December 2025 arXiv papers — page 11

R. Kh. Zhukavin, V. D. Kukotenko, P. A. Bushuykin, Yu. Yu. Choporova

Photon echo is observed in n-type Ge uniaxially stressed along the [111] crystallographic direction, with a coherence relaxation time of 300 ps. The nonlinear polarization responsible for the effect originates from antimony donors. Uniaxial stress induces valley splitting of the donor states, substantially enhancing the coherence time and enabling the observ

Prantik Nandi, Narendranath Layek, Sandip K Chakrabarti, Sachindra Naik

We present a comprehensive long-term, multi-epoch spectral and timing study of the Seyfert 1 Active Galactic Nucleus (AGN) Mrk~1040, utilizing X-ray observations spanning from 2009 to 2024 ($\sim$15 years). The source exhibits pronounced spectral and temporal variability, indicative of transitions between different accretion regimes in the vicinity of the ce

Han Yin, Yang Xiao, Rohan Kumar Das, Jisheng Bai

Recent progress in audio generation models has made it possible to create highly realistic and immersive soundscapes, which are now widely used in film and virtual-reality-related applications. However, these audio generators also raise concerns about potential misuse, such as producing deceptive audio for fabricated videos or spreading misleading informatio

Haoran He, Yuxiao Ye, Jie Liu, Jiajun Liang

Fine-tuning diffusion models via online reinforcement learning (RL) has shown great potential for enhancing text-to-image alignment. However, since precisely specifying a ground-truth objective for visual tasks remains challenging, the models are often optimized using a proxy reward that only partially captures the true goal. This mismatch often leads to rew

Nadia Creignou, Timo Camillo Merkl, Reinhard Pichler, Daniel Unterberger

Fixed-parameter tractable (FPT) algorithms have been successfully applied to many intractable problems -- with a focus on decision and optimization problems. Their aim is to confine the exponential explosion to some parameter, while the time complexity only depends polynomially on the instance size. In contrast, intractable enumeration problems have received

Matthew Gentry Durham

In this mostly expository article, we provide a new account of our proof with Minsky and Sisto that mapping class groups and Teichm\"uller spaces admit bicombings. More generally, we explain how the hierarchical hull of a pair of points in any colorable hierarchically hyperbolic space is quasi-isometric to a finite CAT(0) cube complex of bounded dimension, w

Dario Fasone, Shreyasi Mukherjee, Mauro Paternostro, Elisabetta Paladino

We introduce and validate a machine learning-assisted protocol to classify time and space correlations of classical noise acting on a quantum system, using two interacting qubits as probe. We consider different classes of noise, according to their Markovianity and spatial correlations. Leveraging the sensitivity of a coherent population transfer protocol und

Victor Berezin, Inna Ivanova, Anastasia Kuprina

We propose conformal invariance as a fundamental symmetry governing cosmological particle creation from vacuum fluctuations, employing a phenomenological approach with an ideal fluid action to address the long-standing back-reaction problem. We demonstrate that particle production cannot emerge from classical vacua but must originate from a quantum vacuum at

Yifei Zhu, Jiahui Zhang, Binni Huang, Zhenggang Lan

Analyzing nonadiabatic molecular dynamics trajectories traditionally heavily relies on expert intuition and visual pattern recognition, a process that is difficult to formalize. We present VisU, a vision-driven framework that leverages the complementary strengths of two state-of-the-art large language models to establish a "virtual research collective." This

Swaraj Kumar Nanda, Maibam Ricky Devi, Chandini Dash, R. N. Panda

We discuss a double seesaw mechanism for generating light neutrino masses within the Standard Model extensions that include both right-handed neutrinos and extra gauge-singlet sterile fermions. The flavour structure of the double seesaw framework is invoked by an $A_4$ discrete symmetry which yields predictive textures for the Dirac neutrino mass matrix $M_D

Francesca Larosa, Daniel Depellegrin, Andrea Conte, Marco Molinari

The proliferation of machine learning and artificial intelligence redefines the interaction between the anthropogenic and natural elements of our habitat.The use of monitoring tools, processing facilities and the internet of things supports the assessment of planetary health at any given time through automation. However, these data, natural resources and inf

Xinfu Zheng, Chen Peng, Duanfu Chen, Tinggui Zhang

The novel and ingenious scheme we propose for achieving unidirectional reflection lasing (URL) involves integrating a one-dimensional (1D) defective atomic lattice with a coherent gain atomic system. Its physical essence lies in the fact that the right-side reflectivity is drastically reduced due to the destructive interference between primary and secondary

John Pravin Arockiasamy, Andy Comeca, Victoria Yang, Manuel Bied

On the way toward full autonomy, sharing roads between automated and autonomous vehicles in so-called mixed traffic is unavoidable. Moreover, even if all vehicles on the road were autonomous, pedestrians would still cross streets. We propose social robots as moderators between autonomous vehicles and vulnerable road users. This paper presents a first proof-o

Gökçe Çakmak, Ali Deniz, Şahin Koçak, Murat Limoncu

In this note, using some regular triangular tilings of the sphere, the Euclidean plane and the hyperbolic plane, we examine the potential relationship between their discrete Bakry - Emery curvatures and the smooth curvatures of their ambient space forms.

