arXiv:2602.15149v1 Announce Type: new Abstract: We introduce SoliDualSPHysics, a novel open-source and GPU-accelerated software that extends DualSPHysics to enable the numerical simulation of hyperelastic, finite-strain plastic, and brittle fracture behavior in deformable solids within a unified smoothed particle hydrodynamics (SPH) formulation. The software implements a total Lagrangian formulation for solid mechanics that allows direct application of external loads and boundary conditions, enabling independent solid mechanics simulations. Brittle fracture is modeled through a phase-field approach coupled with SPH, allowing […]

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arXiv:2603.28788v1 Announce Type: new Abstract: Quorum design over asymmetric topologies conflates two independent concerns: inter-tier obligation (which tiers must participate for cross-tier safety) and intra-tier replication (how each tier survives local failures). Flat quorums treat all nodes as interchangeable; when consensus fails, the structure does not reveal whether a tier was unreachable or a tier lost too many replicas. We show that mapping a crumbling-wall quorum construction to a physically tiered network separates these concerns and makes the […]

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Efficient estimation of high-dimensional matrices-including covariance and precision matrices-is a cornerstone of modern multivariate statistics. Most existing studies have focused primarily on the theoretical properties of the estimators (e.g., consistency and sparsity), while largely overlooking the computational challenges inherent in high-dimensional settings. Motivated by recent advances in learning-based optimization method-which integrate data-driven structures with classical optimization algorithms-we explore high-dimensional matrix estimation assisted by machine learning. Specifically, for the optimization problem of high-dimensional matrix estimation, we first present a […]

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arXiv:2603.22332v1 Announce Type: new Abstract: Data imputation is a cornerstone technique for handling missing values in real-world datasets, which are often plagued by missingness. Despite recent progress, prior studies on Large Language Models-based imputation remain limited by scalability challenges, restricted cross-model comparisons, and evaluations conducted on small or domain-specific datasets. Furthermore, heterogeneous experimental protocols and inconsistent treatment of missingness mechanisms (MCAR, MAR, and MNAR) hinder systematic benchmarking across methods. This work investigates the robustness of Large Language Models […]

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The gap between faster payments and business visibility Cross-border payments have never moved faster. Settlement cycles are shrinking. Messaging standards are richer. Transparency is an explicit policy goal. From the outside, it looks like the problem is being solved. Yet ask a mid‑market exporter a simple question — “What did this FX transaction actually cost us, end to end?” — and the answer is often buried across spreadsheets, bank portals, manual reconciliations, and post‑trade analysis. Infrastructure has improved. […]

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I am a research mathematician that has recently written a (in my opinion) pretty neat paper in theoretical computer science that is probably of more interest to machine learning researchers than to fellow mathematicians. I’m therefore seeking to place it in machine learning venues. It’s rather long (60 pages) and I have no particular desire to engage with conference culture, so therefore I’m thinking a journal rather than a conference. What are the good journals in ML or […]

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arXiv:2602.23543v1 Announce Type: new Abstract: We introduce Synthetic Visual Genome 2 (SVG2), a large-scale panoptic video scene graph dataset. SVG2 contains over 636K videos with 6.6M objects, 52.0M attributes, and 6.7M relations, providing an order-of-magnitude increase in scale and diversity over prior spatio-temporal scene graph datasets. To create SVG2, we design a fully automated pipeline that combines multi-scale panoptic segmentation, online-offline trajectory tracking with automatic new-object discovery, per-trajectory semantic parsing, and GPT-5-based spatio-temporal relation inference. Building on this […]

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