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Period ending 2026-09-21

17 new papers

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15 new papers

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Period ending 2026-09-07

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  1. Quantization in Federated Learning: Methods, Challenges and Future Directions

    Jun 25, 2026Farwa Ikram, Dipanwita Thakur, Antonella Guzzo +1Federated LearningQuantization

  2. Escaping Iterative Parameter-Space Noise: Differentially Private Learning with a Hypernetwork

    Jun 25, 2026Naoki Nishikawa, Shokichi Takakura, Satoshi HasegawaDifferential PrivacyStochastic Gradient Descent

  3. TGHE: Template-based Graph Homomorphic Encryption for Privacy-Preserving GNN Inference in Edge-Cloud Systems

    Jun 25, 2026Ngoc Bao Anh Le, Thai T. Vu, John Le +2Homomorphic EncryptionGraph Neural Networks

  4. Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents

    Jun 25, 2026Nada Lahjouji, Ashwin Gerard ColacoLarge Language Model AgentsAI Privacy Risks and Protection

  5. Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries

    Jun 24, 2026Tânia Carvalho, Maxime CordyTabular Foundation ModelsMembership Inference Attacks

  6. Federated Hash Projected Latent Factor Learning

    Jun 24, 2026Jialan HeFederated LearningAI Privacy Risks and Protection

  7. TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems

    Jun 24, 2026Erdenebileg Batbaatar, Young YoonFederated LearningPrivacy-Preserving Framework

  8. Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems

    Jun 24, 2026Balamurugan Palanisamy, G S S Chalapathi, Vikas Hassija +1Retrieval-Augmented Generation SystemsLarge Language Model Safety

  9. Homomorphic Encryptions for Privacy Preserving Vision

    Jun 23, 2026Preey Shah, Rohan Virani, Sanjari SrivastavaHomomorphic EncryptionGraph Neural Network Inference

  10. Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity

    Jun 23, 2026Yuanhe Zhao, Tianyu Zhang, Huafei Xing +3AI Privacy Risks and ProtectionLarge Language Model Baselines

  11. Natural Identifiers for Privacy and Data Audits in Large Language Models

    Jun 23, 2026Lorenzo Rossi, Bartłomiej Marek, Franziska Boenisch +1Algorithm AuditingAI Privacy Risks and Protection

  12. ComputeFHE: A Privacy-Preserving General-Purpose Computation Library

    Jun 23, 2026Faris Serdar Tasel, Efe CiftciHomomorphic EncryptionDiffie-Hellman

  13. FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters

    Jun 23, 2026Feihong Nan, Zhengyi Zhong, Pan Wang +4Federated LearningPrivacy-Preserving Framework

  14. EmotionAI: A Privacy-Preserving Computational Intelligence Pipeline for Speech-Emotion-Grounded Conversational Analysis

    Jun 22, 2026Wai Laam Mak, Isibor Kennedy Ihianle, Pedro MachadoSpeech EvaluationText Corpora

  15. Privacy-preserving federated tensor decomposition of single-cell immune data: recovering multicellular programs across institutions

    Jun 22, 2026Axel Faes, Stephanie M. van den Berg, Maryam Amir HaeriSingle-Cell Rna SequencingSpatial Transcriptomics

  16. Development and Design of FLKit: A Structured Onboarding Toolkit for Federated Learning in Health and Life Sciences

    Jun 22, 2026Ashkan Pirmani, Ilse Vermeulen, Goran Vinterhalter +7Federated LearningPrivacy-Preserving Framework

  17. Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization

    Jun 22, 2026Raphaël Delécluse, Hazem Wannous, Laurent GuimasRe-IdentificationRgb-Depth Cameras

  18. MuPPET: A Benchmark for Contextual Privacy of LLM Assistants in Multi-Party Conversations

    Jun 22, 2026Elena Sofia Ruzzetti, Cornelius Emde, Sangdoo Yun +2Efficient Privacy LossAI Privacy Risks and Protection

  19. Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy

    Jun 22, 2026Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1MinimaxGeneralized Linear Bandit

  20. FLFL: Federated Latent Factor Learning for Private Recovery of Spatio-Temporal Signals

    Jun 22, 2026Chengjun Yu, Di Wu, Yi He +1Federated LearningPrivacy-Preserving Framework

  21. Towards Robust Personalized Federated Learning: Vulnerability Assessment and Defense Co-Design

    Jun 22, 2026Mingyuan Fan, Cen ChenFederated LearningPrivacy-Preserving Framework

  22. Detecting and Understanding Vulnerabilities in Fully Homomorphic Encryption Frameworks

    Jun 21, 2026Yiteng Peng, Dongwei Xiao, Zhibo Liu +2Homomorphic EncryptionVulnerability Detection & Repair

  23. ππ-RAG: Oblivious Retrieval via Semantic Quantization and Transcendental Addressing for Large Language Models

    Jun 20, 2026Aniket Wattamwar, Mrunal KakirwarPrivacy-Preserving FrameworkExtreme Low-Bit Quantization

  24. On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA

    Jun 20, 2026Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar +1Differential PrivacyPrincipal Component Analysis

  25. From Gradient Clipping to Structural Refinement: Improving DPSGD for Medical Image Segmentation

    Jun 19, 2026Shiva Parsarad, Parth Shandilya, Isabel WagnerMedical Image SegmentationDifferential Privacy

  26. AdaPrivate-TS: Private Thompson Sampling for Contextual Bandits with Privacy Amplification

    Jun 19, 2026Mohammadreza Riyazat, Eranga UkwattaLinear Contextual BanditsThompson Sampling

  27. PrivacyAlign: Contextual Privacy Alignment for LLM Agents

    Jun 19, 2026Manveer Singh Tamber, Abhay Puri, Marc-Etienne Brunet +3Artificial Intelligence AlignmentLarge Language Model Agents

  28. Privacy-Preserving Federated Temporal Graph Learning with Digital Twin--Guided Adaptive Deception for Cyber-Resilient IoMT

    Jun 19, 2026Syed Zeeshan Haider, Anwar Shah, Muneeb Arif +2Internet Of ThingFederated Reinforcement Learning

  29. Federated Temporal Attention Intelligence for Cyber-Resilient IoMT: Lightweight Digital Twins and PPO-Driven Honeypot Deception

    Jun 19, 2026Syed Zeeshan Haider, Anwar Shah, Muneeb Arif +2Internet Of ThingFederated Reinforcement Learning

  30. Enhancing Differentially Private Mechanisms via Empirical Bayes

    Jun 19, 2026Minwoo Kim, Junyong Park, Sungkyu JungDifferential PrivacyBayesian

  31. Predictability as a Fine-Grained Measure for Privacy

    Jun 18, 2026Linda Lu, Karthik SridharanDifferential PrivacyAI Privacy Risks and Protection

  32. Quantum ring all-reduce: communication and privacy advantages for distributed learning

    Jun 18, 2026María Gragera Garcés, Lirandë PiraQuantum AdvantageQuantum Machine Learning

  33. GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI

    Jun 18, 2026Julia Alekseenko, Pietro Mascagni, AI4SafeChole Consortium +1Federated LearningGradient Surgery

  34. Giskard : Byzantine Robust and Confidential Aggregation for Large-Scale Decentralized Learning

    Jun 17, 2026Ousmane Touat, César Sabater, Mohamed Maouche +1Byzantine AttacksHomomorphic Encryption

  35. Private Learning with Public Feature Conditioning

    Jun 17, 2026Shuli Jiang, Walid Krichene, Nicolas MayorazDifferential PrivacyAI Privacy Risks and Protection

  36. What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry

    Jun 17, 2026Zachary P. BradshawFingerprintEquivariant Neural Networks

  37. PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization

    Jun 16, 2026Arshia Ilaty, Hossein Shirazi, Manasi Chitale +5Synthetic Tabular DataPrivacy-Preserving Framework

  38. Security and Privacy Prompts in the Wild: What Users Ask LLMs and How LLMs Respond

    Jun 16, 2026Hobin Kim, Xiaoyuan Wu, Omer Akgul +2Large Language Model ReliabilityChatbots

  39. Differential Privacy of Gaussian Process Posterior Sampling

    Jun 16, 2026Tomasz MaciazekDifferential PrivacyGaussian Process

  40. CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models

    Jun 16, 2026Jeffrey G. Wang, Jason Wang, Marvin Li +1Membership Inference AttacksLanguage Model Evasion Attacks