Bruno Ebner, Daniel Hlubinka

We introduce a new goodness-of-fit test for count data on $\mathbb{N}$ for the Zeta distribution with unknown parameter. The test is built on a Stein-type characterization that uses, as Stein operator, the infinitesimal generator of a birth-death process whose stationary distribution is Zeta. The resulting $L^2$-type statistic is shown to be omnibus consiste

Alessia Lucca, Michael Dumbser

This paper aims at developing exactly energy-conservative and structure-preserving finite volume schemes for the discretisation of first-order symmetric-hyperbolic and thermodynamically compatible (SHTC) systems of partial differential equations in continuum physics. Due to their thermodynamic compatibility the class of SHTC systems satisfies an additional c

Kirill Kobialko, Dmitri Gal'tsov

We present a fully analytical method for calculating the key parameters of a Kerr-like gravitational shadow, including its horizontal and vertical diameters, $D_X$ and $D_Y$, the coordinates of its center $X_{C}$, the average radius $\bar{R}$, the deviation from sphericity $\delta C$, and the mean deviation from the Kerr shadow $\delta K$. Developed within t

Joey Chan, Huan Wang, Haoyu Pan, Wei Wu

Accurate forecasting of battery capacity fade is essential for the safety, reliability, and long-term efficiency of energy storage systems. However, the strong heterogeneity across cell chemistries, form factors, and operating conditions makes it difficult to build a single model that generalizes beyond its training domain. This work proposes a unified capac

Advait Gadhikar, Riccardo Grazzi, James Hensman

The presence of outliers in Large Language Models (LLMs) weights and activations makes them difficult to quantize. Recent work has leveraged rotations to mitigate these outliers. In this work, we propose methods that learn fusible rotations by minimizing principled and cheap proxy objectives to the weight quantization error. We primarily focus on GPTQ as the

Stefano Muzzolon, Michael Dumbser, Olindo Zanotti, Elena Gaburro

We propose two new alternative numerical schemes to solve the coupled Einstein-Euler equations in the Generalized Harmonic formulation. The first one is a finite difference (FD) Central Weighted Essentially Non-Oscillatory (CWENO) scheme on a traditional Cartesian mesh, while the second one is an ADER (Arbitrary high order Derivatives) discontinuous Galerkin

Yuan Feng, Yue Yang, Xiaohan He, Jiatong Zhao

Geometric problem solving constitutes a critical branch of mathematical reasoning, requiring precise analysis of shapes and spatial relationships. Current evaluations of geometric reasoning in vision-language models (VLMs) face limitations, including the risk of test data contamination from textbook-based benchmarks, overemphasis on final answers over reason

Gorachand Chakraborty, Subhasis Ghora, Tarakanta Nayak

The existence of the Herman ring of a function adds interest and complexity to the dynamics of the function. We present a detailed and understandable summary of the core discoveries and recent developments on the Herman ring of rational and transcendental meromorphic functions. It is demonstrated that the Herman ring is intriguing on its own and valuable in

Pawan Adhikari, Satish Raj Regmi, Hari Ram Shrestha

Glacial Lake Outburst Floods (GLOFs) are one of the most devastating climate change induced hazards. Existing remote monitoring approaches often prioritise maximising spatial coverage to train generalistic models or rely on optical imagery hampered by persistent cloud coverage. This paper presents an end-to-end, automated deep learning pipeline for the targe

Julian Allagan, Benkam Bobga

Given a graph G equals (V,E), a subset S subset of V is a dominating set if every vertex in V minus S is adjacent to some vertex in S. The dominating set with the least cardinality, gamma, is called a gamma-set which is commonly known as a minimum dominating set. The dominion of a graph G, denoted by zeta(G), is the number of its gamma-sets. Some relations b

Daran Fu, Liu Yang, Yi Shen, Kebin Xiao

Altermagnetism is a newly identified magnetic phase, distinct from conventional ferromagnetism and antiferromagnetism. It exhibits no net magnetization while breaking time-reversal symmetry. Although its momentum-space signatures are established, direct real-space visualization of its defining rotational-symmetry breaking remains missing. Here, using scannin

