Search: “privacy”

Setoka: A Benchmark for Hierarchical User Understanding in Personalized Agents over Heterogeneous Data

model-releasesarxiv-cs-cl

arXiv:2607.27056v1 Announce Type: cross Abstract: Personalized agents are increasingly applied to assist users across a wide range of tasks. Effective personalized assistance requires not only retriev

30 Jul 2026

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What is the fastest local research tool (deep research) ?

DGX agent

I've tried grok and Claude's deep research mode and I was amazed with the speed considering the amount of sources analysed. Is there anything as fast that can run locally? My guess would be that to ru

model-releasesr-localllama

30 Jul 2026

Diff-ID: Identity Consistent Facial Image Generation and Morphing via Diffusion Models

arXiv:2607.25078v1 Announce Type: new Abstract: Generative diffusion models have revolutionized facial image synthesis, yet robust identity preservation in high resolution outputs remains a critical c

I2VShield: An Efficient Proactive Defense Framework against DiT-based Image-to-Video Models

arXiv:2607.25522v1 Announce Type: cross Abstract: The rapid advancement of video generation models has led to the increasing misuse of image-to-video (I2V) models. Although substantial progress has be

local-aiarxiv-cs-ai

On the Use of Synthetic Data for Threshold Calibration in Face Recognition: Performance and Security Implications for Border Control Systems

arXiv:2607.25990v1 Announce Type: new Abstract: The recently deployed Entry/Exit System (EES) introduces large-scale biometric verification into European border control, requiring face recognition sys

safetyarxiv-cs-cv

OPERA: Offline Policy-guided Expert Routing and Adaptation for Universal Biomedical Image Analysis

arXiv:2607.25108v1 Announce Type: cross Abstract: Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, pro

safetyarxiv-cs-ai

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r

safetyarxiv-cs-ai

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data

arXiv:2603.07841v2 Announce Type: replace Abstract: Recent advances in large language models have strengthened Text2SQL systems that translate natural language questions into database queries. A persi

researcharxiv-cs-cl

Breaking the Synthetic-Real Domain Shortcut for Training-Free Generative Replay-based Class Incremental Learning

arXiv:2607.22994v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires models to continuously acquire new knowledge while avoiding catastrophic forgetting. While exemplar replay is

safetyarxiv-cs-cv

Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification

arXiv:2607.24683v1 Announce Type: cross Abstract: Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance. However, real-world scen

applicationsarxiv-cs-ai

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607.22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents aut

Distributed Convolutional Rank Regression over Decentralized Networks

arXiv:2607.23639v1 Announce Type: cross Abstract: This paper studies convolution rank regression (CRR) over decentralized distributed learning networks. We propose a novel decentralized CRR framework,

researcharxiv-cs-lg

False Prophets: On the Security of World Models in Agentic Systems

arXiv:2607.23147v1 Announce Type: cross Abstract: Large language models now power autonomous agents capable of complex, multi-step tasks in different environments. Accurate and reliable execution of t

FedTaste: Topology-Aware Structural Transfer for Multimodal Federated Learning with Missing Modalities

arXiv:2607.23245v1 Announce Type: cross Abstract: Multimodal Federated Learning is often challenged by arbitrary modality missingness and Non-IID data distributions, which lead to severe representatio

GEMCo: A Validated, Ethically Releasable Proxy for Inaccessible Counselling Data

model-releasesarxiv-cs-cl

arXiv:2607.23621v1 Announce Type: new Abstract: This paper presents GEMCo, a releasable, human-written proxy for inaccessible counselling data: 86 complete German e-mail counselling conversations (728