  41. Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges

    Jun 15, 2026Masoume Gholizade, Fabrizio Ruffini, Pietro Ducange +1Federated LearningExplainable Artificial Intelligence

  42. Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

    Jun 15, 2026Xiaolin Li, Ning Wang, Ninghui Li +1Differential PrivacyFederated Learning

  43. Beyond Weights and Gradients: A Taxonomy of Federated Learning Messages

    Jun 15, 2026Alvaro Javier Vargas Guerrero, Xinguang Wang, Quang Manh Doan +1Federated LearningModel Weights

  44. The Art of Mixology: Mixup-based Obfuscation for Privacy-Preserving Split Learning in Large Language Models

    Jun 15, 2026Chen Chen, Xiang Gao, Xianshun Wang +6Privacy-Preserving FrameworkObfuscation

  45. SoK: Security and Privacy of Foundation-Model-Powered Robots

    Jun 15, 2026Xueluan Gong, Chen Chen, Jinxin Liu +2SecurityRobot Systems

  46. Cross-Silo De-Anonymization Under Local Differential Privacy: Threat Model, Phase Transition, and Coordination Necessity

    Jun 15, 2026Ziniu Liu, Aiping LiDifferential PrivacyAnonymization

  47. TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations

    Jun 15, 2026Rutger Hendrix, Leonardo G. Russo, Concetto Spampinato +2Machine UnlearningSeveral Approximate Unlearning Strategies

  48. Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference

    Jun 15, 2026Alexander Yukhimchuk, Andrey Shulga, Mladen Kolar +1ObfuscationPrivacy-Preserving Framework

  49. FEnc2^2: Unifying Data Packing for Efficient Private Inference via Convolution and Architecture-Aware Fragment Encoding

    Jun 15, 2026Ran Ran, Zhaoting Gong, Nuo Xu +3Homomorphic EncryptionConvolutional

  50. pFedUL: Layer-Aware Federated Unlearning for Personalized Federated Learning

    Jun 15, 2026Zhuodong Liu, Xiangyu Li, Zhihao ZhangFederated LearningFedavg

  51. Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs

    Jun 15, 2026Md Abdullah Al Mamun, Ngoc Phu Doan, Pedram Zaree +2Language Model Evasion AttacksDifferential Privacy

  52. Facial Affect Analysis for Service-Oriented Systems: Advances, Challenges, and Future Visions

    Jun 13, 2026Spyridon Georgiou, Aggelos Psiris, Thomas Lagkas +4MicroservicesSoftware

  53. Behavioral Audit of Machine Unlearning Has a Privacy Cost

    Jun 12, 2026Liou Tang, James Joshi, Ashish KunduMachine UnlearningEfficient Privacy Loss

  54. Securing the Future of IoMT in the Post-Quantum Era: An Edge-Native Federated Learning Approach

    Jun 12, 2026Taym Alshoghri, Deemah H. Tashman, Mohammad Reza Gerami +1Post-Quantum CryptographyFederated Learning

  55. Crypto x AI, AI x Crypto: A Survey

    Jun 11, 2026Sarah Allen, Pranay Anchuri, James Austgen +22BlockchainDiffie-Hellman

  56. FedSPC: Shared Parameter Correction for Personalized Federated Learning

    Jun 11, 2026Kannanthodath Induchoodan Ajay Menon, Christian Prehofer, Yunfei Xu +1Federated LearningPrivacy-Preserving Framework

  57. Disparate Impact in Synthetic Data Generation

    Jun 11, 2026Paul Andrey, Michaël Perrot, Batiste Le Bars +1Synthetic DataDifferential Privacy

  58. A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction

    Jun 11, 2026John Fields, K M Sajjadul Islam, Ruchitha Thota +2Privacy-Preserving FrameworkMachine Learning

  59. Let's Ask Gauss: Improved One-Run Privacy Auditing

    Jun 10, 2026Adya Agrawal, Yu Wei, Jaspal Singh +2Differential PrivacyAI Privacy Risks and Protection

  60. Fed-FBD: Federated Functional Block Diversification for Isolation, Privacy, and Surgical Unlearning

    Jun 10, 2026Weijie Chen, Alan B. McMillanFederated LearningFederated Averaging