Jiaxin Hu, Tao Wang, Bingsan Yang, Hongrun Wang

Large Language Models (LLMs) have demonstrated a remarkable capacity in understanding user preferences for recommendation systems. However, they are constrained by several critical challenges, including their inherent "Black-Box" characteristics, susceptibility to knowledge hallucination, and limited online learning capacity. These factors compromise their t

Zonghan Li, Tianwen Tao, Rao Fu, Liang Wang

Significant challenges are posed by simulation and testing in the field of low-altitude unmanned aerial vehicle (UAV) traffic due to the high costs associated with large-scale UAV testing and the complexity of establishing low-altitude traffic test scenarios. Stringent safety requirements make high fidelity one of the key metrics for simulation platforms. De

Yongtao Chen, Yanbo Wang, Wentao Zhao, Guole Shen

Monocular Depth Estimation (MDE) serves as a core perception module in autonomous driving systems, but it remains highly susceptible to adversarial attacks. Errors in depth estimation may propagate through downstream decision making and influence overall traffic safety. Existing physical attacks primarily rely on texture-based patches, which impose strict pl

Chong Han, Mingjie Zhu, Wenqi Zhao, Ziming Yu

The explosive growth of artificial intelligence (AI) workloads in modern data centers demands a radical transformation of interconnect architectures. Traditional copper and optical wiring face fundamental challenges in latency, power consumption, and rigidity, constraining the scalability of distributed AI clusters. This article introduces a vision for Terah

L. Palaversa, E. Donev, Ž. Ivezić, K. Mrakovčić

Aims: We investigate the utility of Rubin's Data Preview 1 for estimating stellar number density profile in the Milky Way halo. Methods: Stellar broad-band near-UV to near-IR $ugrizy$ photometry released in Rubin's Data Preview 1 is used to estimate distance and metallicity for blue main sequence stars brighter than $r=24$ in three $\sim$1.1. sq.~deg. fields

Li-Wei Wang, Bolun Hu, Haixiao Zhang, Kefan Sun

The interplay between topology and non-Hermiticity gives rise to exotic dynamic phenomena that challenge conventional wave-packet propagation and entanglement dynamics. While recent studies have established the non-Hermitian skin effect (NHSE) as a key mechanism for anomalous wave dynamics, a unified framework for characterizing and controlling entanglement

Sachin Saini, Uaday Singh

In this paper, we construct a class of stochastic interpolation neural network operators (SINNOs) with random coefficients activated by sigmoidal functions. We establish their boundedness, interpolation accuracy, and approximation capabilities in the mean square sense, in probability, as well as path-wise within the space of second-order stochastic (random)

Maxime Lucet, Nawal Benabbou, Aurélie Beynier, Nicolas Maudet

We introduce the concept of multilevel fair allocation of resources with tree-structured hierarchical relations among agents. While at each level it is possible to consider the problem locally as an allocation of an agent to its children, the multilevel allocation can be seen as a trace capturing the fact that the process is iterated until the leaves of the

Bernd Bohnet, Pierre-Alexandre Kamienny, Hanie Sedghi, Dilan Gorur

We demonstrate an approach for LLMs to critique their \emph{own} answers with the goal of enhancing their performance that leads to significant improvements over established planning benchmarks. Despite the findings of earlier research that has cast doubt on the effectiveness of LLMs leveraging self critique methods, we show significant performance gains on

Yves Ruffenach

This paper provides an ablation-based analysis of latent autoregression in GP-VAE models, building upon our previous work introducing the architecture. Language models typically rely on an autoregressive factorization over tokens. In contrast, our prior work proposed shifting sequential structure to the latent space through a causal Gaussian process, while u

Anh Ngoc Pham

Viewing Leavitt path algebras of finite digraphs as rings of quotients defined by the ideal topology of the ideal generated by all arrows and sinks allows us to induce their representations from those of the quiver algebras and therefore provides a way to construct representations of Leavitt path algebras of not necessarily finite digraphs together with a co

Yijie Qian, Juncheng Wang, Yuxiang Feng, Chao Xu

Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language directly to continuous poses. While effective for simple actions, this System 1 approach faces a fundamental theoretical bottleneck we identify as the Semantic-Kinematic Impedance Mismatch: the inherent difficulty

