Search: “privacy”

Protecting Bystander Privacy via Selective Hearing in Audio LLMs

arXiv:2512.06380v3 Announce Type: replace-cross Abstract: Audio Large language models (LLMs) are increasingly deployed in the real world, where they inevitably capture speech from unintended nearby by

22 Apr 2026

Human

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Research

PrivaDE: Privacy-preserving Data Evaluation for Blockchain-based Data Marketplaces

DGX agent

arXiv:2510.18109v4 Announce Type: replace-cross Abstract: Evaluating the usefulness of data before purchase is essential when obtaining data for high-quality machine learning models, yet both model bu

researcharxiv-cs-lg

21 Apr 2026

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy

arXiv:2604.15851v1 Announce Type: cross Abstract: Differential privacy (DP) has a wide range of applications for protecting data privacy, but designing and verifying DP algorithms requires expert-leve

20 Apr 2026

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).

15 Apr 2026

PAC-BENCH: Evaluating Multi-Agent Collaboration under Privacy Constraints

arXiv:2604.11523v1 Announce Type: new Abstract: We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. H

14 Apr 2026

Quotation-Based Data Retention Mechanism for Data Privacy in LLM-Empowered Network Services

arXiv:2503.23001v5 Announce Type: replace Abstract: The deployment of large language models (LLMs) for next-generation network optimization introduces novel data governance challenges. mobile network

14 Apr 2026

Zero-Shot Generative De-identification: Inversion-Free Flow for Privacy-Preserving Skin Image Analysis

arXiv:2602.00821v2 Announce Type: replace Abstract: The secure analysis of dermatological images in clinical environments is fundamentally restricted by the critical trade-off between patient privacy

researcharxiv-cs-cv

13 Apr 2026

Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

model-releasesarxiv-cs-cv

arXiv:2604.07884v1 Announce Type: new Abstract: High-fidelity generative models are increasingly needed in privacy-sensitive scenarios, where access to data is severely restricted due to regulatory an

10 Apr 2026

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation

arXiv:2604.06831v1 Announce Type: cross Abstract: Current LLM-based services typically require users to submit raw text regardless of its sensitivity. While intuitive, such practice introduces substan

safetyarxiv-cs-ai

10 Apr 2026

Industry

Use 𝕏 Chat for messaging and voice/video calls. Comes with this great benefit of actual privacy.

Use 𝕏 Chat for messaging and voice/video calls. Comes with this great benefit of actual privacy. 🚨 WhatsApp’s “end-to-end encrypted” privacy is a total lie. New class-action lawsuit just dropped: Meta

industryelon-musk--x

9 Apr 2026

Reward-Driven Learning under Prompt-Level Differential Privacy

arXiv:2610.07212v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) trains a language model on problems that may themselves be confidential, and the trained model can

7 Oct 2026

Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy

model-releasesarxiv-cs-cv

arXiv:2610.02943v1 Announce Type: new Abstract: Multimodal 3D Human Pose Estimation (3D HPE) combines complementary information from RGB, LiDAR, and mmWave radar, but models trained on correlated obse

5 Oct 2026

PrivMeSA: Privacy-Aware Self-Evolving Multi-Agent System for Medicine via Local-Remote LLM Collaboration

arXiv:2609.38458v1 Announce Type: new Abstract: Clinical large language model (LLM) agents deployed locally can consult more capable remote models, but doing so risks exposing patient information. Pri

1 Oct 2026

Local Ai

Privacy-Friendly Cohort Determination: Sealed, CSP-Independent In-Browser ML Inference of Professional Segments for Identity-Less Advertising

arXiv:2609.36153v1 Announce Type: cross Abstract: B2B advertising targets a viewer's professional attributes (employer size and industry, function, seniority) and has obtained them by matching identit

local-aiarxiv-cs-lg

30 Sept 2026

'We'll Fix It Later': Education, AI, and the Deferral of Privacy in EdTech

arXiv:2609.28137v1 Announce Type: cross Abstract: Educational technology (EdTech) platforms collect highly sensitive student data, including behavioral logs, disability records, and academic histories

safetyarxiv-cs-ai

24 Sept 2026

Learning Defensive Policies against Diverse Inference Attacks for Smart Meter Privacy

