March 2026 arXiv papers — page 86

Manie Tadayon, Mayank Gupta

Recent advances in Retrieval-Augmented Generation (RAG) have revolutionized knowledge-intensive tasks, yet traditional RAG methods struggle when the search space is unknown or when documents are semi-structured or structured. We introduce a novel end-to-end Graph RAG framework that leverages both Labeled Property Graph (LPG) and Resource Description Framewor

Wen Yang, Wei Wang, Qianhan Zhou

Based on Insight-HXMT observations, we present a detailed timing analysis and spectral evolution of a complete Main High state for Her X-1 in February 2020. We determine an accurate local ephemeris using the R{\o}mer delay measured from five eclipses. We report the spin period of the neutron star at $P_{\rm spin}=1.23765212 \pm 0.00000026$ s with a spin peri

Peter J. Dolton, Richard S. J. Tol

The Nobel Memorial Prize in Economics has been awarded annually since 1969. Who wins the prize is a topic of much interest and tracks the whole course of the academic discipline over the last 57 years. Explaining who wins the prize in any given year is a complex process, which involves the subtle endogeneity of the choice of the field and the individual(s) w

Michele Circelli

We study a stochastic variant of the Team Orienteering Problem with lognormal travel times and an all-or-nothing reward policy, under which the reward of a route is lost if its travel time exceeds the available budget. We propose a reliability-aware simheuristic that combines a savings-based constructive heuristic with three specific design elements: a Top-$

Olalla A. Castro-Alvaredo

In this paper I propose a branch point twist field approach to computing the temporal entropy, that is, an entanglement measure across different time regions, as opposed to the usual spacial measures. Considering only the ground state of a gapped theory, I discuss how the shift to time-dependence manifests in form factor calculations. I show that the general

Thierry Darnige, Daniel Midtvedt, Renaud Baillou, Benjamin Perez Estay

How microorganisms respond to and interact with their environment can vary significantly from individual to individual, which can have important microbiological and ecological implications. However, most microscopy techniques can only observe motile microorganisms for short times because of their limited fields of view. Using Lagrangian tracking, a single mi

Rahul Gulia

Extremely Large Antenna Arrays (ELAA) operating at sub-terahertz frequencies introduce a regime where near-field Fresnel propagation and high-mobility carrier Doppler interact simultaneously, creating a four-dimensional signal space that existing schemes exploit only partially. This paper proposes \textbf{4D Fresnel Space-Time Modulation (4D-FSM)}, a unified

Federico Girotti, Jukka Kiukas, Mădălin Guţă

In this paper we investigate the asymptotic statistical theory of irreducible quantum Markov chains, focusing on identifiability properties and asymptotic convergence of associated quantum statistical models. We show that the space of identifiable parameters for the stationary output is a stratified space called an orbifold, which is obtained as the quotient

Jun Li, Bingqiu Chen, He Zhao, Jian Gao

The Pillars of Creation in M16 represent an iconic star-forming region where stellar feedback shapes molecular cloud evolution. We present a detailed investigation of dust extinction and density structure in the Pillars of Creation using multiband photometric observations from \emph{JWST} NIRCam. A high-resolution (2\arcsec) extinction map reaching depths of

Edoardo Cesaroni, Giampaolo Liuzzi, Stefano Lucidi

In this work, we propose derivative-free framework for bilevel optimization. We consider both the upper and lower-level problems with bound constraints on the variables, as well as general nonlinear constraints, assuming that first-order information (in the upper-level) is not available or it is impractical to obtain. The lower-level problem is solved with a

Eduard Feireisl, Maria Lukacova-Medvidova, Bangwei She, Yuhuan Yuan

We prove strong convergence of an upwind-type finite volume method to a weak solution of the Navier-Stokes-Fourier system with the Dirichlet boundary conditions. The limit solution satisfies a weak form of the mass and momentum equations, together with a weak form of the entropy and ballistic energy inequalities, and complies with the weak-strong uniqueness

Giuseppe Colletta, Susan Johny, Hua Feng, Mohammed Alkhalidi

We report the realization of multilayer three-dimensional nanobridge Josephson junctions based on Nb/NbN and Nb/TiN superconducting stacks fabricated using electron-beam lithography and chlorine-based dry etching. In this architecture, a high-resistivity nitride layer defines the geometrical weak link, while the top Nb layer sets the overall critical tempera

Sunghyun Park, Jeongho Kim, Hyoungwoo Park, Debasmit Das

Diffusion Transformers (DiTs) have significantly enhanced text-to-image (T2I) generation quality, enabling high-quality personalized content creation. However, fine-tuning these models requires substantial computational complexity and memory, limiting practical deployment under resource constraints. To tackle these challenges, we propose a memory-efficient f

Matvey Smirnov

We find an explicit expression for the Richelot isogeny of Kummer surfaces of genus 2 curves in terms of Kleinian hyperelliptic functions of weight 2. We use this expression to relate Kleinian hyperelliptic functions associated to Richelot isogenous curves.

