Search: “privacy”

Answer It or Not? Towards Prompt-Adapted Adversarial Images on Vision Language Models

arXiv:2610.16622v1 Announce Type: new Abstract: With the advancement in language modeling, research on adversarial images has recently shifted from image classifiers to vision-language models (VLMs).

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CryoTracer: A Synthetic-to-Real System for Filament Instance Tracing in Cryo-EM

DGX agent

arXiv:2610.18696v1 Announce Type: new Abstract: Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by boun

local-aiarxiv-cs-cv

14 Oct 2026

DT-LoRA: Reaching Beyond the Tangent Space of Low-Rank Adaptation

arXiv:2610.17730v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) often underperforms full fine-tuning. We investigate this performance gap through a tangent-space lens: factorized updates ar

local-aiarxiv-cs-cv

EV-JEPA: Elastic V-JEPA for Any Device and Cross-Device Inference

arXiv:2610.14324v1 Announce Type: new Abstract: Foundation models like V-JEPA are increasingly deployed across a heterogeneous edge-cloud continuum spanning smart glasses, phones, robots, and servers.

local-aiarxiv-cs-cv

inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMs

arXiv:2610.18051v1 Announce Type: new Abstract: This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine

TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks

arXiv:2610.15699v1 Announce Type: new Abstract: Generative modeling for tabular data has advanced to the point where models can synthesize realistic records, recover missing values, and generate sampl

applicationsarxiv-cs-lg

Agentic Large Language Models

arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has

12 Oct 2026

Agentic Peer-to-Peer Networks: From Content Distribution to Capability and Action Sharing

arXiv:2603.03753v2 Announce Type: replace-cross Abstract: The ongoing shift of Artificial Intelligence (AI) from centralized cloud application programming interfaces (APIs) to local inference on edge

12 Oct 2026

Deploying RDMA for Large-Scale Inference and Training Workloads

arXiv:2610.12815v1 Announce Type: new Abstract: RDMA can reduce communication overhead in distributed machine learning systems, but realizing these benefits in production requires more than replacing

12 Oct 2026

Fed-GRPO: Reward-Signal-Driven Federated Group Relative Policy Optimization

arXiv:2610.11502v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL), particularly through Group Relat

9 Oct 2026

Nullify: Null-Space Activation Steering for Training-Free LLM Unlearning

arXiv:2610.10655v1 Announce Type: cross Abstract: Large Language Models (LLMs) inevitably internalize substantial amounts of sensitive or private information during pre-training, while LLM unlearning

9 Oct 2026

Temporal transformer CAN encoder with federated lightweight heads for anomaly detection

arXiv:2610.10613v1 Announce Type: new Abstract: Modern vehicles rely on large numbers of Electronic Control Units (ECUs) that constantly exchange information over the Controller Area Network (CAN) bus

9 Oct 2026

RunningTab: Direct Workspace Interaction with Environment-Side Tabs

model-releasesarxiv-cs-cl

arXiv:2610.10444v1 Announce Type: cross Abstract: Much knowledge work produces new deliverables from files a workspace already holds, and LLM agents are beginning to take such work over. Through direc

8 Oct 2026

Do I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents

arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet stru

DySCo: Dynamic Sharding for Collaborative Edge-Cloud LLM Inference with Depth-Synchronized Batching

arXiv:2610.08268v1 Announce Type: cross Abstract: Pervasive intelligent applications are increasingly deployed on mobile and Internet of Things (IoT) edge devices. Consequently, Large Language Models

Exact Unlearning via Quantized Sufficient Statistics

arXiv:2610.07197v1 Announce Type: new Abstract: Exact unlearning requires a deployed predictor to match one rebuilt without the information named by a deletion request. Existing general-purpose exact

local-aiarxiv-cs-lg

FedDermaSeg: Federated Learning for Dermatological Image Segmentation

arXiv:2610.08574v1 Announce Type: cross Abstract: Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment

Safety

Intersectional Fairness via Mixed-Integer Optimization

arXiv:2601.19595v2 Announce Type: replace-cross Abstract: The deployment of Artificial Intelligence in high-risk domains, such as finance and healthcare, necessitates models that are both fair and tra

safetyarxiv-cs-ai

Protective Perturbations Must Survive the Resize: Scale-Robust Image Immunization against Malicious Editing

arXiv:2610.07464v1 Announce Type: new Abstract: Protective perturbations aim to stop malicious instruction-guided editing of personal photos, but they are optimized and evaluated at the editor's worki

researcharxiv-cs-cv

SIFT: Search Intent-to-Filter Transformer for Multi-Task Personalized Filter Ranking at Airbnb

arXiv:2610.07810v1 Announce Type: new Abstract: Search filters help guests navigate vast catalogs in two-sided marketplaces like Airbnb, and recommending the right filters can meaningfully lift bookin

applicationsarxiv-cs-lg

Beyond the Model: The Critical Role of Data Filtering in Clinical Machine Learning

arXiv:2610.06640v1 Announce Type: new Abstract: Machine learning (ML) studies using clinical data often rely on preprocessing and filtering pipelines before model development. The filtering decisions

Cross-Trait Transfer in Subliminal Learning

arXiv:2610.04260v1 Announce Type: new Abstract: Subliminal learning is a phenomenon where a student language model acquires a teacher model's behavioral traits by training on semantically unrelated ou

MemLeak: Cross-User Semantic Leakage in Multi-Tenant AI Agent Memory

arXiv:2610.04195v1 Announce Type: cross Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface f

