Search: “privacy”

STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media

arXiv:2605.25162v1 Announce Type: cross Abstract: Large language models for vertical domains are bottlenecked by the scarcity of complex, domain-specific task-oriented dialogues. Existing data acquisi

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The Model Is Not the Product: A Dual-Pillar Architecture for Local-First Psychological Coaching

DGX agent

arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe

model-releasesarxiv-cs-ai

26 May 2026

Towards Large Model Feature Coding

arXiv:2605.24025v1 Announce Type: cross Abstract: Large models have delivered remarkable performance across a wide range of perception and generation tasks, yet practical deployment is increasingly co

Trade-off Functions for DP-SGD with Subsampling based on Random Shuffling: Tight Upper and Lower Bounds

arXiv:2605.06259v2 Announce Type: replace Abstract: We derive a tight analysis of the trade-off function for Differentially Private Stochastic Gradient Descent (DP-SGD) with subsampling based on rando

Transformer-based few-shot learning for modeling Electricity Consumption Profiles with minimal data across thousands of domains

arXiv:2408.08399v3 Announce Type: replace Abstract: Electricity Consumption Profiles (ECPs) are crucial for operating and planning power distribution systems, especially with the increasing number of

TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks

arXiv:2605.23988v1 Announce Type: cross Abstract: Adapting large AI models (LAMs) to personalized edge data is challenging because wireless devices have limited memory, computation, and uplink capacit

Android app Ollama Talk now on playstore

Ollama Talk is an Android app that connects to an Ollama server, enabling conversations with AI models like Llama and Mistral . The app features an intuitive chat interface with real-time conversation

local-air-ollama

Call for Papers - Workshop on Unlearning and Model Editing U&ME at ECCV 2026 [R]

researchr-machinelearning

This call for papers announces a workshop focused on the growing need for efficient and effective techniques for editing trained models, especially large generative models. The workshop solicits paper

Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs

model-releasesarxiv-cs-cl

arXiv:2605.22971v1 Announce Type: new Abstract: Employees often struggle to identify ``who knows what,'' leading to organizational productivity losses. We investigate whether Large Language Models (LL

Diffusion and Flow Matching Models for Tabular Data: A Survey

arXiv:2502.17119v2 Announce Type: replace-cross Abstract: Deep generative models have made rapid progress in image, text, audio, and video generation, and are increasingly being applied to structured

safetyarxiv-cs-ai

How Far Will They Go? Red-Teaming Online Influence with Large Language Models

arXiv:2605.22880v1 Announce Type: cross Abstract: As large language model (LLM)-based agents increasingly participate in online discourse, red-teaming their capacity to support political influence cam

local-aiarxiv-cs-ai

Tutorials

Nonlinear Transformations Against Unlearnable Datasets

arXiv:2406.02883v2 Announce Type: replace Abstract: Automated scraping stands out as a common method for collecting data in deep learning models without the authorization of data owners. Recent studie

tutorialsarxiv-cs-lg

OpenStudio - Hybrid local/cloud (openrouter) AI router

OpenStudio is a hybrid AI router that combines local model inference with cloud-based model access through OpenRouter, a unified API providing access to hundreds of AI models through a single endpoint

local-air-ollama

When Determinants Are Not Enough: Private Rare Switching

arXiv:2605.23131v1 Announce Type: new Abstract: In this note, I would like to share a small research moment where Codex helped me find the right way to adapt rare switching to the private setting. The

Boundary-targeted Membership Inference Attacks on Safety Classifiers

arXiv:2605.22373v1 Announce Type: cross Abstract: Safety classifiers are essential safeguards within generative AI systems, filtering harmful content or identifying at-risk users when interacting with

local-aiarxiv-cs-cl

Tools

FTC to Require Cox Media Group, Two Other Firms to Pay Nearly $1 Million to Settle Charges They Deceived Customers About “Active Listening” AI-Powered Marketing Service

