Search: “privacy”

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

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

DGX agent

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

9 Sept 2026

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

model-releasesarxiv-cs-lg

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

model-releasesarxiv-cs-lg

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

The case for boycotting Generative AI: https://garymarcus.substack.com/p/the-case-for-boycotting-generative

Gary Marcus argues that current generative‑AI models fail to meet basic standards of reliability because they routinely hallucinate facts, amplify existing biases, and provide no transparent audit tra

safetygary-marcus--x

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

agentsarxiv-cs-ai

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

Qwen3.8 27b for agentic coding and next .... what?

model-releasesr-localllama

First, I'd like to thank the Qwen and Unsloth teams for the Qwen3.8 27b UD Q4_K_XL. Fits the poor 24GB of 3090 VRAM with 100k context at Q8 and works phenomenally well! Imho if theres anything that ca

5 Sept 2026

What to expect at Workiva’s Amplify event: Join theCUBE Sept. 15–16

As companies entrust more responsibility to artificial intelligence, managing governance and regulatory reporting becomes even more essential. Workiva Inc.’s platform provides AI-powered collaboration

agentssiliconangle

5 Sept 2026

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

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

arXiv:2609.03095v1 Announce Type: cross Abstract: Smartphone skin photographs are indispensable to teledermatology, yet assessing the diagnostic suitability of submitted cases (gradability) remains a

researcharxiv-cs-cv

Federated Causal Discovery via Regression-Directed Cumulants

arXiv:2609.03705v1 Announce Type: new Abstract: In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Marko

FedPS: Federated Preprocessing for structured data via aggregated Statistics

arXiv:2602.10870v2 Announce Type: replace-cross Abstract: Federated Learning (FL) enables multiple parties to collaboratively train machine learning models without sharing raw data. However, before tr

Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluation

arXiv:2609.03727v1 Announce Type: new Abstract: Large language model agents can plan, invoke tools, and modify external states, yet most systems still take an explicit user instruction as a fixed star

safetyarxiv-cs-ai

RL-ADA: A World-Feedback Framework for Adversarially Robust Enterprise Dialogue Agents

arXiv:2609.02902v1 Announce Type: new Abstract: Deploying task-oriented dialogue agents in enterprise customer support faces a persistent annotation bottleneck: robust training requires labelled inter

agentsarxiv-cs-cl

Context Inference Attacks Without Jailbreaks

arXiv:2609.01663v1 Announce Type: cross Abstract: Agentic AI systems are increasingly deployed to process sensitive data at inference time, such as healthcare records or financial documents assembled

agentsarxiv-cs-lg

Efficient GUI Agents: A Systems Survey of Observation, Memory, Action, and Runtime Optimization

model-releasesarxiv-cs-cl

arXiv:2609.02309v1 Announce Type: new Abstract: GUI agents increasingly operate across websites, mobile apps, and desktop environments, yet the field still reports progress primarily through task succ

Federated LoRA Adaptation of BiomedCLIP Across Four International Chest X-Ray Cohorts

arXiv:2609.02101v1 Announce Type: cross Abstract: Federated learning (FL) lets institutions train a shared model without exchanging data, and Low-Rank Adaptation (LoRA) makes this practical at scale b

Test-Time Logit Prompting for Source-Free Missing Modality Adaptation

arXiv:2609.02039v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable performance by leveraging complementary information from large-scale image-text pairs. However, m

applicationsarxiv-cs-cv

WiFlow: Estimating Optical Flow using WiFi Channel State Information

arXiv:2609.02452v1 Announce Type: new Abstract: Knowing where and how fast objects are moving within a scene is important across various domains. Usually, cameras are used to capture the data necessar

researcharxiv-cs-cv

Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

arXiv:2609.01818v1 Announce Type: cross Abstract: The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the cl

local-aiarxiv-cs-ai

Tutorials

A Network Science Perspective on Evaluating Deep Graph Generative Models

arXiv:2609.01015v1 Announce Type: cross Abstract: Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selecte

tutorialsarxiv-cs-ai

An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics

arXiv:2609.00846v1 Announce Type: new Abstract: The rising prevalence of psychological disorders necessitates effective emotion monitoring, yet current methods relying on facial or physiological signa

local-aiarxiv-cs-cv

Assessing Suicide Risk in Arabic Crisis Helpline Calls: A Comparison of Arabic and English Large Language Models

arXiv:2609.00191v1 Announce Type: cross Abstract: Crisis helplines assess suicide risk through structured interviews, a process that is slow and dependent on operator training and workload. Natural la

local-aiarxiv-cs-ai

Hardware

Closing Cost-Quality Gap in Document VLMs: Difficulty-Aware Data Curation and Quality-Adjusted Deployment Economics

arXiv:2609.01575v1 Announce Type: new Abstract: Extracting structured fields from hundreds of millions of documents annually remains costly in regulated industries: bespoke OCR cascades cover only a f

hardwarearxiv-cs-cl

Confess What You Know: Forget-Set Misalignment with Model Knowledge in LLM Unlearning

arXiv:2609.00605v1 Announce Type: cross Abstract: Machine unlearning for large language models (LLMs) often assumes that a pre-defined forget set matches what the model has memorized, but this frequen

applicationsarxiv-cs-ai

Differentially Private Paired Table-Image Multimodal Synthesis

arXiv:2609.00708v1 Announce Type: cross Abstract: Differentially private (DP) synthesis has been extensively studied for tabular and image data separately, yet many real-world datasets contain images

safetyarxiv-cs-ai

Do LLMs Know Your Neighborhood? Auditing LLM Priors for Neighborhood-Level Mobility Prediction and Structural Alignment

arXiv:2609.00345v1 Announce Type: new Abstract: Human mobility is central to urban planning, transportation, public health, and emergency response, yet fine-grained trajectory data are often proprieta

safetyarxiv-cs-lg

From metal to model: Private cloud gets an assembly line for production AI

Enterprises moving artificial intelligence from pilot projects into production are discovering that the hard part is no longer the model. It’s the infrastructure beneath it. Cost, tokenomics, data pri

applicationssiliconangle

Incremental Risk Assessment of Progressive Elder Financial Scams via Instruction-Tuned Small Language Models

arXiv:2609.00005v1 Announce Type: new Abstract: Financial scams targeting older adults increasingly occur through text and voice channels such as email, SMS, and phone calls, unfolding over multiple c

The Curse of Multilinguality in Lexical Normalization

arXiv:2609.00329v1 Announce Type: cross Abstract: Lexical normalization rewrites the noisy, non-standard words that fill user-generated text (tmrw, u, gr8) into their standard forms. Because labelled

User Representation via Cross Multi-source Behavior Pre-training for Mobile Games

arXiv:2609.01057v1 Announce Type: new Abstract: User representation pre-training has become a fundamental paradigm for alleviating data sparsity in downstream personalization tasks. However, existing

applicationsarxiv-cs-ai

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs

arXiv:2502.10673v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has become an effective method for enhancing large language models (LLMs) with up-to-date knowledge. Howe

researcharxiv-cs-cl

DIASENTINEL: An Auditable Multi-Agent System for Guideline-Grounded Diabetes Risk Screening

arXiv:2608.31128v1 Announce Type: new Abstract: Large language models (LLMs) offer promising clinical decision support but remain vulnerable to hallucinated facts, unsupported recommendations, and cit

agentsarxiv-cs-cl

Facts Without Rules: Boundary Metadata Collapse in Multi-Agent LLM Handoffs

arXiv:2608.29028v1 Announce Type: new Abstract: Multi-agent LLM systems often coordinate by compressing an upstream interaction into a handoff artifact that downstream agents treat as shared state. We

Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multipliers

arXiv:2608.29388v1 Announce Type: cross Abstract: Recent machine learning research has increasingly focused on equilibrium analysis in non-cooperative games rather than solely on optimal solutions. Ma

GeoAgent: Evaluating VLM Geolocalization Through Embodied Navigation

model-releasesarxiv-cs-cl

arXiv:2608.29483v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) perform well above the human baseline in image geolocalization, a task critically important in disaster response,