Search: “privacy”

Pseudo-Label Augmentation for Affect Sensing in Small Collaborative Groups

arXiv:2609.16077v1 Announce Type: cross Abstract: Physiological affect sensing in naturalistic group interaction is often limited by sparse labels rather than sensor data: wearable devices produce man

16 Sept 2026

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StackTok: Accelerating VLMs Inference with Budget-Adaptive Visual Token Selection

DGX agent

arXiv:2609.16841v1 Announce Type: cross Abstract: Increasing image resolution produces ever-longer visual-token sequences in vision-language models (VLMs), substantially raising their inference cost.

local-aiarxiv-cs-ai

16 Sept 2026

Disparate Impact in Synthetic Data Generation

arXiv:2606.13105v2 Announce Type: replace Abstract: We revisit the fairness notion of disparate impact for synthetic data generation (SDG), that assesses whether the utility of generated records is th

safetyarxiv-cs-lg

EdgeHAR: An Edge-Native Compact Sensor Foundation Model for Human Activity Recognition

arXiv:2609.14498v1 Announce Type: cross Abstract: Sensor-based human activity recognition (HAR) is fundamental to ubiquitous and wearable computing, yet existing foundation models are largely designed

applicationsarxiv-cs-ai

FLoKD: Adaptive Knowledge Distillation for Federated Low-Rank LLM over Wireless Networks

model-releasesarxiv-cs-ai

arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-

Governing at Machine Speed: An Adaptive Intelligence Architecture for Real-Time AI Policy Enforcement

arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifie

LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions

arXiv:2609.14849v1 Announce Type: cross Abstract: We characterize how people are turning to LLMs as oracles: all-knowing authorities on subjective personal questions. Motivated by risks to users' auto

OrchSLM: Probing the Dynamics of Small Language Model Orchestration

arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challeng

Personalizing Personal Health Interfaces: Co-Design with Generative AI

arXiv:2609.15046v1 Announce Type: cross Abstract: Personal health interfaces present wellbeing data through standardized dashboards that rarely fit how people interpret or act on it. Personalizing the

Scalability and Performance Evaluation of Federated Learning Frameworks: A Comparative Analysis

arXiv:2609.15681v1 Announce Type: cross Abstract: This paper presents a systematic examination and experimental comparison of the prominent Federated Learning (FL) frameworks FedML, Flower, Substra, a

applicationsarxiv-cs-ai

Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity?

arXiv:2606.23189v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-appli

safetyarxiv-cs-cl

14 Sept 2026

Correlation-Guided Fast Machine Unlearning via Hessian Analysis

arXiv:2609.12620v1 Announce Type: new Abstract: The increasing adoption of machine learning in network and distributed security systems has created an urgent need for mechanisms that can selectively a

14 Sept 2026

Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation

arXiv:2607.18029v2 Announce Type: replace-cross Abstract: Researchers need to answer ad-hoc questions about the contents of domain-specific archives but often lack the expertise to write structured qu

12 Sept 2026

A Short Survey of Viewing Large Language Models in Legal Aspect

arXiv:2303.09136v2 Announce Type: replace Abstract: Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These

safetyarxiv-cs-cl

Artificial Intelligence Algorithms for the Detection of Pathologies Related to Lung Cancer through Image Analysis using Convolutional Neural Networks and Data Augmentation: a systematic mapping of the literature

arXiv:2609.10652v1 Announce Type: cross Abstract: Lung cancer is one of the leading causes of death worldwide, and its early diagnosis is crucial to improving patients prognosis and quality of life. H

researcharxiv-cs-cl

AUC Maximization from Biased Positive-unlabeled Data with Confidence

arXiv:2609.10928v1 Announce Type: new Abstract: Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced binary classification. Although positiv

safetyarxiv-cs-lg

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

arXiv:2609.09647v1 Announce Type: new Abstract: Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding th

EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

arXiv:2609.11058v1 Announce Type: new Abstract: Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogen

Local Ai

A Trust-Network-Based Federated Learning Framework for Multi-Center Aging Clock Prediction

arXiv:2609.10108v1 Announce Type: new Abstract: Aging clocks quantify biological aging and help characterize individual health status. What protein interactions are important for accurate aging clocks

local-aiarxiv-cs-lg

Algorithmic stability via ensembling

arXiv:2609.10428v1 Announce Type: cross Abstract: Algorithmic stability refers to the property of an algorithm being insensitive to perturbations of the input data, where the type of perturbation may

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2506.10633v2 Announce Type: replace Abstract: Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent years. In the domain of natural (RGB) images, recent

Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking

arXiv:2609.09536v1 Announce Type: cross Abstract: Average treatment effect (ATE) estimation in observational studies is a fundamental statistical tool used frequently in social science, medicine, and

safetyarxiv-cs-lg

Influence-Oriented Personalized Federated Learning

arXiv:2410.03315v2 Announce Type: replace Abstract: Federated learning (FL) is a machine learning paradigm where clients with different behaviors and preferences can learn collaboratively without comp

Intent Drift at SME Scale: Deployment Practice, Not Model Capability, Determines Agentic Compliance

arXiv:2609.05975v1 Announce Type: cross Abstract: We introduce Chain of Intent, a governance framework for agentic AI at small regulated firms, and validate it against a failure it was built to addres