Gengchen Meng Qi Sun, Zhicheng Xie, Yumin Yang, Yu Zhang

Conventional spintronic mechanisms, such as spin-transfer and spin-orbit torques based on the spin current, rely on breaking time-reversal symmetry to manipulate magnetic moments. In contrast, for spatially separated dual spin currents, the time-reversal-invariant vector chirality emerges as a critical factor governing magnetization dynamics. Here, we invest

Liling Tan

The development of Large Language Models (LLMs) has primarily been driven by resource-rich research groups and industry partners. Due to the lack of on-premise computing resources required for increasingly complex models, many researchers are turning to cloud services like AWS SageMaker to train Hugging Face models. However, the steep learning curve of cloud

Wenzheng Zeng, Difei Gao, Mike Zheng Shou, Hwee Tou Ng

Recent video-language models have shown great potential for video understanding, but still struggle with accurate temporal grounding for event-level perception. We observe that two main factors in video understanding (i.e., temporal grounding and textual response) form a logical hierarchy: accurate temporal evidence grounding lays the foundation for reliable

Michal Kolesár, José Luis Montiel Olea, Jonathan Roth

We study settings in which a researcher has an instrumental variable (IV) and seeks to evaluate the effects of a counterfactual policy that alters treatment assignment, such as a directive encouraging randomly assigned judges to release more defendants. We develop a general and computationally tractable framework for computing sharp bounds on the effects of

Xidi Wang

Can purely mechanical systems generate intelligent language? We prove that dissipative quantum dynamics with analytically tractable non-local context aggregation produce coherent text generation, while conservation laws cause fundamental failure. Employing Koopman operators with closed-form path integral propagators, we show irreversible computation fundamen

Steen Rasmussen, Thomas Frederiksen, Masayuki Imai, Sheref S. Mansy

As minimal cells or protocells are dramatically simpler than modern unicells it is possible to quantitatively estimate free energy changes for every process in the lifecycle of a protocell and compare these with estimates of the free energy changes for lifecycles in modern unicells. We present quantitative estimates of all metabolic changes in part by new de

Cédric Bonnafé

Miyaoka proved that a smooth surface of degree $d$ in ${\mathbf{P}}^3({\mathbb{C}})$ contains at most $2d(d-2)$ pairwise disjoint lines. In this note, we verify that the Maschke octic contains $96$ pairwise disjoint lines, thereby proving that Miyaoka's bound is optimal for $d=8$.

Guo-Wei Zhang, Sheng-Teng Zheng, You Xiao, Fang-Xiang Wang

Quantum key distribution (QKD) enables secure communication by harnessing the fundamental principles of quantum physics, which inherently guarantee information-theoretic security and intrinsic resistance to quantum computing attacks. However, the secure key rate of QKD typically decreases exponentially with increasing channel distance. In this work, by devel

Sanchi Monga, Saswata Bhattacharya

We present a comprehensive first-principles investigation of the electronic structure and excited-state carrier dynamics in the carbide antiperovskites Ca$_6$CSe$_4$ and Sr$_6$CSe$_4$. Using many-body perturbation theory ($G_0W_0$/BSE), we show that both materials are direct band gap semiconductors with quasiparticle gaps of 1.66 eV (Ca) and 1.22 eV (Sr), ly

Mao Zheng, Zheng Li, Tao Chen, Mingyang Song

In this report, we introduce our latest translation models, HY-MT1.5-1.8B and HY-MT1.5-7B, a new family of machine translation models developed through a holistic training framework tailored for high-performance translation. Our methodology orchestrates a multi-stage pipeline that integrates general and MT-oriented pre-training, supervised fine-tuning, on-po

Bhuvneshwari Sharma, Soumyaranjan Dash, Shaktiranjan Mohanty, Brindaban Ojha

Synthetic ferrimagnetic (SFiM) multilayers offer a versatile platform for hosting skyrmions with tunable magnetic properties, combining the advantages of ferromagnets and antiferromagnets. Unlike synthetic antiferromagnets, SFiMs retain a finite magnetization that allows direct observation of magnetic textures while still benefiting from reduced dipolar fiel

Dong Wang, Weidong Mei, Zhi Chen, Boyu Ning

Movable antenna (MA) has emerged as a promising technology to enhance wireless communication performance by exploiting the new degree of freedom (DoF) via antenna position optimization. In this letter, we investigate the MA-enhanced wide beam coverage over multiple subregions in the spatial domain. Specifically, we aim to maximize the minimum beam gain over

William Borrelli, Elena Danesi, Simone Dovetta, Lorenzo Tentarelli

In this paper we study a family of one-dimensional stationary cubic nonlinear Schr\"odinger (NLS) equations with periodic potentials and linear part displaying Dirac points in the dispersion relation. By introducing a suitable periodic perturbation, one can open a spectral gap around the Dirac-point energy. This allows to construct standing waves of the NLS