Tutorials

Gradient-Free Continual Learning

arXiv:2504.01219v2 Announce Type: replace Abstract: Neural networks are notorious for forgetting old skills when taught new ones - a problem known as catastrophic forgetting. Standard continual learni

tutorialsarxiv-cs-lg

Not Forgotten: Implementation and Evaluation of a Personalized Episodic Memory for the Humanoid Robot Head Kim

arXiv:2607.24190v1 Announce Type: cross Abstract: Social robots that rely on large language models for conversation are unable to retain information across sessions. This absence of memory violates so

researcharxiv-cs-ai

OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows

arXiv:2510.24411v3 Announce Type: replace Abstract: Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobi

Agents

SCTA: An Agentic Framework for Stable and Interpretable Target Gene Discovery from Single-Cell RNA Sequencing

arXiv:2607.23821v1 Announce Type: new Abstract: Identifying therapeutic target genes from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in translational biology. Unlike b

agentsarxiv-cs-lg

Understanding Machine Unlearning Through the Lens of Mode Connectivity

arXiv:2607.23970v1 Announce Type: cross Abstract: Machine Unlearning aims to remove undesired information from trained models without full retraining from scratch. Despite recent progress, the loss la

Carpe Diem: Critical Learning Period-Aware Contract-Based Incentives for Federated Learning

arXiv:2503.07869v4 Announce Type: replace Abstract: Critical learning periods (CLPs) in federated learning (FL) refer to early stages during which low-quality contributions (e.g., sparse training data

researcharxiv-cs-lg

FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs

arXiv:2607.21624v1 Announce Type: cross Abstract: Transformer-based models have enabled unprecedented capabilities across language, vision, and multimodal tasks. On-device fine-tuning of transformer m

local-aiarxiv-cs-lg

How much usage does Ollama Pro give right now vs direct API?

I'm considering the 20 Pro plan, but the limits seem to change over time and are hard to compare with direct API pricing. For anyone using Pro currently, roughly how much coding agent usage do you get

local-air-ollama

Joint Lossless Compression and Steganography for Medical Images via Large Language Models

arXiv:2508.01782v4 Announce Type: replace-cross Abstract: Recently, large language models (LLMs) have driven promising progress in lossless image compression. However, directly adopting existing parad

A Knowledge-Injection Framework for Zero-Shot Adaptation of LLMs to Delirium Prediction

arXiv:2607.20453v1 Announce Type: cross Abstract: Large language models show promise for clinical prediction, but zero-shot performance on specialized tasks is limited by incomplete domain knowledge,

Backpropagation-Free Test-Time Adaptation for Lightweight EEG-Based Brain-Computer Interfaces

arXiv:2601.07556v2 Announce Type: replace-cross Abstract: Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) face significant deployment challenges due to inter-subject variability, sig

applicationsarxiv-cs-ai

GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes

arXiv:2607.21117v1 Announce Type: cross Abstract: Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, partic

researcharxiv-cs-ai

How Many Bits Can an Adapter Write? Measuring the Capacity and Memorization of Parameter-Efficient Fine-Tuning

arXiv:2607.21351v1 Announce Type: new Abstract: A LoRA adapter is a few megabytes that almost everyone treats as a skill rather than a record of the data behind it. We put that assumption on a scale.

Tutorials

M^3-Gen: Interpretable Multimodal Generation of Gene Expression Profiles Using Clinical and Imaging Data

arXiv:2607.21343v1 Announce Type: cross Abstract: Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive di

tutorialsarxiv-cs-ai

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your p…

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your private data. That's sovereignty. Closed models hand one comp

local-aifireworks-ai--x

OpenAI and Anthropic are now competing to see who can make the scariest AI for marketing purposes. What could possibly go wrong?

