arXiv:2602.16812v1 Announce Type: new Abstract: Large-scale facilities increasingly face analysis and reporting latency as the limiting step in scientific throughput, particularly for structurally and magnetically complex samples that require iterative reduction, integration, refinement, and validation. To improve time-to-result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source that takes instrument data products through reduction, integration, refinement, and validation to a validated crystal structure and a publication-ready CIF. […]

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Optimal power flow (OPF) is one of the fundamental tasks for power system operations. While machine learning (ML) approaches such as deep neural networks (DNNs) have been widely studied to enhance OPF solution speed and performance, their practical deployment faces two critical scaling questions: What is the minimum training data volume required for reliable results? How should ML models’ complexity balance accuracy with real-time computational limits? Existing studies evaluate discrete scenarios without quantifying these scaling relationships, leading to […]

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Binary droplet collisions are ubiquitous in dense sprays. Traditional deterministic models cannot adequately represent transitional and stochastic behaviors of binary droplet collision. To bridge this gap, we developed a probabilistic model by using a machine learning approach, the Light Gradient-Boosting Machine (LightGBM). The model was trained on a comprehensive dataset of 33,540 experimental cases covering eight collision regimes across broad ranges of Weber number, Ohnesorge number, impact parameter, size ratio, and ambient pressure. The resulting machine learning classifier […]

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Last year was a testament to the fact that macOS malware is now everybody’s problem. We started 2025 watching simple stealers grab passwords and cookies. We ended it tracking multi-stage attack platforms with persistent backdoors, alongside increasingly sophisticated phishing operations. In this new reality, we’d like to help Mac users understand what defenses they have and where they might fall short, so their security decisions in 2026 are guided by informed choices rather than anxiety. For a safer […]

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Why the next 24 months represent not an upgrade cycle, but an architectural transformation in human-AI symbiosis The Fallacy of Linear Extrapolation When analyzing AI trajectory predictions, most analysts fall into the trap of linear extrapolation — projecting current capabilities forward at constant rates. The predictions outlined in the source document, while appearing speculative, actually reveal something more profound: we’re approaching an architectural phase transition in how intelligence itself is deployed in human systems. Let me be explicit about what’s technically […]

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arXiv:2601.08040v1 Announce Type: new Abstract: Scientific image manipulation in biomedical publications poses a growing threat to research integrity and reproducibility. Unlike natural image forensics, biomedical forgery detection is uniquely challenging due to domain-specific artifacts, complex textures, and unstructured figure layouts. We present the first vision-language guided framework for both generating and detecting biomedical image forgeries. By combining diffusion-based synthesis with vision-language prompting, our method enables realistic and semantically controlled manipulations, including duplication, splicing, and region removal, across diverse […]

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arXiv:2603.18938v1 Announce Type: new Abstract: We study contextual bandits with finitely many actions in which the reward of each arm follows a single-index model with an arm-specific index parameter and an unknown nonparametric link function. We consider a regime in which arms correspond to stable decision options and covariates evolve adaptively under the bandit policy. This setting creates significant statistical challenges: the sampling distribution depends on the allocation rule, observations are dependent over time, and inverse-propensity weighting induces […]

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Hi, I need advice for my PhD research area. I am interested in in the field of Deep RL, Meta RL, Neural Architecture Search, Hardware aware NAS, multi agent system. Robotics will be the application field. Need advice for research problem statement from the above mentioned topics. Thank you submitted by /u/Programmer-Bose [link] [comments]

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