Yoann De Figueiredo, Ulysse Delabre, Sébastien Cassagnère, Martin Romanus

Active particles locally transduce energy into motion, leading to unusual and emergent behaviors. However, current synthetic particles lack sensing and adaptation mechanisms. Here, we demonstrate a novel regulation pathway, through the combined use of thermophoretic propulsion and nanometric building blocks. We build an active fluid composed of artificial na

Saraf Krish, Cai Yiyu, Huang Li Hui

During surgeries, there is a risk of medical gauzes being left inside patients' bodies, leading to "Gossypiboma" in patients and can cause serious complications in patients and also lead to legal problems for hospitals from malpractice lawsuits and regulatory penalties. Diagnosis depends on imaging methods such as X-rays or CT scans, and the usual treatment

Vincenzo Citro, Davide Palitta

BoostConv has been introduced in earlier works as an effective acceleration technique for nonlinear iterative processes and has been successfully employed in a variety of applications to enhance convergence rates or to compute unstable fixed points that are otherwise inaccessible through standard approaches. Despite its demonstrated practical effectiveness,

Tony Lau

Prior to this work, the largest known gap between the entangled value and the classical value for a one-round two-player nonlocal game with a perfect entangled strategy using two Bell states of entanglement was $\frac{1}{9}$, achieved by the Mermin-Peres magic square game. A larger gap of $\frac{2}{15}$ has been claimed for the related doily game of Kelleher

Chun-Yen Lin

For any Dirac theory of quantum gravity governed by a set of well-defined quantum constraints, we discover a universal formula for the exact form of the evolution Hamiltonian operator in a variable quantum reference frame of our construction, expressed in terms of the quantum-constraint operators and frame-condition operators as the only inputs. Due to the f

Matta Varun, Ajay Kumar Dhakar, Yuan Hong, Shamik Sural

Graph neural network (GNN) is a powerful tool for analyzing graph-structured data. However, their vulnerability to adversarial attacks raises serious concerns, especially when dealing with sensitive information. Local Differential Privacy (LDP) offers a privacy-preserving framework for training GNNs, but its impact on adversarial robustness remains underexpl

Václav Klika, Vojtěch Kužel

We investigate the transport and adsorption of solutes within graded porous filters characterised by a spatially varying microstructure. While classical homogenisation theory typically assumes periodic media, we employ the method of multiple scales to derive an effective macroscopic model for ``near-periodic'' geometries where the porosity varies slowly over

Zuxian He, Ján Rusz

The Time Autocorrelation of Auxiliary Wave (TACAW) method has established a framework for modeling angle-resolved electron energy loss spectroscopy (EELS) of phonons and magnons by deriving scattering intensities from the time autocorrelation of the beam wavefunction. This approach enables efficient computation of scattering intensities while naturally accou

Kuan-Yu Chen, Yi-Cheng Lin, Po-Chung Hsieh, Huang-Cheng Chou

Current bias evaluations in Instruction Text-to-Speech (ITTS) often rely on univariate testing, overlooking the compositional structure of social cues. In this work, we investigate gender bias by modeling prompts as combinations of Social Status, Career stereotypes, and Persona descriptors. Analyzing open-source ITTS models, we uncover systematic interaction

Faraz Shaikh, Gianluca Reali, Mauro Femminella

In the emerging landscape of edge computing, the stochastic and bursty nature of serverless workloads presents a critical challenge for autonomous resource orchestration. Traditional reactive controllers, such as the Kubernetes Horizontal Pod Autoscaler (HPA), suffer from inherent reaction latency, leading to Service Level Objective (SLO) violations during t

Jun Li, Guanghai Guo, Pengfei Yan

In this study, we investigate the scenario in which the stochastic signal arises from primordial gravitational waves. Within this framework, we consider two distinct possibilities: one in which the pulsar timing arrays (PTAs) signal corresponds to a stochastic gravitational-wave background (SGWB), and one in which it does not. Primordial gravitational waves

Xiefan Guo, Xinzhu Ma, Haiyu Zhang, Di Huang

Recent advancements in text-to-image synthesis have been largely propelled by diffusion-based models, yet achieving precise alignment between text prompts and generated images remains a persistent challenge. We find that this difficulty arises primarily from the limitations of conventional diffusion loss, which provides only implicit supervision for modeling

E. Churazov, I. I. Khabibullin, A. M. Bykov, N. N. Chugai

Unlike the complicated X-ray and radio structure observed in the North Polar Spur area, the South-Eastern part of the eROSITA bubbles can be reasonably well described as a propagating forward shock, plausibly created by the transient energy release at the Galactic Center. In this model, the physical radius of the bubble is $R_{\rm b}\sim 7-8\,{\rm kpc}$ and

Jincen Jiang, Qianyu Zhou, Yuhang Li, Kui Su

While recent Transformer and Mamba architectures have advanced point cloud representation learning, they are typically developed for single-task or single-domain settings. Directly applying them to multi-task domain generalization (DG) leads to degraded performance. Transformers effectively model global dependencies but suffer from quadratic attention cost a

Qunjie Huang, Weina Zhu

Cross-subject EEG-to-image retrieval for visual decoding is challenged by subject shift and hubness in the embedding space, which distort similarity geometry and destabilize top-k rankings, making small-k shortlists unreliable. We introduce SATTC (Structure-Aware Test-Time Calibration), a label-free calibration head that operates directly on the similarity m