Modeling Deletion Requests in Machine Unlearning

arXiv:2610.04310v1 Announce Type: new Abstract: Machine unlearning is seen as a promising approach to enable users to exercise the 'right to erasure' in the context of AI models. We ask how users migh

On the Cardinality of Optimal Representations in the Binary-Source Information Bottleneck

arXiv:2610.06627v1 Announce Type: cross Abstract: The information bottleneck (IB) seeks a representation U of a source X that retains as much information as possible about a target Y, subject to a con

Proxy Confidence: Auditing Black-Box LLM Agents with a Surrogate's Log-Probabilities

arXiv:2610.03894v1 Announce Type: cross Abstract: A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier ch

agentsarxiv-cs-lg

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf

local-aiarxiv-cs-lg

vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models

You May Be Running the Wrong Inception Crop

arXiv:2610.04147v1 Announce Type: new Abstract: A decade after its inception, Inception crop has become the standard crop-based data augmentation method for training deep vision models. Not only is it

LEAP: Learning Efficient Action Proposals For LLM Agents

arXiv:2610.02670v1 Announce Type: cross Abstract: LLM agents are known to be slow in rollouts. An agent completes a task one step at a time. At each step, it reasons and then chooses an action to exec

Multi-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework

arXiv:2606.26567v1 Announce Type: cross Abstract: High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challen

Toward SLM-based agentic task-tool intent matching

arXiv:2610.03213v1 Announce Type: new Abstract: Tool-equipped AI agents use tool calls to access data and act on external systems. Horizontal growth of agentic systems increases the number of these in

ZeBROD: Zero-Retraining Based Recognition and Object Detection Framework

arXiv:2512.04888v4 Announce Type: replace Abstract: Object detection constitutes the primary task within the domain of computer vision. It is utilized in numerous domains. Nonetheless, object detectio

local-aiarxiv-cs-cv

A Verifier Can Leak the Answer: Diagnosability Before Optimization in Closed-Loop Agent Debugging

arXiv:2610.00126v1 Announce Type: cross Abstract: Agent developers increasingly compare prompts, tools, policies, and diagnosis algorithms through simulator-grounded verifiers. A verifier can neverthe

Actions with Receipts: Jointly Binding Claims, Evidence, and Execution for Replayable Tool-Agent Auditing

arXiv:2610.00327v1 Announce Type: cross Abstract: Tool-using agents can expose citations and execution logs while leaving a critical association unaudited: whether the claim shown to a user is the cla

Can AI Oversight Be Zero Knowledge?

arXiv:2610.01995v1 Announce Type: new Abstract: AI systems increasingly produce outputs from confidential data, such as a fitness-for-duty assessment from medical records or the predicted properties o

Federated Agent Optimization

arXiv:2610.01195v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in private environments and accumulate valuable experience from task execution, tool use, feedbac

FedSAP: Federated Learning with Structured Adaptive Partitioning for Multi-Domain Heterogeneous Edge Devices

arXiv:2610.01638v1 Announce Type: new Abstract: Federated learning (FL) on heterogeneous edge devices must jointly accommodate unequal resource budgets and domain-shifted local data. Existing resource

local-aiarxiv-cs-lg

K-Dense BYOK: An Open-Source AI Research Assistant That Runs Locally and Keeps a Hash-Chained Lab Notebook

arXiv:2610.00074v1 Announce Type: new Abstract: K-Dense BYOK (bring your own keys) is a free, open-source AI research assistant for scientists in any field that runs on the researcher's own computer.

Rethinking Data Augmentation under Covariate Shift: Invariant-Guided Diffusion and Prototype Reweighting

arXiv:2610.00873v1 Announce Type: cross Abstract: In many industrial applications, 1) tabular data is scarce and imbalanced and thus requires synthetic expansion; 2) input distributions drift between

SCOPE-AD: Sequential cost-aware ordinal-belief planning with energy-based models for diagnostic agents

arXiv:2610.01278v1 Announce Type: new Abstract: Alzheimer's disease (AD) diagnosis requires sequential evidence acquisition under heterogeneous test costs and patient burden. Fixed-modality predictors

Walking the Embedding Space: Datastore Extraction from Multimodal RAG

arXiv:2610.01871v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (MRAG) has emerged as a reliable and cost-effective technique of grounding the generative capabilities of Mu

applicationsarxiv-cs-ai

A 3GPP-Compliant Benchmark Dataset for RIS-Aided Beyond 5G Networks

arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (

Safety

Aligned Data Can Induce Misalignment via Context Confusion

arXiv:2609.38379v1 Announce Type: new Abstract: Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for prev

safetyarxiv-cs-ai

CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data

arXiv:2609.39124v1 Announce Type: new Abstract: Generative models for tabular data are typically trained separately for each dataset, limiting knowledge transfer and requiring the storage of many spec

applicationsarxiv-cs-lg

Inference-Layer Security: Defending Against Adversarial Inference and Infrastructure Abuse

arXiv:2609.38239v1 Announce Type: cross Abstract: A Technical Report: Operating a large language model (LLM) as a service requires more than inference infrastructure: the provider must also defend aga

NodeGround: A Node Classification Benchmark in the Graph Foundation Model Era

arXiv:2609.39673v1 Announce Type: new Abstract: Can a pretrained graph model replace training and tuning a separate predictor for each dataset? Answering this requires evaluating prediction quality al

RAGScope: A Leakage-Controlled, Cost-Aware Evidence-Gating Protocol for RAG Hallucination Triage

arXiv:2609.39075v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems need inexpensive ways to route generated answers: accept low-risk outputs, review uncertain ones, and res