Search: “privacy”

Entropy-Punctured Bloom Filters for Memory-Efficient Machine Learning

arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva

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Machine Unlearning for Speech Question Answering in Large Audio-Language Models

DGX agent

arXiv:2609.13195v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently shown strong capabilities in speech understanding and question answering (QA), but they also inherit

safetyarxiv-cs-cl

15 Sept 2026

MoARa: Module-Aware Rank Allocation and Structure-Preserving Decomposition for Low-Rank LLM Pre-training

model-releasesarxiv-cs-cl

arXiv:2609.15037v1 Announce Type: cross Abstract: Low-rank gradient projection reduces the optimizer-state memory cost of large language model (LLM) pretraining, but the steps and wall-clock time need

Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition

arXiv:2601.00900v2 Announce Type: replace-cross Abstract: As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target rec

local-aiarxiv-cs-cv

RA-CoA: Training-free Fashion Image Captioning via Retrieval-Augmented Chain-of-Attributes

arXiv:2609.14100v1 Announce Type: cross Abstract: Fashion Image Captioning (FIC) plays a vital role in enhancing user experience and product search in e-commerce platforms. Unlike natural scene image

applicationsarxiv-cs-ai

Trustworthy Agentic AI: A Comprehensive Cybersecurity and Systems Survey on Threat Landscapes, Defense Architectures, and Open Challenges

arXiv:2609.13731v1 Announce Type: new Abstract: The transition from passive foundation models to autonomous, goal-directed agentic AI systems has introduced unprecedented capabilities by coupling recu

safetyarxiv-cs-ai

unfairly-maligned symbolic AI is about to have its big moment - without formal verification we are screwed.

applicationsgary-marcus--x

unfairly-maligned symbolic AI is about to have its big moment - without formal verification we are screwed. Greg Brockman says OpenAI pointed Astra at its own systems until it ran out of vulnerabiliti

Unsupervised Keypoints for Real-Time Fall Detection: Comparative Analysis Under Real-world Conditions with Predictive Bandwidth Reduction

arXiv:2607.15400v3 Announce Type: replace Abstract: Falls among older adults are a major safety and health-systems challenge, yet continuous in-person monitoring is difficult to sustain across home an

local-aiarxiv-cs-cv

When Malicious Instructions Persist: Persistent Memory Poisoning Attack on Harness-Based Agents

model-releasesarxiv-cs-ai

arXiv:2609.13889v1 Announce Type: cross Abstract: Harness design has transformed the development of LLM-based agents by integrating memory, tool use, and runtime control. However, this design also int

A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data

arXiv:2609.12410v1 Announce Type: new Abstract: Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central

Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

arXiv:2609.12994v1 Announce Type: new Abstract: Heavy-tailed empirical spectral densities of neural-network weight matrices are widely used as diagnostics of implicit self-regularization, but the step

I Am No One: Style-Aware Paraphrasing for Text Anonymization

arXiv:2609.12341v1 Announce Type: new Abstract: Authorship attribution models can re-identify users from seemingly anonymized text by exploiting stable stylistic fingerprints, even after explicit iden

researcharxiv-cs-cl

MPT: Missing Prototype Tracking via Barycentric Reconstruction in Vehicular Federated Learning

arXiv:2609.12771v1 Announce Type: cross Abstract: Cross-vehicle federated learning enables vehicles to collaboratively improve perception models while keeping locally collected driving data private. H

USPLIT-VQA: U-Shaped Split Learning for Visual Question Answering with Contribution-Aware Weighted Aggregation

arXiv:2609.12168v1 Announce Type: new Abstract: Visual Question Answering (VQA) systems, jointly interpreting images and natural language queries, hold significant promise across many domains, yet the

Anyone can get my friend’s real SSN from Claude I'm Terrified of my data in training sets. Emails in databases. iMessages harvested. Cant tr…

Anyone can get my friend’s real SSN from Claude I'm Terrified of my data in training sets. Emails in databases. iMessages harvested. Cant trust the cloud as AI is crazy good at hacking So I built Unde

model-releasesswyx--x

12 Sept 2026

A Dynamic Fusion Large Language Model for Traffic Flow Prediction

arXiv:2609.11314v1 Announce Type: new Abstract: Traffic flow prediction is a core supporting technology for intelligent transportation systems. It uses historical data to infer future traffic dynamics