Pedro Domingos noted that OpenAI and Anthropic are competing to develop the scariest AI for marketing, raising concerns about the potential misuse of persuasive machine‑learning models. His comment hi

safetygary-marcus--x

Three-Pronged Spectral Control for Federated Parameter Efficient Fine Tuning

arXiv:2607.20914v1 Announce Type: new Abstract: Federated parameter-efficient fine-tuning (PEFT) enables communication-efficient adaptation of large pretrained models on decentralized edge data, but i

Toward Generalizable Cognitive Impairment Detection with Speech-Based Multimodal Large Language Models

arXiv:2607.21496v1 Announce Type: cross Abstract: Cognitive impairment (CI) is a growing public health concern. Early and accurate diagnosis is critical for enabling timely intervention and improving

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models

arXiv:2607.18034v2 Announce Type: replace Abstract: Smart home assistants interpret a wide range of user commands, from explicit device control to underspecified and preference dependent requests. Whi

local-aiarxiv-cs-ai

Announcing OpenWorker! An open-source agent that doesn't just chat with you, but delivers finished work -- like hand you a polished document…

model-releasesandrew-ng--x

Announcing OpenWorker! An open-source agent that doesn't just chat with you, but delivers finished work -- like hand you a polished document, send a slack message, or update a calendar entry. Ask it t

Economic Evaluations of Language Models

arXiv:2607.19375v1 Announce Type: cross Abstract: Language models perform economically valuable work, yet they are not currently assessed for how well they perform every economically valuable task. We

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images

model-releasesarxiv-cs-cv

arXiv:2607.18283v1 Announce Type: cross Abstract: Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnorm

In-Context Learning for Wound Classification with Small Multimodal Language Models

model-releasesarxiv-cs-cv

arXiv:2607.18819v1 Announce Type: new Abstract: Wound image classification is often treated as a task-specific supervised learning problem, requiring substantial amounts of manually labelled data and

TalentCLEF at CLEF2026: Skill and Job Title Intelligence for Human Capital Management

arXiv:2607.20009v1 Announce Type: new Abstract: This paper presents the second edition of the TalentCLEF Challenge, which will run as an evaluation lab as part of CLEF 2026. The aim of TalentCLEF is t

safetyarxiv-cs-cl

Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation

arXiv:2504.03707v2 Announce Type: replace-cross Abstract: Emotion recognition is crucial for advancing mental health, healthcare, and technologies such as brain-computer interfaces. EEG-based models,

applicationsarxiv-cs-lg

Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization

arXiv:2607.13336v1 Announce Type: new Abstract: Recent diffusion-based video generation models have enabled high-quality personalized video customization through both tuning-based pipelines, which fin

16 Jul 2026

Learning Speaker Identity Beyond Language and Modality Constraints: Insights from the POLY-SIM 2026 Challenge

arXiv:2607.13669v1 Announce Type: new Abstract: Multimodal speaker identification systems typically assume the availability of complete and homogeneous audio-visual modalities during both training and

applicationsarxiv-cs-cv

16 Jul 2026

Data-Native AI Agents: Why Agents Must Move to Your Data

Enterprise AI agents lose effectiveness when they must access data outside of protected, governed systems. The article argues that truly reliable agents need to be *data‑native*—run directly inside th

applicationsdatabricks

Generalization and Memorization in Rectified Flow

arXiv:2603.13421v2 Announce Type: replace-cross Abstract: Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-f

Ollama is back in NYC today! It's exciting to see more people and businesses realize the benefits of open models! Ownership. Affordable. Pri…

Ollama announced its return to New York City on July 15 2026, celebrating a growing audience of individuals and businesses that value open AI models. The message highlights key benefits of Ollama’s pl

local-aiollama--x

Open-KNEAD: Knowledge-grounded Nutrition Estimation via Agentic Decomposition

arXiv:2607.12911v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown to

local-aiarxiv-cs-cv

PFAdapter: Hierarchical LoRA Decomposition for Personalized Federated MLLMs

arXiv:2607.12111v1 Announce Type: cross Abstract: Agentic AI systems are reshaping communications and networking by deploying autonomous intelligent agents capable of collaborative learning while main

Tutorials

PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

arXiv:2602.04029v2 Announce Type: replace-cross Abstract: Relational Foundation Models (RFMs) facilitate data-driven decision-making by learning from complex multi-table databases. However, the divers

tutorialsarxiv-cs-ai