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arXiv preprints from January 1, 2026 through September 22, 2026 — 16:30:55 EST

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Posted in physics.class-ph · 2026-01-13 · Alexandre Yoshitaka Charau, Jérôme Laurent, Tony Valier-Brasier

Adiabatic Lamb modes in 3D tapered waveguides: Cut-off effects and ZGV resonances

This paper aims to enhance our understanding of the physical behavior of adiabatic modes in inhomogeneous elastic plates, particularly their remarkable capacity to adapt to gradual perturbations. The study investigates the propagation characteristics of higher-order adiabatic Lamb modes in waveguides with linearly varying thickness,...

💬 0 commentsarXiv:2601.08337v1PDF
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Posted in cs.CV · 2026-01-13 · Junzhuo Liu, Xuemei Du, Daniel Reisenbuchler, Ye Chen, Markus Eckstein, Christian Matek, Friedrich Feuerhake, Dorit Merhof

Tissue Classification and Whole-Slide Images Analysis via Modeling of the Tumor Microenvironment and Biological Pathways

Automatic integration of whole slide images (WSIs) and gene expression profiles has demonstrated substantial potential in precision clinical diagnosis and cancer progression studies. However, most existing studies focus on individual gene sequences and slide level classification tasks, with limited attention to spatial transcriptomics...

💬 0 commentsarXiv:2601.08336v1PDF
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Posted in eess.SY · 2026-01-13 · Moussa Labbadi, Christophe Roman, Yacine Chitour

On Robust Fixed-Time Stabilization of the Cauchy Problem in Hilbert Spaces

This paper presents finite-time and fixed-time stabilization results for inhomogeneous abstract evolution problems, extending existing theories. We prove well-posedness for strong and weak solutions, and estimate upper bounds for settling times for both homogeneous and inhomogeneous systems. We generalize finite-dimensional results to...

💬 0 commentsarXiv:2601.08335v3PDF
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Posted in cs.LG · 2026-01-13 · Jose Lozano-Montoya, Emilio Soria-Olivas, Almudena Fuster-Matanzo, Angel Alberich-Bayarri, Ana Jimenez-Pastor

Automated Machine Learning in Radiomics: A Comparative Evaluation of Performance, Efficiency and Accessibility

Automated machine learning (AutoML) frameworks can lower technical barriers for predictive and prognostic model development in radiomics by enabling researchers without programming expertise to build models. However, their effectiveness in addressing radiomics-specific challenges remains unclear. This study evaluates the performance,...

💬 0 commentsarXiv:2601.08334v2PDF
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Posted in cs.AI · 2026-01-13 · Oleg Romanchuk, Roman Bondar

Semantic Laundering in AI Agent Architectures: Why Tool Boundaries Do Not Confer Epistemic Warrant

LLM-based agent architectures systematically conflate information transport mechanisms with epistemic justification mechanisms. We formalize this class of architectural failures as semantic laundering: a pattern where propositions with absent or weak warrant are accepted by the system as admissible by crossing architecturally trusted...

💬 0 commentsarXiv:2601.08333v1PDF
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Posted in cs.CV · 2026-01-13 · Ahmed A. Hashim, Ali Al-Shuwaili, Asraa Saeed, Ali Al-Bayaty

IGAN: A New Inception-based Model for Stable and High-Fidelity Image Synthesis Using Generative Adversarial Networks

Generative Adversarial Networks (GANs) face a significant challenge of striking an optimal balance between high-quality image generation and training stability. Recent techniques, such as DCGAN, BigGAN, and StyleGAN, improve visual fidelity; however, such techniques usually struggle with mode collapse and unstable gradients at high...

💬 0 commentsarXiv:2601.08332v1PDF
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Posted in cs.CL · 2026-01-13 · Daniil Gurgurov, Yusser Al Ghussin, Tanja Baeumel, Cheng-Ting Chou, Patrick Schramowski, Marius Mosbach, Josef van Genabith, Simon Ostermann

CLaS-Bench: A Cross-Lingual Alignment and Steering Benchmark

Understanding and controlling the behavior of large language models (LLMs) is an increasingly important topic in multilingual NLP. Beyond prompting or fine-tuning, , i.e.,~manipulating internal representations during inference, has emerged as a more efficient and interpretable technique for adapting models to a target language. Yet,...

💬 0 commentsarXiv:2601.08331v1PDF
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Posted in math.PR · 2026-01-13 · Wenjing Cao, Zhenjie Ren, Xiaolu Tan

Quantitative weak propagation of chaos for McKean--Vlasov branching diffusion processes

We study in this paper the weak propagation of chaos for McKean--Vlasov diffusions with branching, whose induced marginal measures are nonnegative finite measures but not necessary probability measures. The flow of marginal measures satisfies a non-linear Fokker--Planck equation, along which we provide a functional Itô's formula. We...