Devika S, Pratik Narang, Tejasvi Alladi

This work implements a lightweight Transformer model for IDS in the domain of Connected and Autonomous Vehicles

Lei Liu, Yuhao Chi, Shunqi Huang, Zhaoyang Zhang

As wireless communication applications evolve from traditional multipath environments to high-mobility scenarios like unmanned aerial vehicles, multiplexing techniques have advanced accordingly. Traditional single-carrier frequency-domain equalization (SC-FDE) and orthogonal frequency-division multiplexing (OFDM) have given way to emerging orthogonal time-fr

Aiyue Chen, Yaofu Liu, Junjian Huang, Guang Lian

In video and image generation tasks, Diffusion Transformer (DiT) models incur extremely high computational costs due to attention mechanisms, which limits their practical applications. Furthermore, with hardware advancements, a wide range of devices besides graphics processing unit (GPU), such as application-specific integrated circuit (ASIC), have been incr

Xueying Shao, He Gao

This paper presents simulations of the synchrotron self-Compton (SSC) spectrum within the Internal-Collision-induced Magnetic Reconnection and Turbulence (ICMART) model. We investigate how key parameters like the magnetization $\sigma_0$ shape the broadband spectral energy distribution by regulating the electron distribution and magnetic field strength. The

Di Liu, Han Liu, Zheng Xi

Optical spin textures with nontrivial topology hold promise for structured light and photonic information processing, yet their generation typically relies heavily on externally structured light with care. This raises questions about their universal existence and true robustness. Here, we uncover and experimentally verify a meron-like spin texture that emerg

Miklos Eper, Szilard Szabo

We use formal microlocalization to describe the Fourier--Laplace transformation between rank 3 and rank 2 D-module representations of Painleve systems. We conclude the existence of biregular morphism between the corresponding de Rham complex structures.

Federico Talamucci

This paper investigates the dynamics of nonholonomic mechanical systems, focusing on fundamental variational assumptions and the role of the transpositional rule. We analyze how the Cetaev condition and the first variation of constraints define compatible virtual displacements for systems subject to kinematic constraints, including those nonlinear in general

Andrea Ricciarini

Let $M$ be a smooth manifold, let $TM$ be its tangent bundle and $T^{*}M$ its cotangent bundle. This paper investigates integrability conditions for generalized metrics, generalized almost para-complex structures, and generalized Hermitian structures on the generalized tangent bundle of $M$, $E=TM \oplus T^{*}M$. In particular, two notions of integrability a

Sijin Li, Wei Wang

Quantum parameter estimation exploits quantum states to achieve estimation sensitivity beyond classical limit. In continuous variable (CV) regime, squeezed state has been exploited to implement deterministic phase estimation. It is however, often restricted by fragility of quantum states. The quantum phase estimation sensitivity of squeezed state is signific

Will Sawin, Mark Shusterman

For large enough (but fixed) prime powers $q$, and trace functions to squarefree moduli in $\mathbb{F}_q[u]$ with slopes at most $1$ at infinity, and no Artin--Schreier factors in their geometric global monodromy, we come close to square-root cancellation in short sums. A special case is a function field version of Hooley's Hypothesis $R^*$ for short Klooste

Xiang Fan, Jun-Qi Tao, Ze-Fang Jiang, Ben-Wei Zhang

We investigate the imprint of $\alpha$ clustering on initial spin fluctuations in relativistic $^{16}\mathrm{O}+{}^{16}\mathrm{O}$ and $^{20}\mathrm{Ne}+{}^{20}\mathrm{Ne}$ collisions at $\sqrt{s_{\mathrm{NN}}}=5.36$~TeV. Utilizing \textit{ab initio} configurations from Nuclear Lattice Effective Field Theory (NLEFT) and phenomenological $\alpha$-cluster mode

Junyu Liao, Ashwin Lall, Mitsunori Ogihara, Raymond Wong

Multi-criteria decision making in large databases is very important in real world applications. Recently, an interactive query has been studied extensively in the database literature with the advantage of both the top-k query (with limited output size) and the skyline query (which does not require users to explicitly specify their preference function). This

Chunhui Wan, Xunan Dai, Zhuo Wang, Minglei Li

The transition from static Large Language Models (LLMs) to self-improving agents is hindered by the lack of structured reasoning in traditional evolutionary approaches. Existing methods often struggle with premature convergence and inefficient exploration in high-dimensional code spaces. To address these challenges, we introduce LoongFlow, a self-evolving ag