LatentDx: Latent Multi-Agent Communication for Cross-Hospital Rare-Disease Diagnosis

model-releasesarxiv-cs-cl

arXiv:2606.13945v2 Announce Type: replace Abstract: Rare diseases affect over 300 million patients across more than 7{,}000 conditions, yet no single hospital encounters enough cases of any one condit

Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services

model-releasesarxiv-cs-cl

arXiv:2609.09889v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR mo

Mapping the Emerging Social Science of Large Language Models

arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d

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OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis

arXiv:2609.10364v1 Announce Type: new Abstract: Simultaneous assessment of medical imaging and patient records is often required in clinical diagnosis. However, standard machine learning algorithms ca

local-aiarxiv-cs-lg

The Mutations of Machine Speech

arXiv:2609.09496v1 Announce Type: new Abstract: Algorithmic outputs now populate the digital environments through which contemporary life is organized. The role of law in facilitating and constituting

applicationsarxiv-cs-cl

Typed Federated Artifacts for the Agentic Web:Sharing Tool-Routing Knowledge Across Frozen,Heterogeneous LLM Agents

model-releasesarxiv-cs-ai

arXiv:2609.06815v1 Announce Type: cross Abstract: An open, networked web will allow agents to run frozen models from multiple vendors, keep their history private, and teach each other which tool to ca

Tutorials

A Specialized Large Multimodal Model for Interpreting PET/CT in Head and Neck Cancer

arXiv:2609.05532v1 Announce Type: new Abstract: Background: Diagnosing head and neck cancer using PET/CT is clinically challenging and time-consuming due to the anatomical complexity of the region, mo

tutorialsarxiv-cs-cv

Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generation

arXiv:2609.06218v1 Announce Type: new Abstract: Automatic skeleton generation involves predicting both joint positions and skeletal connectivity. However, existing approaches struggle to encode branch

researcharxiv-cs-cv

Diffusion models for eye-gaze trajectory generation using position and velocity representations

arXiv:2609.05522v1 Announce Type: new Abstract: Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of priva

researcharxiv-cs-cv

Tutorials

Geographically Regularized AUC-Maximizing Personalized Federated Learning

arXiv:2609.08379v1 Announce Type: new Abstract: Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks. However, priva

tutorialsarxiv-cs-lg

GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2512.15560v3 Announce Type: replace Abstract: The text encoder is a critical component of text-to-image and text-to-video diffusion models, fundamentally determining the semantic fidelity of the

Input-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensus

arXiv:2609.06983v1 Announce Type: cross Abstract: Generalized Nash Equilibrium Problems (GNEPs) often arise in multi-agent engineering applications that require distributed algorithms. Unlike traditio

agentsarxiv-cs-lg

On-the-go Forgetting without Explicit Unlearning via ERASE

arXiv:2609.05966v1 Announce Type: new Abstract: Existing unlearning approaches typically rely on post hoc weight adaptation or distillation, leading to duplicated memory costs, degraded generalization

Remove360: Benchmarking Residuals After Object Removal in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2508.11431v3 Announce Type: replace Abstract: An object can disappear from a 3D scene, yet still be detectable. Even after visual removal, modern vision models may infer what was originally pres

Tempora-Fusion: Time-Lock Puzzle with Efficient Verifiable Homomorphic Linear Combination

arXiv:2406.15070v3 Announce Type: replace-cross Abstract: We present Tempora-Fusion, the first homomorphic TLP scheme with efficient public verification of both individual puzzle solutions and homomor

Topological Fraud Detection in Latent Transaction Spaces

arXiv:2609.08445v1 Announce Type: new Abstract: Working entirely on topologically anonymized embeddings, we perform fraud detection using iterative rounds of unsupervised filtering followed by supervi

A Roadmap for MEG Foundation Models

arXiv:2609.04461v1 Announce Type: cross Abstract: Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific decoding pipelines toward reusable models pr

Client-Side Probing of Deleted Ridge Statistics in Federated Unlearning

arXiv:2609.04475v1 Announce Type: cross Abstract: Federated unlearning aims to remove a client's data from a shared model without retraining from scratch. Some efficient systems make deletion exact by

Conformal Prediction for Offensive Security

arXiv:2609.05165v1 Announce Type: cross Abstract: Despite its introduction more than a quarter century ago, Conformal Prediction (CP) has seen surprisingly few applications to the cyber security world

Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges

arXiv:2609.04778v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer a non-autoregressive alternative for mobile edge agentic artificial intelligence (AI) by refining tokens through

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FedDRAW: Federated Dual Reputation Annealing Weighting for Heterogeneous Multi-Institutional Chest Radiograph Classification

arXiv:2609.05223v1 Announce Type: new Abstract: Artificial intelligence models are promising for medical diagnosis, but they require large numbers of unbiased data, which in medicine are distributed a

local-aiarxiv-cs-lg

Qlippy: A Retrieval-Augmented GenAI Assistant for Reproducible Quantum Workflows and Experiment Tracking

arXiv:2609.05039v1 Announce Type: cross Abstract: Quantum software development is iterative and error-prone. Noisy hardware and repeated re-execution make experiment tracking, provenance, and reproduc

An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data

arXiv:2609.03505v1 Announce Type: new Abstract: Anomaly detection in Internet of Things (IoT) networks presents unique challenges due to the diversity of devices, lack of labeled data, and domain vari

applicationsarxiv-cs-lg

4 Sept 2026

Beyond Blur: A Semantic Tri-view Pipeline for Teledermatology Gradability via Skin Micro-relief