Cognitive Digital Twins: Ethical Risks and Governance for AI Systems That Model the Mind

arXiv:2606.23094v2 Announce Type: replace-cross Abstract: As AI systems become increasingly persistent and personalized, they make possible a class of technologies that we call cognitive digital twins

agentsarxiv-cs-cl

Distributed Physical Layer Authentication and Collaborative RSMA in Non-Terrestrial Networks via Graph Reinforcement Learning

arXiv:2609.09475v1 Announce Type: cross Abstract: Existing physical-layer authentication (PLA) schemes for non-terrestrial networks (NTNs) often rely on single-anchor verification, lack joint authenti

researcharxiv-cs-ai

LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection

model-releasesarxiv-cs-cl

arXiv:2609.10896v1 Announce Type: new Abstract: Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both

Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning

arXiv:2609.09659v1 Announce Type: new Abstract: Federated learning shares model updates rather than raw data, yet these updates can be inverted to reconstruct the clients' training data. Analytic reco

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these dep

local-aiarxiv-cs-cv

From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining

arXiv:2609.07984v1 Announce Type: new Abstract: Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions

Kernel-Managed Shared Memory for System-Wide Personalization

arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema

Storage-Scalable Progressive Semantic Communication via Knowledge-Base Reuse

arXiv:2609.10112v1 Announce Type: new Abstract: Existing knowledge-base-assisted semantic communication schemes commonly adopt either single knowledge-base quantization (SKBQ) or multi-knowledge-base

Versioned Transitive Dependency-Closure Binding and Operation-Time Effect Governance for Agent Skills: ClosureBound

arXiv:2609.05920v1 Announce Type: cross Abstract: Agent Skills combine instructions with files, packages, tools, models, and services, so operational identity can exceed a signed directory. Recursive

D3ARC: Time-Critical Distributed Disaster Detection for Asynchronous Cooperative Multi-Robot Systems

arXiv:2609.07350v1 Announce Type: cross Abstract: Climate change is increasing the severity and unpredictability of natural disasters. In time-critical crises such as wildfires, traditional monitoring

agentsarxiv-cs-cv

Diffusion Model in Latent Space for Medical Image Segmentation Task

arXiv:2512.01292v4 Announce Type: replace Abstract: Medical image segmentation is crucial for clinical diagnosis and treatment planning. Traditional methods typically produce a single segmentation mas

Improving Federated Graph Recommendation with Semantic Guidance

arXiv:2606.15277v2 Announce Type: replace-cross Abstract: Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning

MSSP: Multi-Scale Spatially-Constrained Partition for Unsupervised Semantic Segmentation of 3D Point Clouds

arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv

applicationsarxiv-cs-cv

Novel Methods for Catheter and Guidewire Segmentation in X-ray Fluoroscopy under a Federated Learning Setting

model-releasesarxiv-cs-cv

arXiv:2609.06876v1 Announce Type: new Abstract: Endovascular procedures rely on real-time manipulation of thin instruments, catheters and guidewires, under X-ray fluoroscopy guidance, where accurate v

Situation Awareness for Intelligent Data Distribution in Connected Vehicles

arXiv:2609.05521v1 Announce Type: cross Abstract: The limitations of on-board sensors and blind spots caused by occlusion cause the reduction of perception quality in autonomous vehicles. In such case

agentsarxiv-cs-cv

TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation

model-releasesarxiv-cs-cv

arXiv:2609.06665v1 Announce Type: new Abstract: Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a shared, under-studied error source: VAE rec

From Matching Models to Recruiting Agents: A Systematized Narrative Review of AI Recruitment Systems, Evaluation, and Governance

arXiv:2609.04286v1 Announce Type: new Abstract: Artificial intelligence in recruitment has shifted the object being automated from profile pairs and ranked lists to multi-stage workflows that retrieve

safetyarxiv-cs-ai

7 Sept 2026

Shadow Queries for Private Retrieval in Vector Databases

arXiv:2609.04767v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on information retrieval (IR) systems, such as Retrieval-Augmented Generation (RAG), to incorporate domai

researcharxiv-cs-ai

7 Sept 2026

Epistemic Warrant for LLM Recommendations: Characterizing the Basis for Reliance When Ground Truth Is Unavailable

arXiv:2609.04127v1 Announce Type: new Abstract: Large language models are increasingly used to support organizational decisions, yet users often lack a principled basis for assessing whether to rely o

local-aiarxiv-cs-ai

KC-Bench: A Dynamic Interactive Benchmark for Evaluating Knowledge Conflicts in LLM Agents

model-releasesarxiv-cs-ai

arXiv:2609.03588v1 Announce Type: new Abstract: As LLMs increasingly act through tools, they must reconcile user instructions, parametric knowledge, and dynamic environmental observations before takin

Portable Causal Fairness Across Synthetic Data Generator Families

arXiv:2609.03180v1 Announce Type: new Abstract: When a statistical agency or regulator releases synthetic data in place of sensitive records, it chooses the generator that produces the table, and can

safetyarxiv-cs-lg

PrivateHub: Contrastive Diffusion Model for Private Sensor-Intensive Environment Data Generation

arXiv:2609.02958v1 Announce Type: cross Abstract: Sensor-intensive environments enable many intelligent services by inferring user applications from heterogeneous data streams. However, not all applic

applicationsarxiv-cs-ai

Speculative Macro Commit for Faster Tool-Using Agents

arXiv:2609.03236v1 Announce Type: new Abstract: Tool-using LLM agents spend wall-clock time not only on model inference but also in serial action--observation turns, where each tool call, environment

Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings

arXiv:2609.03376v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has made dense retrieval over large document collections a standard building block. Organizations increasingly ou

Value-Preserving Architectures for Agentic AI Systems

arXiv:2609.03920v1 Announce Type: new Abstract: The emergence of agentic AI and LLM-based multi-agent systems (MAS) presents unprecedented opportunities for automating complex tasks, while simultaneou

safetyarxiv-cs-ai

Grounded, Compute-Efficient LLM Policy Agents for Energy-Poverty Equity in Physically-Constrained Peer-to-Peer Energy Markets

arXiv:2609.01918v1 Announce Type: new Abstract: Energy poverty is nearly absent from NLP-for-social-good, and the little existing work is either static retrieval/QA or relies on carbon-intensive cloud

local-aiarxiv-cs-cl

3 Sept 2026

Hearing the Whispers: Black-Box Membership Inference Attacks on Finetuned TTS Models

arXiv:2609.01723v1 Announce Type: cross Abstract: Text-to-Speech (TTS) foundation models are increasingly fine-tuned on private datasets to synthesize highly personalized voices, introducing severe pr

3 Sept 2026

Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language

arXiv:2609.02606v1 Announce Type: new Abstract: Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objec

researcharxiv-cs-cl

3 Sept 2026

Bridging Lexical Divergence: LLM-Assisted, Cost-Efficient, Zero-shot Scientific Entity Linking

model-releasesarxiv-cs-cl

arXiv:2609.00228v1 Announce Type: new Abstract: Scientific domain entity linking (EL) differs from general domain EL because mentions and entity names often lack lexical overlap. Another challenge is

Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States

arXiv:2603.03146v2 Announce Type: replace-cross Abstract: Integrated communication and computation (IC^2) has emerged as a new paradigm for enabling efficient edge inference in sixth-generation (6G) n

local-aiarxiv-cs-ai

DNC-IMM: Early Lane-Change Intention Recognition via Neural Calibration Based on Driving Context Information

arXiv:2609.01120v1 Announce Type: cross Abstract: Early recognition of lane-change intention is essential for proactive decision-making in autonomous driving and advanced driver assistance systems. Th

Federated Trust for Embodied Robot Capability Marketplaces

arXiv:2609.00404v1 Announce Type: cross Abstract: Robot capability marketplaces, the 'app store for robot skills,' are emerging as the deployment vector for LLM-driven robot fleets. The default cloud-

local-aiarxiv-cs-ro