João Augusto Sobral, Pietro M. Bonetti, Subrata Mandal, Mathias S. Scheurer

We construct spin-$3/2$ and spin-$7/2$ models on the square-octagon and checkerboard lattices that are exactly solvable with Majorana representations. They give rise to spin-liquid phases with full spin-rotation and lattice-translational symmetries but broken time-reversal symmetry. Although non-zero on elementary plaquettes, the net orbital magnetic moment

Jingzhou Chen, Dexin Chen, Fengchao Xiong, Yuntao Qian

Fine-grained remote sensing datasets often use hierarchical label structures to differentiate objects in a coarse-to-fine manner, with each object annotated across multiple levels. However, embedding this semantic hierarchy into the representation learning space to improve fine-grained detection performance remains challenging. Previous studies have applied

Pankaj Chaudhary, Neminath Hubballi, Sameer G. Kulkarni

Caching content is an inherent feature of Named Data Networks. Limited cache capacity of routers warrants that the choice of content being cached is judiciously done. Existing techniques resort to caching popular content to maximize utilization. However, these methods experience significant overhead for coordinating and estimating the popularity of content.

Jiajun Mo, Leandro M. Chinellato, Fletcher Williams, Akiko Kikkawa

Topological spin textures in frustrated intermetallics hold great promise for spintronics applications. However, understanding their origin and properties remains a significant challenge due to competing and often long-range interactions mediated by conduction electrons. Here, by combining neutron scattering experiments with theoretical modeling via unpreced

Dong-Ping Xuan, Zhi-Xi Wang, Shao-Ming Fei

Quantum speed limits (QSLs) establish intrinsic bounds on the minimum time required for the evolution of quantum systems. We present a class of QSLs formulated in terms of the two-parameter Sharma-Mittal entropy (SME), applicable to finite-dimensional systems evolving under general nonunitary dynamics. In the single-qubit case, the QSLs for both quantum chan

Hubiao Niu, Jing Zhong, Yu Zhang, Jianchun Shi

The Antarctic TianMu Staring Observation Program is a time-domain optical sky survey project carried out in Antarctica, capable of large sky coverage, high-cadence sampling, and long-period staring. It utilizes the exceptional observing conditions in Antarctica to conduct high-cadence time-domain sky surveys. At present, we have successfully developed an 18-

Dan Zhou, Jing Zhong, Jianchun Shi, Zhenghong Tang

Wide-field rapid sky surveys serve as critical observational methods for time-domain astronomical research. The Antarctic region, with several months of continuous dark nights annually, is an ideal site for time-domain astronomical observations. The Antarctic TianMu Staring Observation Project aims to deploy a fleet of small telescopes, adopting an array obs

Zunjie Xiao, Xiaoqing Zhang, Risa Higashita, Jiang Liu

Pathology context and expert experience play significant roles in clinical ocular disease diagnosis. Although deep neural networks (DNNs) have good ocular disease recognition results, they often ignore exploring the clinical pathology context and expert experience priors to improve ocular disease recognition performance and decision-making interpretability.

Nicolas Fournier, Stéphane Mischler

We show that the Kac particle system converges, as the number of particles tends to infinity, to the solution of the homogeneous Boltzmann equation, in the regime of moderately soft potentials, $\gamma \in (-2,0)$ with the common notation. This proves the propagation of chaos. We adapt the recent work of Imbert, Silvestre and Villani, to show that the Fisher

Yizhi Liu, Ruitao Pu, Shilin Xu, Yingke Chen

In recent years, Cross-Modal Retrieval (CMR) has made significant progress in the field of multi-modal analysis. However, since it is time-consuming and labor-intensive to collect large-scale and well-annotated data, the annotation of multi-modal data inevitably contains some noise. This will degrade the retrieval performance of the model. To tackle the prob

Haoyue Bai, Yiyou Sun, Wenjie Hu, Shi Qiu

Large Language Models (LLMs) display strikingly different generalization behaviors: supervised fine-tuning (SFT) often narrows capability, whereas reinforcement-learning (RL) tuning tends to preserve it. The reasons behind this divergence remain unclear, as prior studies have largely relied on coarse accuracy metrics. We address this gap by introducing a nov

Rui Chen, Junjun Guo, Hongbin Wang, Yan Xiang

Graph Representation Learning (GRL) can be fundamentally modeled as a physical process of seeking an energy equilibrium state for a node system on a latent manifold. However, existing Graph Neural Networks (GNNs) often suffer from uncontrolled energy dissipation during message passing, driving the system towards a state of Thermal Death--manifested as featur