💬 0 commentsarXiv:2601.08330v1PDF
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Posted in physics.plasm-ph · 2026-01-13 · Mahmoud Saad Afify, Kristopher G. Klein, Mihailo M. Martinović, Maria Elena Innocenti

Velocity-Space Signatures of Energy Transfer for Ion-Acoustic Instabilities

Context. Observations by Parker Solar Probe (PSP) of electrostatic waves suggest that electrostatic instabilities, including the ion-ion-acoustic instability (IIAI) frequently observed in the inner heliosphere, play an important role in plasma heating and particle acceleration. Aims. Our aim is to explore the application of single...

💬 0 commentsarXiv:2601.08329v1PDF
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Posted in cs.CR · 2026-01-13 · Mingqi Lv, Shanshan Zhang, Haiwen Liu, Tieming Chen, Tiantian Zhu

APT-MCL: An Adaptive APT Detection System Based on Multi-View Collaborative Provenance Graph Learning

Advanced persistent threats (APTs) are stealthy and multi-stage, making single-point defenses (e.g., malware- or traffic-based detectors) ill-suited to capture long-range and cross-entity attack semantics. Provenance-graph analysis has become a prominent approach for APT detection. However, its practical deployment is hampered by (i)...

💬 0 commentsarXiv:2601.08328v1PDF
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Posted in cs.RO · 2026-01-13 · Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis, George Nikolakopoulos

Safe Heterogeneous Multi-Agent RL with Communication Regularization for Coordinated Target Acquisition

This paper introduces a decentralized multi-agent reinforcement learning framework enabling structurally heterogeneous teams of agents to jointly discover and acquire randomly located targets in environments characterized by partial observability, communication constraints, and dynamic interactions. Each agent's policy is trained with...

💬 0 commentsarXiv:2601.08327v1PDF
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Posted in cs.IT · 2026-01-13 · Emil Björnson, Amna Irshad, Özlem Tugfe Demir, Giuseppe Thadeu Freitas de Abreu, Alva Kosasih, Vitaly Petrov

From Antenna Abundance to Antenna Intelligence in 6G Gigantic MIMO Systems

Current cellular systems achieve high spectral efficiency through Massive MIMO, which leverages an abundance of antennas to create favorable propagation conditions for multiuser spatial multiplexing. Looking towards future networks, the extrapolation of this paradigm leads to systems with many hundreds of antennas per base station,...

💬 0 commentsarXiv:2601.08326v1PDF
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Posted in cs.RO · 2026-01-13 · Zhenyang Liu, Yongchong Gu, Yikai Wang, Xiangyang Xue, Yanwei Fu

ActiveVLA: Injecting Active Perception into Vision-Language-Action Models for Precise 3D Robotic Manipulation

Recent advances in robot manipulation have leveraged pre-trained vision-language models (VLMs) and explored integrating 3D spatial signals into these models for effective action prediction, giving rise to the promising vision-language-action (VLA) paradigm. However, most existing approaches overlook the importance of active...

💬 0 commentsarXiv:2601.08325v1PDF
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Posted in cond-mat.dis-nn · 2026-01-13 · F. Iwase

Critical quantum states and hierarchical spectral statistics in a Cantor potential

We study the spectral statistics and wave-function properties of a one-dimensional quantum system subject to a Cantor-type fractal potential. By analyzing the nearest-neighbor level spacings, inverse participation ratio (IPR), and the scaling behavior of the integrated density of states (IDS), we demonstrate how the self-similar...

💬 0 commentsarXiv:2601.08324v1PDF
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Posted in cs.AI · 2026-01-13 · Yupeng Huo, Yaxi Lu, Zhong Zhang, Haotian Chen, Yankai Lin

AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operation

Equipping agents with memory is essential for solving real-world long-horizon problems. However, most existing agent memory mechanisms rely on static and hand-crafted workflows. This limits the performance and generalization ability of these memory designs, which highlights the need for a more flexible, learning-based memory...

💬 0 commentsarXiv:2601.08323v3PDF
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Posted in cs.NI · 2026-01-13 · Aymen Hasan Alawadi

Streamlined Pathway (SP) Approach: An Efficient Load Balancer to Enhance Quality of Service

Efficient load-balancing mechanisms are critical for maximizing performance and increasing the quality of service (QoS) of data center networks (DCNs). Obtaining the optimal QoS while minimizing resource consumption remains a significant challenge. This paper proposes the streamlined pathway (SP) model, which is a flow scheduling...

