arXiv:2603.16969v1 Announce Type: cross Abstract: This paper presents DeepStage, a deep reinforcement learning (DRL) framework for adaptive, stage-aware defense against Advanced Persistent Threats (APTs). The enterprise environment is modeled as a partially observable Markov decision process (POMDP), where host provenance and network telemetry are fused into unified provenance graphs. Building on our prior work, StageFinder, […]
A Comedy of Estimators: On KL Regularization in RL Training of LLMs
arXiv:2512.21852v3 Announce Type: replace-cross Abstract: The reasoning performance of large language models (LLMs) can be substantially improved by training them with reinforcement learning (RL). The RL objective for LLM training involves a regularization term, which is the reverse Kullback-Leibler (KL) divergence between the trained policy and the reference policy. Since computing the KL divergence exactly […]
Parameterizing Dataset Distillation via Gaussian Splatting
arXiv:2509.26219v3 Announce Type: replace-cross Abstract: Dataset distillation aims to compress training data while preserving training-aware knowledge, alleviating the reliance on large-scale datasets in modern model training. Dataset parameterization provides a more efficient storage structure for dataset distillation, reducing redundancy and accommodating richer information. However, existing methods either rely on complex auxiliary modules or fail to […]
Generative Hints
arXiv:2511.02933v2 Announce Type: replace-cross Abstract: Data augmentation is widely used in vision to introduce variation and mitigate overfitting, by enabling models to learn invariant properties. However, augmentation only indirectly captures these properties and does not explicitly constrain the learned function to satisfy them beyond the empirical training set. We propose generative hints, a training methodology […]
Volumetric Ergodic Control
arXiv:2511.11533v2 Announce Type: replace-cross Abstract: Ergodic control synthesizes optimal coverage behaviors over spatial distributions for nonlinear systems. However, existing formulations model the robot as a non-volumetric point, whereas in practice a robot interacts with the environment through its body and sensors with physical volume. In this work, we introduce a new ergodic control formulation that […]
Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor
arXiv:2603.17759v2 Announce Type: cross Abstract: Dark humor often relies on subtle cultural nuances and implicit cues that require contextual reasoning to interpret, posing safety challenges that current static benchmarks fail to capture. To address this, we introduce a novel multimodal, multilingual benchmark for detecting and understanding harmful and offensive humor. Our manually curated dataset comprises […]
Telehealth Approaches for Pediatric Otitis Media and Clinical Outcomes: Scoping Review
Background: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, which is not always accessible, contributing to delayed care and inappropriate prescribing, especially in underserved settings. Rapid advances in telemedicine and digital tools have accelerated the development of remote approaches for assessing pediatric ear diseases, while diagnostic […]
Randomised study of human machine collaboration for cardiotocography interpretation during labour
npj Digital Medicine, Published online: 19 March 2026; doi:10.1038/s41746-026-02556-y Randomised study of human machine collaboration for cardiotocography interpretation during labour
Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority
npj Digital Medicine, Published online: 19 March 2026; doi:10.1038/s41746-026-02552-2 Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority
Advancing diagnostic equity through artificial intelligence chest radiograph screening for osteoporosis in Asian populations
npj Digital Medicine, Published online: 19 March 2026; doi:10.1038/s41746-026-02484-x Advancing diagnostic equity through artificial intelligence chest radiograph screening for osteoporosis in Asian populations
Real-world unified denoising for multi-organ fast MRI: a large-scale prospective validation
npj Digital Medicine, Published online: 19 March 2026; doi:10.1038/s41746-026-02548-y Real-world unified denoising for multi-organ fast MRI: a large-scale prospective validation
Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis
Background: Artificial intelligence (AI) models have been increasingly explored for predicting treatment response to cognitive behavioral therapy (CBT) in patients with anxiety disorders. Identifying potential responders in advance may help inform treatment planning and support clinical decision-making. Although a growing number of studies have applied AI techniques in this context, reported performance estimates vary across […]