FTC to Require Cox Media Group, Two Other Firms to Pay Nearly $1 Million to Settle Charges They Deceived Customers About “Active Listening” AI-Powered Marketing Service Back in 2024 Cox Media Group we

toolssimon-willison

GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety

arXiv:2605.20203v1 Announce Type: cross Abstract: As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

arXiv:2507.01053v4 Announce Type: replace-cross Abstract: Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective use. The Medical I

Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVs

arXiv:2605.21115v1 Announce Type: cross Abstract: Federated learning (FL) has emerged as a promising paradigm for managing electric vehicle (EV) battery data in intelligent transportation systems (ITS

Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models

arXiv:2605.20591v1 Announce Type: new Abstract: Medical large language models (LLMs), including custom medical GPTs (MedGPTs) and open-source models, are increasingly deployed on web platforms to prov

safetyarxiv-cs-cl

Federated Learning of Nonlinear Temporal Dynamics with Graph Attention-based Cross-Client Interpretability

arXiv:2602.13485v2 Announce Type: replace Abstract: Networks of modern industrial systems are increasingly monitored by distributed sensors, where each system comprises multiple subsystems generating

local-aiarxiv-cs-lg

GraphRAG on Consumer Hardware: Benchmarking Local LLMs for Healthcare EHR Schema Retrieval

model-releasesarxiv-cs-cl

arXiv:2605.20815v1 Announce Type: new Abstract: Graph-based Retrieval Augmented Generation (GraphRAG) extends retrieval-augmented generation to support structured reasoning over complex corpora, but i

Tutorials

Q-Net: Queue Length Estimation via Kalman-based Neural Networks

arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp

tutorialsarxiv-cs-lg

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis

arXiv:2510.06063v2 Announce Type: replace-cross Abstract: Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventio

applicationsarxiv-cs-lg

The top announcements for startups from Google I/O ‘26

model-releasesgoogle-cloud-ai

Many of the world’s fastest-growing AI startups are choosing to build their future — and the world’s — on Google Cloud because of our complete and open AI stack. We embed AI into every layer of our ar

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment

model-releasesarxiv-cs-cl

arXiv:2506.14148v2 Announce Type: replace-cross Abstract: This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair a

FedBiCross: A Bi-Level Optimization Framework to Tackle Non-IID Challenges in Data-Free One-Shot Federated Learning on Medical Data

arXiv:2601.01901v2 Announce Type: replace Abstract: Data-free knowledge distillation-based one-shot federated learning (OSFL) trains a model in a single communication round without sharing raw data, m

Governing Evolving Memory in LLM Agents: Risks, Mechanisms, and the Stability and Safety Governed Memory (SSGM) Framework

arXiv:2603.11768v2 Announce Type: replace Abstract: Long-term memory has emerged as a foundational component of autonomous Large Language Model (LLM) agents, enabling continuous adaptation, lifelong m

safetyarxiv-cs-ai

How Does Overparameterization Affect Machine Unlearning of Deep Neural Networks?

arXiv:2503.08633v2 Announce Type: replace Abstract: Machine unlearning is the task of updating a trained model to forget specific training data without retraining from scratch. In this paper, we inves

I built a local Qwen2.5-VL desktop tool that lets you ask questions about any part of your screen (using Ollama + live overlays)

This project implements a local desktop application using Qwen2.5-VL (a vision-language model) and Ollama that enables users to interactively query visual content on their screen through a live overla

local-air-ollama

On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosis

arXiv:2605.19201v1 Announce Type: cross Abstract: Deep learning models detect pneumonia from chest X-rays with high accuracy, but the performance declines under domain shifts caused by differences in

local-aiarxiv-cs-ai

Optimal Reconstruction from Linear Queries

arXiv:2605.19625v1 Announce Type: new Abstract: We study the problem of reconstructing an unknown point in R^d from approximate linear queries. This setting arises naturally in applications ranging fr

Reducing Diffusion Model Memorization with Higher Order Langevin Dynamics

arXiv:2605.19170v1 Announce Type: cross Abstract: Diffusion/score-based models have emerged as powerful generative models, capable of generating high-quality samples that mimic the training data distr

applicationsarxiv-cs-lg

Smooth Partial Lotteries for Stable Randomized Selection

arXiv:2605.20069v1 Announce Type: new Abstract: Competitive selection processes, from scientific funding to admissions and hiring, use evaluations to score candidates, and eventually choose a subset o

Synthesis and Evaluation of Long-term History-aware Medical Dialogue

arXiv:2605.19766v1 Announce Type: cross Abstract: An effective healthcare agent must be able to recall and reason over a patient's longitudinal medical history. However, the absence of datasets with r

Toward an AI-Powered Computational Testbed for Workforce Policy

arXiv:2605.19064v1 Announce Type: cross Abstract: Workforce transformations are difficult to forecast and costly to mismanage. In particular, the integration of artificial intelligence into knowledge

safetyarxiv-cs-ai

ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models

arXiv:2605.18879v1 Announce Type: cross Abstract: Large language models inevitably retain sensitive information, defined as inputs that may induce harmful generations, due to training on massive web c

A major step forward for sovereign enterprise AI in healthcare and biopharma. Cohere has acquired @reliant_ai 🇨🇦🇩🇪

Cohere has acquired Reliant AI, a Canadian-German company, to advance sovereign enterprise AI capabilities in the healthcare and biopharma sectors. This acquisition enables Cohere to expand its AI inf

applicationscohere--x

AI Agents May Always Fall for Prompt Injections

arXiv:2605.17634v1 Announce Type: cross Abstract: Prompt injection is the most critical vulnerability in deployed AI agents. Despite recent progress, we show that the prevailing defense paradigm (data

safetyarxiv-cs-cl

CATA: Continual Machine Unlearning via Conflict-Averse Task Arithmetic

arXiv:2605.18610v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applic

researcharxiv-cs-ai

Tutorials

CBT-Audio: Evaluating Audio Language Models for Patient-Side Distress Intensity Estimation in CBT Session Recordings

arXiv:2605.17370v1 Announce Type: new Abstract: Cognitive behavioural therapy is widely used to help patients understand and manage psychological distress. It is often delivered through spoken convers

tutorialsarxiv-cs-ai

CheckSupport: A Local LLM-Powered Tool for Automated Manuscript Submission Checklist Selection and Completion

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

local-aiarxiv-cs-ai

EgoInteract: Synthetic Egocentric Videos Generation for Interaction Understanding and Anticipation

arXiv:2605.18214v1 Announce Type: new Abstract: Collecting large-scale egocentric video datasets with dense spatial and temporal annotations is costly, slow, and often constrained by environmental bia

applicationsarxiv-cs-cv

Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications

arXiv:2605.17219v1 Announce Type: cross Abstract: Artificial Intelligence (AI) is widely adopted today for its ability to detect patterns, automate tasks, and reduce time and cost across various appli

researcharxiv-cs-ai

M^2FedAQI: Multimodal Federated Learning for Air Quality Prediction on Heterogeneous Edge Devices

arXiv:2605.16375v1 Announce Type: new Abstract: Accurate air quality prediction is essential for public health, environmental monitoring, and industrial safety. However, most existing approaches rely

Machine Unlearning for Masked Diffusion Language Models

arXiv:2605.18253v1 Announce Type: cross Abstract: Recent masked diffusion language models (MDLMs), such as LLaDA and Dream, have achieved performance comparable to autoregressive large language models

On the Accuracy of Newton Step and Influence Function Data Attributions

arXiv:2512.12572v2 Announce Type: replace Abstract: Data attribution aims to explain model predictions by estimating how they would change if certain training points were removed, and is used in a wid

Agents

One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception

arXiv:2605.17907v1 Announce Type: cross Abstract: By sharing intermediate features, collaborative perception extends each agent's sensing beyond standalone limits, but real-world feature modality hete

agentsarxiv-cs-ai