💬 0 commentsarXiv:2601.08887v1PDF
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Posted in cs.CV · 2026-01-13 · Lichen Ma, Xiaolong Fu, Gaojing Zhou, Zipeng Guo, Ting Zhu, Yichun Liu, Yu Shi, Jason Li, Junshi Huang

UM-Text: A Unified Multimodal Model for Image Understanding and Visual Text Editing

With the rapid advancement of image generation, visual text editing using natural language instructions has received increasing attention. The main challenge of this task is to fully understand the instruction and reference image, and thus generate visual text that is style-consistent with the image. Previous methods often involve...

💬 0 commentsarXiv:2601.08321v3PDF
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Posted in cond-mat.soft · 2026-01-13 · Lohitha R. Hegde, Kamendra P. Sharma, Eric Grelet

From Lyotropic to Thermotropic Behavior: Solvent-Free Liquid Crystalline Phases in Polymer-Surfactant-Conjugated Rod-shaped Colloidal Viruses

Filamentous bacteriophages fd are viral particles, highly monodisperse in size, that have been widely used as a model colloidal system for studying the self-assembly of rod-shaped particles as well as a versatile template in nanoscience. In aqueous suspensions, fd viruses exhibit lyotropic behavior, forming liquid crystalline phases...

💬 0 commentsarXiv:2601.08320v1PDF
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Posted in cs.CV · 2026-01-13 · Dapinder Kaur, Neeraj Battish, Arnav Bhavsar, Shashi Poddar

YOLOBirDrone: Dataset for Bird vs Drone Detection and Classification and a YOLO based enhanced learning architecture

The use of aerial drones for commercial and defense applications has benefited in many ways and is therefore utilized in several different application domains. However, they are also increasingly used for targeted attacks, posing a significant safety challenge and necessitating the development of drone detection systems. Vision-based...

💬 0 commentsarXiv:2601.08319v1PDF
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Posted in q-bio.QM · 2026-01-13 · Zhengye Pan, Jianwei Zuo, Jiajia Luo

Disentangling History and Propagation Dependencies in Cross-Subject Knee Contact Stress Prediction Using a Shared MeshGraphNet Backbone

Background:Subject-specific finite element analysis accurately characterizes knee joint mechanics but is computationally expensive. Deep surrogate models provide a rapid alternative, yet their generalization across subjects under limited pose and load inputs remains unclear. It remains unclear whether the dominant source of prediction...

💬 0 commentsarXiv:2601.08318v1PDF
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Posted in cond-mat.mes-hall · 2026-01-13 · Ibuki Terada, Vu Thi Ngoc Huyen, Yuki Yanagi, Michi-To Suzuki

Nodal-line-enhanced quantum geometric effects: anomalous and nonlinear Hall effects in the parity-mixed antiferromagnet NbMnP

The anomalous Hall effect has been understood in terms of the geometric nature of Bloch bands and impurity scattering, and has been observed in a wide variety of magnetic materials such as ferromagnets and antiferromagnets. Recently, a large anomalous Hall effect was reported in the noncollinear antiferromagnetic metal NbMnP whose...

💬 0 commentsarXiv:2601.08317v1PDF
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Posted in cs.LG · 2026-01-13 · Tomoki Kubo, Ryuken Uda, Yusuke Iida

Deep Exploration of Epoch-wise Double Descent in Noisy Data: Signal Separation, Large Activation, and Benign Overfitting

Deep double descent is one of the key phenomena underlying the generalization capability of deep learning models. In this study, epoch-wise double descent, which is delayed generalization following overfitting, was empirically investigated by focusing on the evolution of internal structures. Fully connected neural networks of three...

💬 0 commentsarXiv:2601.08316v1PDF
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Posted in quant-ph · 2026-01-13 · Qi Yao, Jun Zhang, Wenxian Zhang, Chaohong Lee

Extending Qubit Coherence Time via Hybrid Dynamical Decoupling

Dynamical decoupling (DD) and bath engineering are two parallel techniques employed to mitigate qubit decoherence resulting from their unavoidable coupling to the environment. Here, we present a hybrid DD approach that integrates pulsed DD with bath spin polarization to enhance qubit coherence within the central spin model. This...

💬 0 commentsarXiv:2601.08315v1PDF
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Posted in hep-ph · 2026-01-13 · Tian-Liang Feng, Hui-Qiang Shang, Jing Gao, Qin Qin, Fu-Sheng Yu

Study of $CP$ violation in $Λ_b^0/Ξ^-_b\rightarrow Λ(1520)M$ decays with the final-state rescattering mechanism

Recently, the LHCb collaboration reported the first observation of $CP$ violation in baryon decays, with a significance of more than $5σ$. This strongly motivates us to investigate the $CP$ violation in more baryon decay processes. In this work, we employ the final-state rescattering mechanism with introducing two model parameters,...

💬 0 commentsarXiv:2601.08314v1PDF