Search: “privacy”

From Transformers to Weighted Automata: Towards the Verification of Large Language Models

arXiv:2610.04569v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical settings, yet their black-box nature makes it difficult to provide formal gu

safetyarxiv-cs-lg

6 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Private Component-by-Component Learning

DGX agent

arXiv:2610.05102v1 Announce Type: new Abstract: We study differentially private learning problems in the realizable setting, where a hypothesis is specified by k components. A direct iteration of priv

researcharxiv-cs-lg

6 Oct 2026

SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods

arXiv:2610.06334v1 Announce Type: new Abstract: Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation. Image immuni

researcharxiv-cs-cv

6 Oct 2026

Tencent releases Octop, a self-hosted AI assistant

Octop is an open-source, self-hosted AI assistant. Through its multi-agent architecture, it builds an intelligent environment that is both independent and collaborative for teams, families, and indivi

local-air-localllama

6 Oct 2026

A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning

arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only

local-aiarxiv-cs-lg

Agents

Assistant or Actor? Student Trust, Control, and Delegation Regret When Using a General-Purpose AI Agent

arXiv:2607.18257v2 Announce Type: replace-cross Abstract: When AI agents shift from answering questions to taking actions, users face a new problem: deciding what to delegate, to a system whose action

agentsarxiv-cs-ai

Cordial Learning: Distributed Training with Correlated Data

arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent

CSIR: Contextually and Socially Informed Robots for Efficient Person Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2610.02750v1 Announce Type: new Abstract: We address the Person Goal Navigation (PersonNav) problem, enabling robots to search for people under realistic constraints on information accessibility

Mitigating Private Data Leakage in LLMs with Whiteout

arXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit

safetyarxiv-cs-ai

Social bot detection in the age of ChatGPT: Challenges and opportunities

arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c

applicationsarxiv-cs-cl

Speakrail - a low-latency fully-local voice assistant that runs on a single RTX 4090

model-releasesr-localllama

tl;dr: I created a fully-local open-source full-duplex voice agent that rivals GPT-Live on some benchmarks. It uses Voxtral Realtime with a turn-taking head, a microturn-finetuned Gemma 4 12B and Bree

TasteBench: Multimodal Benchmark for Sensory Prediction, from Molecules to Sustainable Foods

arXiv:2610.02599v1 Announce Type: new Abstract: Sustainable protein discovery lacks the fast computational proxies, analogous to molecular docking or density functional theory, that accelerate drug an

When Does Synthetic Relational Data Teach Models to Use Relations? Tracing Predictive Structure from Pretraining Data to Model Behavior

arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus

local-aiarxiv-cs-lg

Agents

Extracted system prompts show Meta's Muse compiles 'a page for every person in the user's life', with facts, history, tips to improve relationships, and more (Wired)

Wired: Extracted system prompts show Meta's Muse compiles “a page for every person in the user's life”, with facts, history, tips to improve relationships, and more — Millions have downloaded Meta's A

agentstechmeme

4 Oct 2026

From 1x3090 to 20 DGX Sparks: my house fuses were the first bottleneck

model-releasesr-localllama

From the first LLaMA 33B I knew I wanted that magic-like intelligence locally, mine, so nobody could take it away when I needed it. I bought a 3090 for my home PC. Then LLaMA 65B appeared and I was

4 Oct 2026

Syntheses

Synthesis: Arxiv-Cs-Ai

synthesisarxiv-cs-aiauto-generated

Auto-generated synthesis of 29846 entries about arxiv-cs-ai

4 Oct 2026

A Framework for Egocentric and Exocentric Procedural Understanding via Temporal Segmentation and Semantic Abstraction

arXiv:2610.00069v1 Announce Type: cross Abstract: Long-horizon ego/exo data contains rich procedural evidence, but are redundant, noisy, and costly to process or retain. We propose a compact framework