arXiv:2609.25484v1 Announce Type: new Abstract: Smart meter (SM) data provides fine-grained visibility into household energy consumption, but also exposes users to privacy risks. Inference attacks, kn

applicationsarxiv-cs-lg

23 Sept 2026

Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning

arXiv:2401.08038v2 Announce Type: replace Abstract: A significant challenge to training accurate deep learning models on privacy policies is the cost and difficulty of obtaining a large and comprehens

safetyarxiv-cs-cl

22 Sept 2026

CIPL: A Channel-Aware Framework for Recoverable Privacy Leakage in LLM Agents

arXiv:2609.21686v1 Announce Type: cross Abstract: Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it diff

safetyarxiv-cs-ai

21 Sept 2026

LLM-Based Schema-Aware Split Learning for Privacy-Preserving Mental Distress Prediction Across Heterogeneous Surveys

arXiv:2609.15871v1 Announce Type: cross Abstract: Rising societal and lifestyle complexity has been linked to a growing prevalence of mental distress worldwide. Educational institutions, workplaces, c

15 Sept 2026

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

arXiv:2609.15950v1 Announce Type: new Abstract: Record-level differential privacy exposes a structural misalignment in personalized federated learning when client-specific variation is low-dimensional

15 Sept 2026

Agents

Privacy Preserving Gossip Learning

arXiv:2609.14778v1 Announce Type: new Abstract: We propose a decentralized privacy-preserving learning algorithm in which each agent holds a single private sample and a shared model. Samples are learn

agentsarxiv-cs-lg

15 Sept 2026

PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning

arXiv:2403.05864v3 Announce Type: replace Abstract: In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cl

14 Sept 2026

Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs

model-releasesarxiv-cs-cl

arXiv:2609.11762v1 Announce Type: new Abstract: Per-layer differential privacy (DP) clipping improves gradient fidelity in federated learning by allocating per-matrix clipping budgets proportional to

11 Sept 2026

Label Differential Privacy via Aggregation

arXiv:2310.10092v4 Announce Type: replace Abstract: This paper explores the use of linear aggregation to protect the privacy of sensitive training labels through the concept of label differential priv

applicationsarxiv-cs-lg

11 Sept 2026

Bayesian Adversarial Privacy

arXiv:2603.04199v2 Announce Type: replace-cross Abstract: Theoretical and applied research into privacy encompasses an incredibly broad swathe of differing approaches, emphases and aims. This work int

10 Sept 2026

Characterizing Privacy-Audit Alignment in Behavioral Audit of Machine Unlearning

arXiv:2606.14518v2 Announce Type: replace Abstract: The removal of learned data from Machine Learning models through Machine Unlearning (MU) has been widely studied; however, there is no agreed-upon s

9 Sept 2026

Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps

arXiv:2609.07623v1 Announce Type: cross Abstract: Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial pattern

applicationsarxiv-cs-cv

9 Sept 2026

Local Ai

Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning

arXiv:2609.02967v1 Announce Type: cross Abstract: Topology-guided safeguards for LLM-based multi-agent systems (MAS) train a GNN over the inter-agent communication graph to localize risky agents and i

local-aiarxiv-cs-ai

4 Sept 2026

Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies

arXiv:2509.10882v2 Announce Type: replace Abstract: In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) syntheti

applicationsarxiv-cs-cl

1 Sept 2026

Memorization Is Not Extraction: Tight Differential-Privacy Bounds and Audit Blind Spots

model-releasesarxiv-cs-cl

arXiv:2608.27782v1 Announce Type: cross Abstract: Memorization in large language models is measured through a zoo of definitions whose formal relations are unknown, and differential privacy (DP) is tr

31 Aug 2026

Provable Privacy Attacks on Trained Shallow Neural Networks

arXiv:2410.07632v3 Announce Type: replace Abstract: We study what provable privacy attacks can be shown for trained 2-layer ReLU neural networks, focusing on two types of attacks: membership inference

safetyarxiv-cs-lg

27 Aug 2026

Quantifying Memorization and Privacy Risks in Genomic Language Models

arXiv:2603.08913v2 Announce Type: replace Abstract: Genomic language models (GLMs) have emerged as powerful tools for learning representations of DNA sequences, enabling advances in variant prediction

