March 2026

Reconfigurable Intelligent Surfaces promise to transform wireless environments, yet practical deployment is hindered by the prohibitive overhead of Channel State Information (CSI) estimation and the dimensionality explosion inherent in centralized optimization. This paper proposes a Hierarchical Multi-Agent Reinforcement Learning (HMARL) framework for the control of mechanically reconfigurable reflective surfaces in millimeter-wave (mmWave) systems. We introduce a "CSI-free" paradigm that substitutes pilot-based channel estimation with readily available user localization data. To manage the massive combinatorial action space, the proposed […]

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Clinical machine learning models are increasingly trained using large scale, multimodal foundation paradigms, yet deployment environments often differ systematically from the data generating settings used during training. Such shifts arise from heterogeneous measurement policies, documentation practices, and institutional workflows, leading to representation entanglement between physiologic signal and practice specific artifacts. In this work, we propose a practice invariant representation learning framework for multimodal clinical prediction. We model clinical observations as arising from latent physiologic factors and environment dependent […]

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Six years ago, as covid-19 was rapidly spreading through the US, my sister was working as a medical resident. One day she was handed an N95 and told to “guard it with her life”, because there weren’t any more coming. N95s are made from meltblown polypropylene, produced from plastic pellets manufactured in a small number of chemical plants. Two of these plants were operated by Braskem America in Marcus Hook PA and Neal WV. If there were infections […]

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Concept Bottleneck Models (CBMs) aim for ante-hoc interpretability by learning a bottleneck layer that predicts interpretable concepts before the decision. State-of-the-art approaches typically select which concepts to learn via human specification, open knowledge graphs, prompting an LLM, or using general CLIP concepts. However, concepts defined a-priori may not have sufficient predictive power for the task or even be learnable from the available data. As a result, these CBMs often significantly trail their black-box counterpart when controlling for information […]

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All applications in fifth-generation (5G) networks rely on stable radio-frequency (RF) environments to support mission-critical services in mobility, automation, and connected intelligence. Their exposure to intentional interference or low-power jamming threatens availability and reliability, especially when such attacks remain below link-layer observability. This paper investigates lightweight, explainable, and hardware-efficient jamming detection using the Convolutional Tsetlin Machine (CTM) operating directly on 5G Synchronization Signal Block (SSB) features. CTM formulates Boolean logic clauses over quantized inputs, enabling bit-level inference and […]

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Neural networks often rely on spurious shortcuts for many epochs before discovering structured representations. However, the mechanism governing when this transition occurs and whether its timing can be predicted remains unclear. Prior work shows that gradient descent converges to low norm solutions and that neural networks exhibit simplicity bias, but neither explains the timescale of the transition from shortcut features to structured representations. We introduce the Norm-Hierarchy Transition (NHT) framework, which explains delayed representation learning as the slow […]

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Like the rest of the Rust community, crates.io has been growing rapidly, with download and package counts increasing 2-3x year-on-year. This growth doesn’t come without problems, and we have made some changes to download handling on crates.io to ensure we can keep providing crates for a long time to come. The Problem This growth has brought with it some challenges. The most significant of these is that all download requests currently go through the crates.io API, occasionally causing […]

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There’s a question you’ve asked yourself a thousand times. Why is it that you know exactly what you should be doing… and you still don’t do it? You think it’s procrastination. n Or discipline. n Or laziness. The classic explanations we reach for when nothing else makes sense. Here’s the deal, my friend. You don’t have a thinking problem. You have a nervous system problem. Your mind decides what it wants. n Your body decides what you’re allowed to […]

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