical Study of Latent Replay","created":"2022-04-30","cited_by_count":61,"area":null},{"id":"2503.06027","title":"Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models","created":"2025-03-08","cited_by_count":46,"area":null},{"id":"2405.05860","title":"The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels","created":"2024-05-09","cited_by_count":38,"area":null},{"id":"2406.14325","title":"Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers","created":"2024-06-20","cited_by_count":34,"area":null},{"id":"2306.14123","title":"Privacy and Fairness in Federated Learning: on the Perspective of Trade-off","created":"2023-06-25","cited_by_count":26,"area":null},{"id":"2302.03629","title":"Ethical Considerations for Responsible Data Curation","created":"2023-02-07","cited_by_count":17,"area":null},{"id":"2305.07854","title":"A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction","created":"2023-05-13","cited_by_count":12,"area":null},{"id":"2412.01079","title":"Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer Interfaces","created":"2024-12-02","cited_by_count":7,"area":null},{"id":"2312.06718","title":"Large Scale Foundation Models for Intelligent Manufacturing Applications: A Survey","created":"2023-12-11","cited_by_count":6,"area":null},{"id":"2503.07501","title":"Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond","created":"2025-03-10","cited_by_count":6,"area":null},{"id":"2202.07787","title":"Trustworthy Anomaly Detection: A Survey","created":"2022-02-15","cited_by_count":5,"area":null},{"id":"2412.06113","title":"Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions","created":"2024-12-09","cited_by_count":5,"area":null},{"id":"2504.04798","title":"TabRep: Training Tabular Diffusion Models with a Simple and Effective Continuous Representation","created":"2025-04-07","cited_by_count":5,"area":"diffusion"},{"id":"2307.15838","title":"Holistic Survey of Privacy and Fairness in Machine Learning","created":"2023-07-28","cited_by_count":4,"area":null},{"id":"2311.18190","title":"Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning","created":"2023-11-30","cited_by_count":4,"area":null},{"id":"2409.05414","title":"CipherDM: Secure Three-Party Inference for Diffusion Model Sampling","created":"2024-09-09","cited_by_count":3,"area":"diffusion"},{"id":"2412.03824","title":"Towards Data Governance of Frontier AI Models","created":"2024-12-05","cited_by_count":3,"area":null},{"id":"2503.22668","title":"Understanding Co-speech Gestures in-the-wild","created":"2025-03-28","cited_by_count":3,"area":null},{"id":"2504.10036","title":"DataPuzzle: Breaking Free from the Hallucinated Promise of LLMs in Data Analysis","created":"2025-04-14","cited_by_count":3,"area":null},{"id":"2211.05717","title":"Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings","created":"2022-11-10","cited_by_count":2,"area":null},{"id":"2403.02780","title":"Data Collaboration Analysis with Orthonormal Basis Selection and Alignment","created":"2024-03-05","cited_by_count":2,"area":null},{"id":"2403.03592","title":"Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training","created":"2024-03-06","cited_by_count":2,"area":null},{"id":"2410.01386","title":"FLAME: Adaptive and Reactive Concept Drift Mitigation for Federated Learning Deployments","created":"2024-10-02","cited_by_count":2,"area":null},{"id":"2412.15114","title":"Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment","created":"2024-12-19","cited_by_count":2,"area":null},{"id":"2504.03668","title":"Intelligent Orchestration of Distributed Large Foundation Model Inference at the Edge","created":"2025-03-19","cited_by_count":2,"area":null},{"id":"2512.01039","title":"Joint Partitioning and Placement of Foundation Models for Real-Time Edge AI","created":"2025-11-30","cited_by_count":2,"area":null},{"id":"2305.15697","title":"Privacy Protectability: An Information-theoretical Approach","created":"2023-05-25","cited_by_count":1,"area":null},{"id":"2306.03679","title":"Human-imperceptible, Machine-recognizable Images","created":"2023-06-06","cited_by_count":1,"area":null},{"id":"2309.04664","title":"Compact: Approximating Complex Activation Functions for Secure Computation","created":"2023-09-09","cited_by_count":1,"area":null},{"id":"2401.02450","title":"Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems","created":"2024-01-03","cited_by_count":1,"area":null},{"id":"2401.10859","title":"Ensembler: Protect Collaborative Inference Privacy from Model Inversion Attack via Selective Ensemble","created":"2024-01-19","cited_by_count":1,"area":null},{"id":"2409.01329","title":"Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning","created":"2024-09-02","cited_by_count":1,"area":null},{"id":"2410.08299","title":"Privately Learning from Graphs with Applications in Fine-tuning Large Language Models","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2503.16251","title":"RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility","created":"2025-03-20","cited_by_count":1,"area":null},{"id":"2509.25072","title":"Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications","created":"2025-09-29","cited_by_count":1,"area":null},{"id":"2605.27219","title":"Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2608.04366","title":"Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework","created":"2026-08-05","cited_by_count":1,"area":"rag"},{"id":"2205.13265","title":"Privacy-Preserving Wavelet Neural Network with Fully Homomorphic Encryption","created":"2022-05-26","cited_by_count":0,"area":null},{"id":"2208.02587","title":"Privacy-Preserving Chaotic Extreme Learning Machine with Fully Homomorphic Encryption","created":"2022-08-04","cited_by_count":0,"area":null},{"id":"2210.12944","title":"Deep Edge Intelligence: Architecture, Key Features, Enabling Technologies and Challenges","created":"2022-10-24","cited_by_count":0,"area":null},{"id":"2403.15510","title":"Privacy-Preserving End-to-End Spoken Language Understanding","created":"2024-03-22","cited_by_count":0,"area":null},{"id":"2404.13421","title":"MultiConfederated Learning: Inclusive Non-IID Data handling with Decentralized Federated Learning","created":"2024-04-20","cited_by_count":0,"area":null},{"id":"2406.03405","title":"Amalgam: A Framework for Obfuscated Neural Network Training on the Cloud","created":"2024-06-02","cited_by_count":0,"area":null},{"id":"2406.19050","title":"FedMap: Iterative Magnitude-Based Pruning for Communication-Efficient Federated Learning","created":"2024-06-27","cited_by_count":0,"area":null},{"id":"2407.00538","title":"Privacy-Preserving and Trustworthy Deep Learning for Medical Imaging","created":"2024-06-29","cited_by_count":0,"area":null},{"id":"2407.14573","title":"Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization","created":"2024-07-21","cited_by_count":0,"area":null},{"id":"2408.14788","title":"Learning from Complementary Features","created":"2024-08-27","cited_by_count":0,"area":null},{"id":"2411.06995","title":"Which PPML Would a User Choose? A Structured Decision Support Framework for Developers to Rank PPML Techniques Based on User Acceptance Criteria","created":"2024-11-11","cited_by_count":0,"area":null},{"id":"2412.01541","title":"Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning","created":"2024-12-02","cited_by_count":0,"area":"safety"},{"id":"2506.22606","title":"A User-Centric, Privacy-Preserving, and Verifiable Ecosystem for Personal Data Management and Utilization","created":"2025-06-27","cited_by_count":0,"area":null},{"id":"2509.15785","title":"CBPNet: A Continual Backpropagation Prompt Network for Alleviating Plasticity Loss on Edge Devices","created":"2025-09-19","cited_by_count":0,"area":null},{"id":"2510.26841","title":"FedPF: Accurate Target Privacy Preserving Federated Learning Balancing Fairness and Utility","created":"2025-10-30","cited_by_count":0,"area":null},{"id":"2512.18932","title":"DPSR: Differentially Private Sparse Reconstruction via Multi-Stage Denoising for Recommender Systems","created":"2025-12-22","cited_by_count":0,"area":null},{"id":"2603.22987","title":"A Critical Review on the Effectiveness and Privacy Threats of Membership Inference Attacks","created":"2026-03-24","cited_by_count":0,"area":"safety"},{"id":"2604.12335","title":"SynMulti: Synthetic-to-Real Learning for Multimodal Video Understanding","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2608.18749","title":"Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2609.13872","title":"Trustworthy, Explainable, and Sustainable Decentralized Intelligence for 6G Networks","created":"2026-09-12","cited_by_count":0,"area":null},{"id":"2609.21484","title":"HE-Guardrail: A Homomorphic Guardrail Against Jailbreak Attacks for Encrypted Large Language Model Inference","created":"2026-09-18","cited_by_count":0,"area":"safety"}],"next_cursor":null}