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Related Articles from SNS
RRISE: Robust Radius Inference via a Surrogate Estimator
Announce Type: new Abstract: Randomized smoothing (RS) uses a smoothed classifier to provide architecture-agnostic certificates of $\ell_2$ classification robustness, but its dependence on per-input Monte Carlo (MC) sampling undermines its use in real-time systems. We argue that this cost is structural rather than fundamental, such that it can be significantly reduced by sharing information across the deployment stream. We introduce RRISE, an RS framework that compresses certification into a...
MC-CPO: Mastery-Conditioned Constrained Policy Optimization for Pedagogically Safe Intelligent Tutoring Systems
arXiv:2604.04251v2 Announce Type: replace Abstract: Intelligent tutoring systems increasingly rely on reinforcement learning to personalise instruction, yet optimising for observable engagement signals can systematically decouple learner activity from genuine knowledge acquisition. Analysing over 21 million student interactions across two deployed platforms, we find engagement events without corresponding mastery gains occur in 26.5% of interactions on Junyi Academy (72,758 students) and...
Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
arXiv:2603.24508v3 Announce Type: replace Abstract: Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple accelerators. In this work, we present a portable, multi-GPU hybrid MPI+OpenMP implementation of BIT1 that enables scalable execution on both Nvidia and AMD accelerators through OpenMP target tasks with...
Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
arXiv:2506.20589v4 Announce Type: replace-cross Abstract: Recent developments in the Internet of Bio-Nano-Things (IoBNT) are laying the foundation for innovative healthcare applications that envision a network of remotely coordinated nanodevices within the human body to monitor and actuate over potential diseases. However, interconnecting such nanodevices requires communication strategies that can cope with molecular communication (MC) channels, whose complex, stochastic, and dynamic...
COF26: A new on-top functional for multiconfiguration pair-density functional theory
arXiv:2605.06215v2 Announce Type: replace-cross Abstract: Multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient and accurate framework for computing electronic energies in strongly correlated molecular systems, with the quality of the on-top functional being a key determinant of its predictive accuracy. Here, we introduce MMCDDB26, a rigorously curated benchmark database comprising 76 datasets and 1,495 reactions.
COF26: A new on-top functional for multiconfiguration pair-density functional theory
arXiv:2605.06215v2 Announce Type: replace Abstract: Multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient and accurate framework for computing electronic energies in strongly correlated molecular systems, with the quality of the on-top functional being a key determinant of its predictive accuracy. Here, we introduce MMCDDB26, a rigorously curated benchmark database comprising 76 datasets and 1,495 reactions. We further propose a constrained,...
Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
arXiv:2603.24508v3 Announce Type: replace-cross Abstract: Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple accelerators. In this work, we present a portable, multi-GPU hybrid MPI+OpenMP implementation of BIT1 that enables scalable execution on both Nvidia and AMD accelerators through OpenMP target tasks...
Show HN: Nucleus – A security-hardened, Nix-native container runtime
Extremely lightweight, security-hardened, declarative container runtime for agents and production services Nucleus is a minimalist container runtime for Linux. It provides isolated execution environments using Linux kernel primitives without the overhead of traditional container runtimes. For production services, it is designed around a fully declarative model: Nix builds the root filesystem, the NixOS module declares the service, and Nucleus mounts a pinned, reproducible closure at runtime.
Multi-Column RBF Neural Network Using Adaptive and Non-Adaptive Particle Swarm Optimization
new Abstract: The radial basis function neural network (RBFN) trained with a gradient descending algorithm provides an effective fully connected structure in both shallow and deep networks. The error correction (ErrCor), a state-of-the-art gradient-based training method, selects optimal hidden units to improve accuracy. Alternatively, as a population-based algorithm, the particle swarm optimization algorithm (PSO) uses the swarm experience to optimize RBFN parameters, offering global search...
Scientists mapped every neural connection in a fruit fly and found a surprise
Scientists mapped every neural connection in a fruit fly and found a surprise Scientists have completed the first full brain-to-body wiring map of a fruit fly, revealing that behavior may be driven more by local neural teamwork than by a central brain command center. - Date: - June 10, 2026 - Source: - Harvard Medical School - Summary: - A groundbreaking new connectome maps every neural connection in an adult fruit fly’s central nervous system, creating an unprecedented view of how the brain...