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The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 116
H-GLow: Accelerating Graph Generation via Hazard-Guided Discrete Flow Matching
Discrete flow matching (DFM) offers a promising approach to graph generation; however, generating high-quality graphs with few steps remains challenging due to the strong dependencies between nodes…Satellite-derived bathymetry of Arabian Gulf ports under leakage-free validation: a multi-site benchmark of empirical, machine-learning and deep-learning models against 285,000 multibeam soundings, with an outlook for UAE waters
Satellite-derived bathymetry (SDB) is often proposed as a low-cost complement to multibeam surveys of ports, but its accuracy is seldom measured on an area the model has never seen.On the Error Analysis of Triangular Transport Maps for Conditional Generation via MMD-based Objectives
Conditional generative models parameterized by triangular transport maps are widely used for conditional sampling, yet theoretical guarantees on the quality of the conditional measures they produce…Geodesic-SVDD Latent Mixup for One-Shot Distributed Tabular Learning
Distributed Learning on structured data is a key and widely adopted approach in privacy-sensitive sectors, ranging from financial fraud prevention to federated healthcare diagnostics.Graph-dependent pooling: adaptive granularity in hierarchical graph neural networks
Graph Neural Networks are widely used to learn structural representations of relational data.RAQ-MLA: Role-Aware Quantization for Multi-Head Latent Attention Caches
Multi-Head Latent Attention (MLA) has been adopted by recent frontier large language models.Beyond Affine Reconstruction: Multi-Resolution Transformer DeepONets for the Radiative Transfer Equation
Radiative heat transfer plays a dominant role in fire simulations, where solving the radiative transfer equation (RTE) is a computational bottleneck.Extraction meets Distillation - cryptanalytic techniques to recover parameters from a Deep Neural Network
We study fully connected neural-network reconstruction by combining cryptanalytic weight-direction extraction with learning from predicted labels.Embedding-Based Educational Taxonomies
Educational taxonomies organize educational content, such as exercise problems, into concepts, which are also called skills or knowledge components.Projection-Based Federated Learning on Compact Submanifolds with Geometry-Independent Differential Privacy
Federated learning trains a shared model across clients without exchanging their data, yet the updates they transmit still leak information about individual records.VulDec: Vulnerability Detection in Binaries via Neural Decompilation
Automated vulnerability detection in binary executables is challenging due to the lack of source code and the limited semantic information available at the assembly level.RoboJev: An Open Vision-Language Judge for Robot Success Detection
Many robot manipulation videos do not indicate whether the task was successfully completed.Latent dynamics for reconstructing fine-scale PDE trajectories from coarse observations
Coarse PDE observations omit spatial detail and intermediate states of evolving fields.Learning Representative Port Subsets for Efficient Fluid Antenna Systems
Fluid antenna systems (FASs) provide many candidate ports, but probing all ports for each channel realization incurs substantial online overhead.How Geometry Shapes Generative Model Evaluation on Riemannian Manifolds
On Riemannian manifolds, generative-model evaluation is geometry-dependent since curvature and dimension jointly determine distances and volume growth.Trust Mechanisms for Offline Generative AI at the Edge: A Connectivity-Regime Framework and an Empirical Study on a Raspberry Pi 5
Generative AI and large language models (LLMs) are moving into the Internet of Things, yet most deployments assume cloud connectivity, and many IoT settings have intermittent, restricted, or no…A SegFormer-based model for spatial Daylight Factor prediction with comprehensive obstruction encoding and regulatory validation
Daylight compliance assessment in residential buildings requires time-consuming raytracing simulations and specialist model preparation, limiting its integration into iterative architectural design.Polynomial Residual Networks are Generically Identifiable
We prove identifiability results for constant-width residual networks with polynomial activations and bias terms.A quantum k-nearest neighbors implementation using magnitude-aware comparisons
Much attention has recently been devoted to the k-nearest neighbors (KNN) algorithm as a case study for quantum computing algorithms.A Distribution-Matching Perspective on LLM Training Algorithms
In this work, we propose a unified framework for training algorithms across different stages of modern large language model development, based on the perspective of distribution matching.