Bogdan Dumitru

The determination of $ES(7)$ is the first open case of the planar Erd\H{o}s--Szekeres problem, where the general conjecture predicts $ES(7)=33$. We present a SAT encoding for the 33-point case based on triple-orientation variables and a 4-set convexity criterion for excluding convex 7-gons, together with convex-layer anchoring constraints. The framework yiel

Shaojing Liu, Yongsheng Zhu, Runli Li, Ximiao Wang

The development of wearable devices for terahertz (THz) integrated sensing and communication (ISAC) is pivotal for forthcoming 6G Internet of Things (IoT) and wearable optoelectronics. However, existing THz system suffers from bulkiness, narrow spectral response and limited flexibility constrained by their dependence on external antennas, complex coupling ar

Hao Zhang, Naoki Marumo, Ting Kei Pong, Akiko Takeda

We develop and analyze a single-loop algorithm for minimizing the sum of a Lipschitz differentiable function $f$, a prox-friendly proper closed function $g$ (with a closed domain on which $g$ is continuous) and the composition of another prox-friendly proper closed function $h$ (whose domain is closed on which $h$ is continuous) with a continuously different

Rohit Kumar Salla, Manoj Saravanan, Shrikar Reddy Kota

Large Language Models (LLMs) like LLaMA, Mistral, and Gemma are increasingly used in decision-critical domains such as healthcare, law, and finance, yet their reliability remains uncertain. They often make overconfident errors, degrade under input shifts, and lack clear uncertainty estimates. Existing evaluations are fragmented, addressing only isolated aspe

Dong-Ping Xuan, Zhong-Xi Shen, Wen Zhou, Zhi-Xi Wang

Quantum entanglement is a crucial resource in quantum information processing, advancing quantum technologies. The greater the uncertainty in subsystems' pure states, the stronger the quantum entanglement between them. From the dual form of $q$-concurrence ($q\geq 2$) we introduce the total concurrence. A bona fide measure of quantum entanglement is introduce

Wenye Li, Hongxu Chen, Jiacai Liu, Ke Wei

This paper studies the policy mirror descent (PMD) method, which is a general policy optimization framework in reinforcement learning and can cover a wide range of policy gradient methods by specifying difference mirror maps. Existing sample complexity analysis for policy mirror descent either focuses on the generative sampling model, or the Markovian sampli

Maximilian Blümke, Kai Schmitz, Tobias Schröder, Deepali Agarwal

The reported evidence for an isotropic gravitational-wave background (GWB) from pulsar timing array (PTA) collaborations has motivated searches for extrinsic and intrinsic anisotropies. Kinematic anisotropies may arise as a consequence of a boosted observer moving with respect to the frame in which the GWB appears isotropic. In this work, we present an analy

Shimin Liang, Nianyu Yi

Magnetic reconnection is a ubiquitous process in astrophysical plasmas and an efficient mechanism for particle acceleration. Using 2.5D magnetohydrodynamic (MHD) simulations with a co-evolving fluid-particle framework, we investigate how particle feedback affects reconnection and acceleration. Our simulations demonstrate that particle feedback to the fluid a

Nathan A. Harper, Ayantika Sengupta, Emily Y. Hwang, Scott K. Cushing

Multiphoton states are needed for quantum communication and computation. Multiphoton states are significantly more difficult to generate than one- and two-photon states because two individual down-conversion processes must be cascaded. Only efficiencies of $<100$ Hz/mW have been reported to date. We integrate two down-converters on the same thin-film lithium

Yanxi Chen, Wenhui Zhu, Xiwen Chen, Zhipeng Wang

Although Large Audio-Language Models (LALMs) deliver state-of-the-art (SOTA) performance, they frequently suffer from hallucinations, e.g. generating text not grounded in the audio input. We analyze these grounding failures and identify a distinct taxonomy: Event Omission, False Event Identity, Temporal Relation Error, and Quantitative Temporal Error. To add

Alessio Basti, Fabio Camilli

We establish $L^p$ error estimates for monotone numerical schemes approximating Hamilton-Jacobi equations on the $d$-dimensional torus. Using the adjoint method, we first prove a $L^1$ error bound of order one for finite-difference and semi-Lagrangian schemes under standard convexity assumptions on the Hamiltonian. By interpolation, we also obtain $L^p$ esti

Subrata Pachhal, Naba P. Nayak, Soumya Bera, Adhip Agarwala

Two-dimensional non-interacting fermions without any anti-unitary symmetries generically get Anderson localized in the presence of disorder. In contrast, topological superconductors with their inherent particle-hole symmetry can host a thermal metallic phase, which is non-universal and depends on the nature of microscopic disorder. In this work, we demonstra

