Search: “privacy”

Cross-Domain Adversarial Augmentation: Stabilizing GANs for Medical and Handwriting Data Scarcity

arXiv:2605.01815v1 Announce Type: new Abstract: Generative Adversarial Networks (GANs) offer a pragmatic route to mitigate data scarcity in vision tasks. We study generative augmentation across two lo

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DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection

DGX agent

arXiv:2511.13108v3 Announce Type: replace Abstract: The rapid progress of generative models such as GANs and diffusion models has led to the widespread proliferation of AI-generated images, raising co

researcharxiv-cs-cv

5 May 2026

FedPLT: Scalable, Resource-Efficient, and Heterogeneity-Aware Federated Learning via Partial Layer Training

model-releasesarxiv-cs-lg

arXiv:2605.02337v1 Announce Type: cross Abstract: Federated Learning (FL) has gained significant attention in distributed machine learning by enabling collaborative model training across decentralized

Foundation Model Guided Dual-Branch Co-Adaptation for Source-Free EEG Decoding

arXiv:2605.00857v1 Announce Type: cross Abstract: Source-free domain adaptation (SFDA) provides a practical solution to cross-subject EEG decoding by adapting source-pretrained models to unlabeled tar

Knowledge-Based Design Requirements for Generative Social Robots in Higher Education

arXiv:2602.12873v4 Announce Type: replace-cross Abstract: Generative social robots (GSRs) powered by large language models enable adaptive, conversational tutoring but also introduce risks such as mis

LiDAR for Rehabilitation: A Comprehensive Survey of Applications, AI Techniques, and Future Directions

arXiv:2605.00879v1 Announce Type: new Abstract: Rehabilitation aims to help patients with limited mobility regain their physical abilities through targeted movements, exercises, stimulation, and other

researcharxiv-cs-ro

MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio

model-releasesarxiv-cs-cl

arXiv:2605.00969v1 Announce Type: cross Abstract: We present MedMosaic, a medical audio question-answering dataset designed to benchmark language and audio reasoning models under realistic clinical co

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models

arXiv:2605.01185v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) enabled by the training of deep learning (DL)-based image recon. models requires large and diverse raw k-sp

Representation learning from OCT images

arXiv:2605.02589v1 Announce Type: new Abstract: Optical Coherence Tomography (OCT) has become one of the most used imaging modality in ophthalmology. It provides high-resolution, non-invasive visualiz

safetyarxiv-cs-cv

Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning

arXiv:2605.01041v1 Announce Type: cross Abstract: In the envisioned future dense urban airspace, multiple companies will operate heterogeneous fleets of small unmanned aerial systems (sUASs), where ea

safetyarxiv-cs-lg

Standing on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone Detection

model-releasesarxiv-cs-lg

arXiv:2605.02860v1 Announce Type: cross Abstract: Cross-language code clone detection (X-CCD) is challenging because semantically equivalent programs written in different languages often share little

SynPAIN: A Synthetic Dataset of Pain and Non-Pain Facial Expressions

arXiv:2507.19673v3 Announce Type: replace Abstract: Accurate pain assessment in patients with limited ability to communicate, such as older adults with severe dementia, represents a critical healthcar

safetyarxiv-cs-cv

The Compliance Gap: Why AI Systems Promise to Follow Process Instructions but Don't

model-releasesarxiv-cs-cl

arXiv:2605.01771v1 Announce Type: new Abstract: An auditor instructs an AI assistant: 'open each file individually using the Read tool -- no scripts, no agents.' The AI replies 'Yes' -- then issues a

Thermal Imaging for Contactless Cardiorespiratory and Sudomotor Response Monitoring

arXiv:2602.12361v2 Announce Type: replace Abstract: Human-machine interfaces in industrial automation need sensing modules that monitor operator actions and physiological state. This is important in f

safetyarxiv-cs-cv

CollaFuse: Collaborative Diffusion Models

arXiv:2406.14429v3 Announce Type: replace-cross Abstract: In the landscape of generative artificial intelligence, diffusion-based models have emerged as a promising method for generating synthetic ima

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration

arXiv:2605.00578v1 Announce Type: new Abstract: Federated learning (FL) offers a promising framework for collaborative digital pathology by enabling model training across institutions. However, real-w

local-aiarxiv-cs-cv

Federated Weather Modeling on Sensor Data

arXiv:2605.00322v1 Announce Type: new Abstract: Federated weather modeling on sensor data is a distributed system underpinned by federated learning, enabling multiple sensor data sources, including gr

Network Digital Untwinning: Towards Backward Optimization of Digital Twins

arXiv:2605.00169v1 Announce Type: cross Abstract: Network digital twins (NDTs) are transforming network management by offering precise virtual replicas of physical network systems. However, their reli

SynQuE: Estimating Synthetic Dataset Quality Without Annotations

arXiv:2511.03928v5 Announce Type: replace Abstract: We introduce and formalize the Synthetic Dataset Quality Estimation (SynQuE) problem: ranking synthetic datasets by their expected real-world task p

Addressing the Reality Gap: A Three-Tension Framework for Agentic AI Adoption

arXiv:2604.27245v1 Announce Type: cross Abstract: Generative AI has rapidly entered education through free consumer tools, outpacing the ability of schools and universities to respond. Now a new wave

EmDT: Embedding Diffusion Transformer for Tabular Data Generation in Fraud Detection

arXiv:2603.13566v2 Announce Type: replace-cross Abstract: Imbalanced datasets pose a difficulty in fraud detection, as classifiers are often biased toward the majority class and perform poorly on rare

Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents

arXiv:2604.27143v1 Announce Type: cross Abstract: Recent research has demonstrated the potential of Large Language Models (LLMs) for autonomous penetration testing, particularly when using cloud-based

local-aiarxiv-cs-ai

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning

arXiv:2604.28024v1 Announce Type: new Abstract: Federated Multi-Label Learning is a distributed paradigm where multiple clients possess heterogeneous multi-label data and perform collaborative learnin

OR-VSKC: Resolving Visual-Semantic Knowledge Conflicts in Operating Rooms with Synthetic Data-Guided Alignment

model-releasesarxiv-cs-ai

arXiv:2506.22500v2 Announce Type: replace-cross Abstract: Automated identification of surgical safety risks is critical for improving patient outcomes; however, Multimodal Large Language Models (MLLMs

Policy-Grounded Safety Evaluation of 20 Large Language Models

arXiv:2507.14719v2 Announce Type: replace Abstract: As large language models (LLMs) become increasingly integrated into real-world applications, scalable and rigorous safety evaluation is essential. T

Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors

arXiv:2604.27426v1 Announce Type: cross Abstract: Local fine-tuning datasets routinely contain sensitive secrets such as API keys, personal identifiers, and financial records. Although ''local offline

local-aiarxiv-cs-ai

Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework

arXiv:2604.27574v1 Announce Type: cross Abstract: Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input mul

researcharxiv-cs-ai

WaferSAGE: Large Language Model-Powered Wafer Defect Analysis via Synthetic Data Generation and Rubric-Guided Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2604.27629v1 Announce Type: new Abstract: We present WaferSAGE, a framework for wafer defect visual question answering using small vision-language models. To address data scarcity in semiconduct

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection

arXiv:2509.11058v2 Announce Type: replace Abstract: Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due

local-aiarxiv-cs-cv

Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats

arXiv:2604.25920v1 Announce Type: cross Abstract: Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tu

applicationsarxiv-cs-ai

Tutorials

CO-EVO: Co-evolving Semantic Anchoring and Style Diversification for Federated DG-ReID

arXiv:2604.26363v1 Announce Type: new Abstract: Federated domain generalization for person re-identification (FedDG-ReID) aims to collaboratively train a pedestrian retrieval model across multiple dec

tutorialsarxiv-cs-cv

Data-Centric Foundation Models in Computational Healthcare: A Survey

arXiv:2401.02458v3 Announce Type: replace-cross Abstract: The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. Th

Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents

arXiv:2505.02077v2 Announce Type: replace-cross Abstract: AI agents are beginning to interact with each other directly and across internet platforms and physical environments, creating security challe

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

Sample Selection Using Multi-Task Autoencoders in Federated Learning with Non-IID Data

arXiv:2604.26116v1 Announce Type: new Abstract: Federated learning is a machine learning paradigm in which multiple devices collaboratively train a model under the supervision of a central server whil

SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning

arXiv:2604.26388v1 Announce Type: cross Abstract: Federated Split Learning has been identified as an efficient approach to address the computational resource constraints of clients in classical federa

Tatemae: Detecting Alignment Faking via Tool Selection in LLMs

arXiv:2604.26511v1 Announce Type: cross Abstract: Alignment faking (AF) occurs when an LLM strategically complies with training objectives to avoid value modification, reverting to prior preferences o

CoRE: Concept-Reasoning Expansion for Continual Brain Lesion Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.25376v1 Announce Type: new Abstract: Accurate brain lesion segmentation in MRI is vital for effective clinical diagnosis and treatment planning. Due to high annotation costs and strict data

Diverse Image Priors for Black-box Data-free Knowledge Distillation

arXiv:2604.25794v1 Announce Type: cross Abstract: Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in

FCMBench-Video: Benchmarking Document Video Intelligence

model-releasesarxiv-cs-cv

arXiv:2604.25186v1 Announce Type: new Abstract: Document understanding is a critical capability in financial credit review, onboarding, and remote verification, where both decision accuracy and eviden

Intrinsic Mutual Information as a Modulator for Preference Optimization

arXiv:2604.24804v1 Announce Type: cross Abstract: Offline preference optimization methods, such as Direct Preference Optimization (DPO), offer significant advantages in aligning Large Language Models

researcharxiv-cs-cl

Knowledge Distillation Must Account for What It Loses

arXiv:2604.25110v1 Announce Type: new Abstract: This position paper argues that knowledge distillation must account for what it loses: student models should be judged not only by retained task scores,

safetyarxiv-cs-lg

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data

arXiv:2604.25467v1 Announce Type: new Abstract: Federated learning increasingly operates in a large-model regime where communication, memory, and computation are all scarce. Typically, non-IID client

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health

arXiv:2410.09635v2 Announce Type: replace Abstract: Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, acc

What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective

arXiv:2604.25132v1 Announce Type: new Abstract: Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an

researcharxiv-cs-cl

A Large-Scale, Cross-Disciplinary Corpus of Systematic Reviews

arXiv:2604.22864v1 Announce Type: cross Abstract: Existing benchmarks for systematic reviewing remain limited either in scale or in disciplinary coverage, with some collections comprising only a modes

researcharxiv-cs-cl

28 Apr 2026

An Empirical Evaluation of Locally Deployed LLMs for Bug Detection in Python Code

model-releasesarxiv-cs-ai

arXiv:2604.23361v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on a wide range of software engineering tasks, including code generation and analysi

28 Apr 2026

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment