arXiv:2603.28804v1 Announce Type: cross
Abstract: Modern particle physics experiments face an increasing demand for high-fidelity detector simulation as luminosities rise and computational requirements approach the limits of available resources. Deep …
arXiv:2509.16139v4 Announce Type: replace
Abstract: Predicting the extreme hydrodynamic response of porous and architected lattice materials is a fundamental challenge in high energy density physics, where shock-induced pore collapse, baroclinic vorti…
arXiv:2603.29261v1 Announce Type: new
Abstract: Item Price Elasticity is used to quantify the responsiveness of consumer demand to changes in item prices, enabling businesses to create pricing strategies and optimize revenue management. Sectors such a…
arXiv:2508.02473v2 Announce Type: replace-cross
Abstract: Code editing is a frequent yet cognitively demanding task in software development. Existing AI-powered tools often disrupt developer flow by requiring explicit natural language instructions and…
arXiv:2511.03849v4 Announce Type: replace-cross
Abstract: Shannon entropy is not the only entropy that is relevant to machine-learning datasets, nor possibly even the most important one. Traditional entropies such as Shannon entropy capture informatio…
arXiv:2603.29384v1 Announce Type: new
Abstract: Federated Graph Learning (FGL) has emerged as a powerful paradigm for decentralized training of graph neural networks while preserving data privacy. However, existing FGL methods are predominantly design…
arXiv:2603.29432v1 Announce Type: new
Abstract: Medical time-series data captures the dynamic progression of patient conditions, playing a vital role in modern clinical decision support systems. However, real-world clinical data is highly heterogeneou…
arXiv:2603.29654v1 Announce Type: new
Abstract: Aligning human-interpretable concepts with the internal representations learned by modern machine learning systems remains a central challenge for interpretable AI. We introduce a geometric framework for…
arXiv:2603.22455v3 Announce Type: replace
Abstract: Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks. As skill ecosystems grow to tens of thousands of entries, expos…
arXiv:2602.14975v2 Announce Type: replace-cross
Abstract: Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS) strategy using non-conservative (NC) forces to fu…