Anti-Persona: Disrupting Unauthorized Identity Binding and Recognition in Personalized Vision--Language Models

arXiv:2610.01944v1 Announce Type: new Abstract: Few-shot personalization enables large vision--language models (LVLMs) to learn user-specific visual concepts for applications such as personalized retr

safetyarxiv-cs-cv

Are AI Coders Snitches? An Empirical Study of Pretraining Data Detection on Code Large Language Models

arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod

CalDec v1 - Fully Open Decision Model for Personal Assistants

model-releasesr-localllama

Somebody just released a fully open-source, open-weights decision model that beats Jev! Just kidding, it's me and I this is my first time releasing a public model, recipe and dataset so I am looking f

Causal-Aware Tabular GANs with Reinforcement Learning

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

applicationsarxiv-cs-ai

Counterfactual Auditing of Bias in Open-Source Large Language Models for Clinical Triage

arXiv:2610.01963v1 Announce Type: new Abstract: Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

applicationsarxiv-cs-lg

FedCKA: Representation-Guided Layer Personalization for Federated 3D Perception Across Driving Domains

model-releasesarxiv-cs-cv

arXiv:2610.01510v1 Announce Type: new Abstract: Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, locati

FedMAD: Modulation-Aware Directional Aggregation for Federated Learning in Remote Sensing Image Classification

arXiv:2610.00693v1 Announce Type: new Abstract: Federated learning (FL) has recently attracted increasing attention in remote sensing (RS) since it enables collaborative model training across decentra

safetyarxiv-cs-cv

Latent Information Sharing for Accelerating Federated Learning

arXiv:2610.01126v1 Announce Type: new Abstract: Federated learning (FL) is a communication-efficient distributed learning paradigm. However, client drift remains one of the most critical challenges, h

researcharxiv-cs-lg

Tutorials

On the Relationship between Model Quantization and Model Inversion Attacks

arXiv:2610.00382v1 Announce Type: cross Abstract: Model quantization reduces the numerical precision of neural network weights and activations to lower storage and computational costs. Model inversion

tutorialsarxiv-cs-lg

Partial AUC Maximization from Positive-unlabeled Data

arXiv:2610.00284v1 Announce Type: cross Abstract: The partial area under the receiver operating characteristic curve (pAUC) is an important performance metric for binary classification that summarizes

applicationsarxiv-cs-ai

ReCast: Contract-Preserving Protection for Fixed-Interface Multimodal Reasoning

arXiv:2610.01184v1 Announce Type: cross Abstract: Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive con

The Innocent Courier: Covert Exfiltration Through Legitimate LLM Web Fetching

model-releasesarxiv-cs-lg

arXiv:2610.01768v1 Announce Type: cross Abstract: With the increasing capabilities of Large-Language-Models (LLMs) and LLM-based agents, users are increasingly using them to solve everyday problems, s

Towards a Cloud Fog Edge System for Smart Building

arXiv:2610.01647v1 Announce Type: cross Abstract: In this article, we present our vision and recent advancements toward creating a decentralized system capable of learning from real-time data within b

applicationsarxiv-cs-lg

US authorities arrest a California man suspected of smuggling $300M+ worth of restricted Nvidia AI chips to China via Malaysia and Singapore from 2023 to 2024 (Michael Shepard/Bloomberg)

Michael Shepard / Bloomberg: US authorities arrest a California man suspected of smuggling $300M+ worth of restricted Nvidia AI chips to China via Malaysia and Singapore from 2023 to 2024 — By continu

safetytechmeme

A Reusable Semantic Web Framework for Evidence-Grounded Fundamental Rights Impact Assessments under the EU AI Act

arXiv:2609.39537v1 Announce Type: cross Abstract: The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the

Behavior-Grounded Semantic Enrichment for Financial Fraud Modeling and Reasoning

arXiv:2609.34211v2 Announce Type: replace Abstract: In financial fraud detection, rich semantic context can provide important evidence for transaction behavior modeling and fraud reasoning. However, p

Comparison of techniques for fine-tuning open-weight models for entity extraction from radiology reports

model-releasesarxiv-cs-cl

arXiv:2609.40236v1 Announce Type: new Abstract: Converting free-text radiology reports into structured labels supports cohort building, quality assurance, and monitoring of clinical imaging models, bu

Contrastive Representation Shaping for LLM Unlearning

arXiv:2601.22028v2 Announce Type: replace Abstract: Most LLM unlearning methods aim to approximate retrain-from-scratch behaviors with minimal distribution shift, often via alignment-style objectives

safetyarxiv-cs-lg

Cybersecurity in Edge Computing: A Trust-Aware Federated Hybrid Intrusion Detection Framework

model-releasesarxiv-cs-lg

arXiv:2609.39584v1 Announce Type: cross Abstract: Edge computing has emerged as a critical computing paradigm in modern distributed systems by migrating data processing closer to end users and Interne

Federated Class-Incremental Learning with Hierarchical Generative Prototypes

model-releasesarxiv-cs-lg

arXiv:2406.02447v5 Announce Type: replace Abstract: Federated Learning (FL) aims at unburdening the training of deep models by distributing computation across multiple devices (clients) while safeguar

Persistent Watermarking of Text-to-Image Models

arXiv:2609.39024v1 Announce Type: new Abstract: Text-to-image (T2I) generation is gaining increasing popularity with the general public, motivating the development of reliable mechanisms for copyright

researcharxiv-cs-cv

RAST: Resolution-Aware Privileged Structure Transfer for Low-Resolution Audio Activity Recognition

arXiv:2609.38780v1 Announce Type: cross Abstract: Audio is increasingly used for human activity recognition (HAR) because it captures object interactions, environmental events, and contextual cues in

Robust Wake-Up Word Detection by Two-stage Multi-resolution Ensembles

arXiv:2310.11379v2 Announce Type: replace-cross Abstract: Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient,

local-aiarxiv-cs-cl

Agents

SimTrace: Grounded Multimodal User Trajectories Generation for Online User Modeling

arXiv:2609.38397v1 Announce Type: new Abstract: Virtual clients offer a cost-effective approach to support applications such as A/B testing, recommender system development, and interface evaluation. H

agentsarxiv-cs-ai

TALK-Dem: Benchmarking Embodied Task Planning under Dementia-Associated Communication Patterns

model-releasesarxiv-cs-cl

arXiv:2609.38371v1 Announce Type: cross Abstract: Existing LLM-driven robot task planners rely on a taken-for-granted assumption of an ideal user whose instructions are clear, complete, and task-focus

An Empirical Study and Assessment of EU AI Act Compliance Checkers

arXiv:2609.36228v1 Announce Type: new Abstract: The EU AI Act introduces extensive compliance requirements for organizations that develop, deploy, or integrate AI systems. Many of these requirements a

safetyarxiv-cs-ai

Governing the Edge: Automating Commercial Property and Casualty Insurance Underwriting via a Hybrid Local-Cloud Multi-Agent Framework

arXiv:2609.37454v1 Announce Type: new Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a s

I love decision models popularized by @typesafeai 's JEV but I also want to run it locally, especially for sensitive info. So as soon as @ol…

The user expresses enthusiasm for the decision‑modeling approach introduced by @typesafeai’s JEV tool, emphasizing a preference for local deployment to protect sensitive data. After learning that @oll

local-aiollama--x

Understanding Private Evolution as Learning-Augmented Clustering

arXiv:2609.36678v1 Announce Type: new Abstract: Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm,

researcharxiv-cs-lg

Using AFM 3 PCC as an alternative to Local LLM

Apple Foundation Model 3 through Private Cloud Compute is directly available in macOS 27.2 through familiar AI clients. For Mac users running local models such as Qwen 3.x or Gemma 4, AFM 3 PCC is a c

model-releasesr-ollama