arXiv preprints from January 1, 2026 through September 25, 2026 — 06:04:42 EST
AI-generated content has progressed from monolithic models to modular workflows, especially on platforms like ComfyUI, allowing users to customize complex creative pipelines. However, the large number of components in ComfyUI and the difficulty of maintaining long-horizon structural consistency under strict graph constraints...
We consider the oxygen abundance distributions for a sample of massive spiral galaxies from the MaNGA survey in which the radial abundance gradient flattens to a constant value outside of the outer break radius, Rb,outer. The outer break radius can be considered as a dividing radius between the galaxy and the circumgalactic medium...
We address the problem of classifying trajectory data generated by some nonlinear dynamics, where each class corresponds to a distinct dynamical system. We propose Dynafit, a kernel-based method for learning a distance metric between training trajectories and the underlying dynamics. New observations are assigned to the class with the...
Objective: Ultra-wideband radar technology offers a promising solution for unobtrusive and cost-effective in-home sleep monitoring. However, the limited availability of radar sleep data poses challenges in building robust models that generalize across diverse cohorts and environments. This study proposes a novel deep transfer learning...
The bifurcation of generative modeling into autoregressive approaches for discrete data (text) and diffusion approaches for continuous data (images) hinders the development of truly unified multimodal systems. While Masked Language Models (MLMs) offer efficient bidirectional context, they traditionally lack the generative fidelity of...
Prompt quality plays a central role in controlling the behavior, reliability, and reasoning performance of large language models (LLMs), particularly for smaller open-source instruction-tuned models that depend heavily on explicit structure. While recent work has explored automatic prompt optimization using textual gradients and...
Designing mechanical linkages to achieve target end-effector trajectories presents a fundamental challenge due to the intricate coupling between continuous node placements, discrete topological configurations, and nonlinear kinematic constraints. The highly nonlinear motion-to-configuration relationship means small perturbations in...
We show that the derived category of complexes with quasi-coherent cohomology on a regular Noetherian algebraic stack with quasi-finite diagonal is generated by a single perfect complex. In the concentrated case, the category is singly compactly generated. Key ingredients in the proofs include gluing generators along recollement and...
Vision-Language-Action (VLA) models have demonstrated impressive capabilities in generalized robotic control; however, they remain notoriously brittle to linguistic perturbations. We identify a critical ``modality collapse'' phenomenon where strong visual priors overwhelm sparse linguistic signals, causing agents to overfit to...
We propose a new Bayesian framework to infer the neutron star equation of state (EOS) from mass and radius observations and neutron matter theory by defining priors that directly parameterize mass-radius space instead of pressure-energy density space. We use direct and accurate inversion approximations to map mass-radius relations to...
We present an explicit family $\mathcal{B}$ of $920$ subsets of size $6$ of $[60]=\{1,\dots,60\}$ with the property that every $6$-subset $S\subset[60]$ intersects at least one block $B\in\mathcal{B}$ in at least three elements, i.e.\ $|S\cap B|\ge 3$. The construction is purely combinatorial, based on a partition of the ground set...
Symbolic regression aims to find symbolic expressions that describe datasets. Due to its inherent interpretability, symbolic regression (SR) is a powerful paradigm for scientific discovery. Recent advances have expanded SR to describe related phenomena using a single expression with varying sets of parameters, thereby introducing a...
The Colin de Verdière parameter is a number assigned to discrete graphs which equals the maximal multiplicity of the second eigenvalue of a certain family of Laplacian matrices related to the graph. In this paper it is shown that the Colin de Verdière parameter can be obtained in the setting of metric graphs by looking at the maximal...
This work introduces an end-to-end framework for multi-asset option pricing that combines market-consistent risk-neutral density recovery with quantum-accelerated numerical integration. We first calibrate arbitrage-free marginal distributions from European option quotes using the Normal Inverse Gaussian (NIG) model, leveraging its...
The accelerated expansion of the Universe remains one of the central open problems in modern cosmology. While the $Λ$CDM model successfully describes a wide range of observations, the physical nature of dark energy is still unknown, motivating the study of alternative theories of gravity. Among these, $f(R)$ models provide a...
Nonlinear nanophotonic waveguides have opened a route to compact frequency combs for precision metrology, spectroscopy and astronomy, yet broadband comb access to the visible remains challenging on CMOS-compatible platforms. Silicon nitride is widely accessible and low loss into the visible, but most demonstrations rely on telecom...
The magneto-optical properties of a Zn$_{0.99}$Mn$_{0.01}$Se/Be$_{0.93}$Mn$_{0.07} $Te diluted magnetic semiconductor heterostructure with type-II band alignment are investigated at cryogenic temperatures down to 16 mK. The temperature of the Mn spin system, which at the lowest possible laser power reaches 270 mK, is evaluated from...
We present a novel approach to the automatic synthesis of recursive programs from mixed-quantifier first-order logic properties. Our approach uses Skolemization to reduce the mixed-quantifier synthesis problem to a $\forall^*$-synthesis problem, synthesizing witness-generating functions for introduced Skolem symbols alongside the...
Controlling the chirality and yield of carbon nanotubes is essential for their diverse applications from macroscopic composites to nanoelectronics. Floating-catalyst chemical vapor deposition is widely employed as a scalable synthesis route, where catalysts inevitably traverse spatially varying environments. However, prevailing...
As Multimodal Large Language Models (MLLMs) become an indispensable assistant in human life, the unsafe content generated by MLLMs poses a danger to human behavior, perpetually overhanging human society like a sword of Damocles. To investigate and evaluate the safety impact of MLLMs responses on human behavior in daily life, we...
The future 6G networks are expected to utilize large antenna arrays and follow the user-centric architecture, where the user is being served by all base stations. This work evaluates such a system within an advanced system-level simulator, which utilizes an accurate 3D Ray-Tracing radio channel model. Results show that the novel...
Bibliometric analysis is a critical tool for understanding the structure, dynamics, and impact of scientific research. Traditional methods often fall short in capturing the intricate relationships and evolving trends within scientific literature. To address this gap, we present pyBiblioNet, a Python library designed to facilitate...
A $t$-all-symbol PIR code and a $t$-all-symbol batch code of dimension $k$ consist of $n$ servers storing linear combinations of $k$ information symbols with the following recovery property: any symbol stored by a server can be recovered from $t$ pairwise disjoint subsets of servers. In the batch setting, we further require that any...
We study the trade-off between (average) spread and width in tree decompositions, answering several questions from Wood [arXiv:2509.01140]. The spread of a vertex $v$ in a tree decomposition is the number of bags that contain $v$. Wood asked for which $c>0$, there exists $c'$ such that each graph $G$ has a tree decomposition of width...
Two widely used model-free lower bounds on the steady-state entropy production rate of a continuous-time Markov jump process are the thermodynamic uncertainty relation (TUR) bound $σ_\text{TUR}$, derived from the mean and variance of a current, and the waiting-time distribution (WTD) bound $σ_\mathcal{L}$, derived from the...