Negin Doostar, Mohammad Reza Heidarpour, Amir Khorsandi

The explosive growth of Internet of Things (IoT) devices has strained traditional cloud infrastructures, highlighting the need for low-latency and energy-efficient alternatives. Fog computing addresses this by placing computation near the network edge. However, limited and heterogeneous fog resources pose reliability challenges, especially for mission-critic

Minkyu Kim

Let $k$ be a unital commutative ring. In this paper, we study polynomial functors from the category of finitely generated free nilpotent groups to the category of $k$-modules, focusing on comparisons across different nilpotency classes and polynomial degrees. As a consequence, we obtain refinements of parts of the results of Baues and Pirashvili on polynomia

Xiaomei Yang, Jiaying Jia, Zhiliang Deng

The reconstruction of time-dependent Robin coefficients is a challenging inverse heat transfer problem due to its inherent ill-posedness. This paper introduces a hierarchical Bayesian approach integrated with a persistent homology (PH) prior for robust coefficient estimation. By quantifying the birth and death of topological features, the PH-based prior prov

Alexander V Turbiner, Juan Carlos Lopez Vieyra, Pavel Winternitz

In this short review paper the detailed analysis of six two-dimensional quantum {\it superintegrable} systems in flat space is presented. It includes the Smorodinsky-Winternitz potentials I-II (the Holt potential), the Fokas-Lagerstrom model, the 3-body Calogero and Wolfes (equivalently, $G_2$ rational, or $I_6$) models, and the Tremblay-Turbiner-Winternitz

Yuan Xin, Dingfan Chen, Linyi Yang, Michael Backes

As large language models (LLMs) are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model alignment to trigger harmful outputs, present significant risks, with existing studies reporting high success rates in evading common LLMs. However, previous evaluations have focused solely on the models, neglec

Sergey Sergeev

We propose a set of algebraic equations describing eigenvalues and eigenstates of a relativistic evolution operator for a two-dimensional $q$-oscillator Kagom\'e lattice. Evolution operator is constructed with the help of $q$-oscillator solution of the Tetrahedron Equation. We focus on the unitary regime of the evolution operator, so our results are related

Lucas Shen, Gaurav Sood

To what extent are users surveilled on the web, by what technologies, and by whom? We answer these questions by combining passively observed, anonymized browsing data of a large, representative sample of Americans with domain-level data on tracking from Blacklight. We find that nearly all users ($ > 99\%$) encounter at least one ad tracker or third-party coo

Natchaya Temyingyong, Daman Jain, Neeraj Kumarsahu, Prabhat Kumar

Automatic Prompt Optimization (APO) has emerged as a critical technique for enhancing Large Language Model (LLM) performance, yet current state-of-the-art methods typically rely on large, labeled gold-standard development sets to compute fitness scores for evolutionary or Reinforcement Learning (RL) approaches. In real-world software engineering, however, su

Shengsong Luo, Ruilin Wu, Chongbin Xu, Junjie Ma

This paper proposes a Chebyshev polynomial expansion framework for the recovery of a continuous angular power spectrum (APS) from channel covariance. By exploiting the orthogonality of Chebyshev polynomials in a transformed domain, we derive an exact series representation of the covariance and reformulate the inherently ill-posed APS inversion as a finite-di

Jun Xu

We provide a proof of the $n$-ary Beki\v{c} principle, which states that a vectorial fixpoint of size $n$ can be written in terms of nested fixpoints in each coordinate according to lexicographic order. The proof is inductive.

Aritra Banik, Sujoy Bhore, Palash Dey, Abhishek Sahu

The kidney exchange mechanism allows many patient-donor pairs who are otherwise incompatible with each other to come together and exchange kidneys along a cycle. However, due to infrastructure and legal constraints, kidney exchange can only be performed in small cycles in practice. In reality, there are also some altruistic donors who do not have any paired

Fazlay Ahmed, Qiang Wu, Sushant G Ghosh, Tao Zhu

We investigate gravitational wave emission from periodic timelike orbits of a test particle around a loop quantum gravity-inspired Schwarzschild black hole. The spacetime is characterised by a holonomy-correction parameter that modifies the radial metric component while preserving asymptotic flatness and the classical location of the horizon. The bound geode

Xinran Qin, Yuhui Quan, Ruotao Xu, Hui Ji

Image denoising is an important problem in low-level vision and serves as a critical module for many image recovery tasks. Anisotropic diffusion is a wide family of image denoising approaches with promising performance. However, traditional anisotropic diffusion approaches use explicit diffusion operators which are not well adapted to complex image structure