19 Aug 2026

PriDyG: Privacy-preserving Dynamic Graph Inference with LLM-GNN Collaboration

arXiv:2608.04255v1 Announce Type: cross Abstract: Graph inference over relational data can expose sensitive edge information, and this risk becomes more severe in dynamic graphs, where repeated model

6 Aug 2026

Robust and Efficient Motion Reasoning for Privacy-Aware Classroom Incident Recognition

arXiv:2608.05115v1 Announce Type: cross Abstract: Can computer vision help make classrooms safer? In this pilot study, we investigate privacy-aware and computationally efficient classroom incident rec

6 Aug 2026

SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant

arXiv:2608.05127v1 Announce Type: cross Abstract: Achieving local differential privacy in distributed optimization while maintaining low communication cost remains challenging. Existing vector quantiz

researcharxiv-cs-ai

6 Aug 2026

End-to-End Differential Privacy in Training Deep Neural Network Classifiers

arXiv:2607.19580v1 Announce Type: new Abstract: Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from

23 Jul 2026

Agents

Predictive single cell foundation model for gene regulation and aging with privacy-preserving tabular learning

arXiv:2607.19400v1 Announce Type: new Abstract: Pre-trained foundation models (FMs) have begun transforming single-cell genomics, but scaling them raises privacy concerns. Moreover, unlike text data,

agentsarxiv-cs-lg

23 Jul 2026

Securing LLMs in the Wild: Privacy and Security Challenges at the Edge

arXiv:2607.13088v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edg

16 Jul 2026

When T2I Synthetic Data Backfires: Amplified Privacy Risks in Real-Synthetic Mix Training

arXiv:2607.13541v1 Announce Type: cross Abstract: To overcome data scarcity and privacy constraints in data collection, it has become standard practice across academia and industry to augment real tra

16 Jul 2026

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

arXiv:2606.26627v1 Announce Type: cross Abstract: Large language model agents increasingly query databases, search document collections, call external APIs, remember past interactions, and act on a us

26 Jun 2026

Natural Identifiers for Privacy and Data Audits in Large Language Models

arXiv:2606.24408v1 Announce Type: new Abstract: Assessing the privacy of large language models (LLMs) presents significant challenges. In particular, most existing methods for auditing differential pr

applicationsarxiv-cs-lg

24 Jun 2026

IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts

arXiv:2606.09908v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming widely deployed as personal AI assistants with access to sensitive user data, making privacy a major challen

10 Jun 2026

P^2RAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top-k Retrieval

arXiv:2603.14778v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to use external knowledge, but outsourcing the RAG service raises privacy c

applicationsarxiv-cs-ai

29 May 2026

Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy

arXiv:2605.28078v1 Announce Type: cross Abstract: We design a class of additive noise mechanisms that satisfy ((arepsilon, elta))-differential privacy (DP) for scalar, real-valued query functions with

researcharxiv-cs-ai

28 May 2026

Local Ai

AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing

arXiv:2605.21421v1 Announce Type: new Abstract: Motion capture is the gold standard for measuring human movement, but clinical use remains limited by cost, technical complexity, and privacy concerns.

local-aiarxiv-cs-cv

21 May 2026

Auditing Privacy in Multi-Tenant RAG under Account Collusion

arXiv:2605.19847v1 Announce Type: cross Abstract: Multi-tenant retrieval-augmented generation (RAG) services advertise per-account differential privacy as the operative leakage boundary: each account'

20 May 2026

Personalized Face Privacy Protection From a Single Image

arXiv:2605.19032v1 Announce Type: new Abstract: Photos of faces uploaded online are vulnerable to malicious actors who can scrape facial images from online sources and intrude on personal privacy via

researcharxiv-cs-cv

20 May 2026

Privacy Preserving Reinforcement Learning with One-Sided Feedback

arXiv:2605.18246v1 Announce Type: cross Abstract: We study reinforcement learning (RL) in multi-dimensional continuous state and action spaces with one-sided feedback, where the agent receives partial