#privacy News & Analysis

Secure and Privacy-Preserving Vertical Federated Learning

Cardano’s Midnight Has A Big 180 Days Ahead, Hoskinson Says

This AI Wearable From Ex-Apple Engineers Looks Like an iPod Shuffle

CURE:Circuit-Aware Unlearning for LLM-based Recommendation

Analogical Reasoning as a Doctor: A Foundation Model for Gastrointestinal Endoscopy Diagnosis

Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap

BLK-Assist: A Methodological Framework for Artist-Led Co-Creation with Generative AI Models

Researchers have developed BLK-Assist, a modular framework that enables artists to fine-tune AI diffusion models using their own artwork while maintaining privacy and stylistic control. The system includes three components for concept generation, transparency-preserving assets, and high-resolution outputs, demonstrating a consent-based approach to human-AI collaboration in creative work.

Can LLMs Reason About Attention? Towards Zero-Shot Analysis of Multimodal Classroom Behavior

Researchers developed a privacy-preserving AI system that analyzes classroom videos to understand student engagement using pose detection and gaze tracking, with data processed by the QwQ-32B-Reasoning LLM. The system deletes original video frames and retains only geometric coordinates to comply with FERPA privacy regulations.

Discrete Prototypical Memories for Federated Time Series Foundation Models

Researchers propose FeDPM, a federated learning framework that addresses semantic misalignment issues when using Large Language Models for time series analysis. The system uses discrete prototypical memories to better handle cross-domain time-series data while preserving privacy in distributed settings.

Agentic Federated Learning: The Future of Distributed Training Orchestration

AgentSocialBench: Evaluating Privacy Risks in Human-Centered Agentic Social Networks

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents

Charles Hoskinson Calls Out Influencer Over Midnight Network Bridge Concerns

Charles Hoskinson publicly demanded an apology from crypto influencer ItsDave_ADA following criticism of Midnight Network's one-way bridge design. The dispute has sparked broader debate within the Cardano community about the technical design choices for the upcoming privacy-focused network.

XRP Makes History Again With ZK Privacy Transactions, Here’s The Update

LNVPN Rebrands to Nadanada.me as Privacy Infrastructure Expands with Anonymous eSIMs and Lightning Payments

G-Drift MIA: Membership Inference via Gradient-Induced Feature Drift in LLMs

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification

Reasoning-Driven Synthetic Data Generation and Evaluation

Privacy Guard & Token Parsimony by Prompt and Context Handling and LLM Routing

Early Exiting Predictive Coding Neural Networks for Edge AI

A Step Toward Federated Pretraining of Multimodal Large Language Models

Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism

Towards Emotion Recognition with 3D Pointclouds Obtained from Facial Expression Images