arXiv preprints from January 1, 2026 through October 1, 2026 — 12:11:10 EST
Polynomial optimization encompasses a broad class of problems in which both the objective function and constraints are polynomial functions of the decision variables. In recent years, a substantial body of research has focused on reformulating polynomial optimization problems (POPs) as conic programs over the cone of completely...
Many agent-based mathematical models of cranial neural crest cell (CNCC) migration impose a binary phenotypic partition of cells into either leaders or followers. In such models, the movement of leader cells at the front of collectives is guided by local chemoattractant gradients, while follower cells behind leaders move according to...
Massive stars are the engines of the Cosmos, shaping their environments and driving galaxy evolution across cosmic time. Yet, this general textbook picture faces many challenges when trying to turn abstract insights into quantitative predictions. Recent discoveries, such the surprisingly high metallicity and early nitrogen enrichment...
Being able to understand the security and privacy (S&P) concerns of IoT users brings benefits to both developers and users. To learn about users' views, we examine Amazon IoT reviews - one of the biggest IoT markets. This work presents a state-of-the-art methodology to identify and categorize reviews in which users express S&P...
We consider the Etingof-Kazhdan quantum vertex algebra $\mathcal{V}^c(R)$ associated with the trigonometric and elliptic $R$-matrix of type $A.$ We establish a connection between (restricted) modules for the $h$-Yangian $\textrm{Y}_h(\mathfrak{gl}_N)$ and the elliptic quantum algebra $\mathcal{A}_{h,p}(\widehat{\mathfrak{gl}}_2)$ of...
Blockchain as a promising technology is gaining its popularity ever since proof-of-work based Bitcoin came to the world. Nevertheless, Bitcoin achieves consensus at an expensive cost of energy. Proof-of-stake is one of the solutions for such a problem. Participants of PoS protocols achieve dynamic-availability in permissionless...
Skeleton-based human action recognition (HAR) has achieved remarkable progress with graph-based architectures. However, most existing methods remain body-centric, focusing on large-scale motions while neglecting subtle hand articulations that are crucial for fine-grained recognition. This work presents a probabilistic dual-stream...
We present a lightweight two-stage framework for joint geometry and color inpainting of damaged 3D objects, motivated by the digital restoration of cultural heritage artifacts. The pipeline separates damage localization from reconstruction. In the first stage, a 2D convolutional network predicts damage masks on RGB slices extracted...
Adversarial attacks pose a significant challenge to the reliable deployment of machine learning models in EdgeAI applications, such as autonomous driving and surveillance, which rely on resource-constrained devices for real-time inference. Among these, patch-based adversarial attacks, where small malicious patches (e.g., stickers) are...
Joint Embedding Predictive Architectures (JEPA) are a novel self supervised training technique that have shown recent promise across domains. We introduce BERT-JEPA (BEPA), a training paradigm that adds a JEPA training objective to BERT-style models, working to combat a collapsed [CLS] embedding space and turning it into a...
The Pulsed Townsend experiment enables the extraction of relevant electron transport properties in different gases such as the electron drift velocity $W$ (or equivalently the mobility $μ$), the longitudinal diffusion coefficient $D_{\mathrm{L}}$, and the effective ionization rate $R_{\mathrm{net}}$ (or equivalently the effective...
Multilingual large language models achieve impressive cross-lingual performance despite largely monolingual pretraining. While bilingual data in pretraining corpora is widely believed to enable these abilities, details of its contributions remain unclear. We investigate this question by pretraining models from scratch under controlled...
Dynamic and stable magnetic textures offer a powerful platform for controlling magnon states in the broader context of spin electronics. In this work, we uncover a novel class of dynamical, crystal-like localization patterns in real space, arising from the hybridization of magnons with topologically non-trivial spin textures that...
Bulk viscosity and thermodynamic variables of a hydrogen-helium cocktail: internal energy, enthalpy, pressure, their derivatives, heat capacities per constant density and pressure are obtained using temperature and density height profiles of the solar atmosphere [Avrett & Loeser, ApJS Vol. 175, 229 (2008)]. The qualitative evaluation...
Construction industries in developing countries face systemic challenges such as chronic project delays, cost overruns, and regulatory inefficiencies. This paper presents a system dynamics (SD) modeling framework for analyzing policy and resource dynamics within the construction sector in Sudan, with broader applicability to Least...
We introduce the first iterative algorithm for constructing a $\varepsilon$-coreset that guarantees deterministic $\ell_p$ subspace embedding for any $p \in [1,\infty)$ and any $\varepsilon > 0$. For a given full rank matrix $\mathbf{X} \in \mathbb{R}^{n \times d}$ where $n \gg d$, $\mathbf{X}' \in \mathbb{R}^{m \times d}$ is an...
As multi-agent AI systems become increasingly autonomous, evidence shows they can develop collusive strategies similar to those long observed in human markets and institutions. While human domains have accumulated centuries of anti-collusion mechanisms, it remains unclear how these can be adapted to AI settings. This paper addresses...
In domestic environments, robots require a comprehensive understanding of their surroundings to interact effectively and intuitively with untrained humans. In this paper, we propose DVEFormer - an efficient RGB-D Transformer-based approach that predicts dense text-aligned visual embeddings (DVE) via knowledge distillation. Instead of...
Temporal asymmetry in the flux variability of active galactic nuclei (AGNs) offers key insights into the physical mechanisms driving AGN variability. In this study, we investigated the variability of the torus by analyzing temporal asymmetry in the mid-infrared (MIR) continuum. We compared ensemble structure functions between the...
As adversaries increasingly weaponize encryption and protocol obfuscation to evade traffic detection, traditional methods are rendered obsolete, necessitating deep learning to unmask sophisticated threats. However, the prohibitive computational costs of existing large models create a critical defense gap, hindering their deployment in...
This paper introduces and investigates degenerate versions of the A-algorithm and B-algorithm by incorporating a parameter lambda into their respective recurrence relations. We derive explicit formulas for the final sequences of these algorithms in terms of the initial sequences and the degenerate Stirling numbers of the second kind....
Melanoma is the most lethal subtype of skin cancer, and early and accurate detection of this disease can greatly improve patients' outcomes. Although machine learning models, especially convolutional neural networks (CNNs), have shown great potential in automating melanoma classification, their diagnostic reliability still suffers due...
Deep Reinforcement Learning based solution for jamming communications using Frequency Hopping Spread Spectrum technology in a 16 channel radio environment is presented. Deep Q Network based transmitter continuously selects the next frequency hopping channel while facing first order reactive jamming, which uses observed transition...
Atmospheric Rivers (ARs) are filamentary moisture pathways responsible for a large fraction of extreme precipitation and often occur as interacting filament bundles within the same synoptic regime. Existing diagnostics typically analyze ARs in isolation, despite the frequent coexistence and interaction of multiple filaments. We...
Resource-constrained Internet of Things (IoT) devices, from medical implants to small drones, must transmit sensitive telemetry under adversarial wireless channels while operating under stringent computing and energy budgets. Authenticated Encryption (AE) is essential to ensure confidentiality, integrity, and authenticity. However,...