Takeshi Hayashida, Koei Matsumoto, Keito Arakawa, Yves Joly

Hematite (alpha-Fe2O3) is a prototypical room temperature antiferromagnet whose time-reversal-odd magnetic structure has recently attracted renewed attention. While such magnetic symmetry can be characterized in terms of higher-order multipoles beyond the magnetic dipole, their manifestation in measurable physical phenomena has remained largely elusive. In t

Bahaa Mazloum, Alexandre Stepanetz, Benjamin Dollet, Misaki Ozawa

We numerically study confined channel flow around an obstacle using a two-dimensional soft par- ticle model, inspired by experiments performed in the same geometry. We systematically vary the polydispersity, the external driving force, and the packing fraction of the system. Our simulations capture a broad range of plastic flow phenomenologies, from highly d

Alexander Tyurin

We consider a realistic decentralized setup with bandwidth-constrained communication and derive optimal time complexities for non-convex stochastic parallel and asynchronous optimization (up to logarithmic factors). We develop the corresponding methods, Grace SGD and Leon SGD, for both homogeneous and heterogeneous settings. Unlike previous work, our optimal

Zheqiao Geng

The interaction between a particle beam and the accelerating mode of a radiofrequency (RF) cavity cause beam loading, representing the beam-induced cavity fields. Beam loading leads to amplitude and phase errors in the cavity fields and reduces the beam quality, especially in accelerators with large beam currents, wideband RF cavities, or circular machines w

Anri Lombard, Simbarashe Mawere, Temi Aina, Ethan Wolff

Decoder-only language models can be adapted to diverse tasks through instruction finetuning, but the extent to which this generalizes at small scale for low-resource languages remains unclear. We focus on the languages of South Africa, where we are not aware of a publicly available decoder-only model that explicitly targets all eleven official written langua

Jun Du

Existing multi-object tracking algorithms typically fail to adequately address the issues in low-quality videos, resulting in a significant decline in tracking performance when image quality deteriorates in real-world scenarios. This performance degradation is primarily due to the algorithms' inability to effectively tackle the problems caused by information

Fan Huang

Existing prompting paradigms structure LLM reasoning in limited topologies: Chain-of-Thought (CoT) produces linear traces, while Tree-of-Thought (ToT) performs branching search. Yet complex reasoning often requires merging intermediate results, revisiting hypotheses, and integrating evidence from multiple sources. We propose Network-of-Thought (NoT), a frame

Jose Luis Lima de Jesus Silva

Acoustic borehole images provide high-resolution borehole-wall structure, but large-scale interpretation remains difficult because dense expert annotations are rarely available and subsurface information is intrinsically multimodal. The challenge is developing weakly supervised methods combining two-dimensional image texture with depth-aligned one-dimensiona

Dragana Bajovic, Dusan Jakovetic, Soummya Kar, Manojlo Vukovic

We present an algorithm for distributed estimation of an unknown vector parameter $\boldsymbol{\theta}^\ast \in {\mathbb R}^M$ in the presence of heavy-tailed observation and communication noises. Heavy-tailed noises frequently appear, e.g., in densely deployed Internet of Things (IoT) or wireless sensor network systems. The presented algorithm falls within

Eric Czech, Zhiwei Xu, Yael Elmatad, Yixin Wang

Chinchilla Approach 2 is among the most widely used methods for fitting neural scaling laws. Its parabolic approximation introduces systematic biases in compute-optimal allocation estimates, even on noise-free synthetic data. Applied to published Llama 3 IsoFLOP data at open frontier compute scales, these biases imply a parameter underallocation correspondin

Mymuna Monem, Ian L. Dryden, Florence George, Natalia Soares Quinete

Regression with compositional responses is challenging due to the nonlinear geometry of the simplex and the limitations of Euclidean methods. We propose a regression framework for manifold-valued data based on mappings to statistically tractable intermediate spaces. For compositional data, responses are embedded in the positive orthant of the sphere and anal

Anurag Jayswal, Ajeet Kumar

In this paper, we propose a a gradient-based neural network model to solve the mathematical programming problems with complementary constraints (MPCC). In order to facilitate tractable optimization, the problem MPCC is transformed via a regularized approach into a relaxed nonlinear optimization problem NLP($\beta$). After that employing the penalty function

Zihao Wang, Yuxiang Wei, Xinpeng Zhou, Tianyu Zhang

Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language models to infer user preferences, but the derived prompts or latent codes rarely reflect them faithfully, leading to suboptimal personalization. We present Premier, a novel preference m

Zacharie Bugaud

Multi-RF Fusion achieves a test ROC-AUC of 0.8476 +/- 0.0002 on ogbg-molhiv (10 seeds), placing #1 on the OGB leaderboard ahead of HyperFusion (0.8475 +/- 0.0003). The core of the method is a rank-averaged ensemble of 12 Random Forest models trained on concatenated molecular fingerprints (FCFP, ECFP, MACCS, atom pairs -- 4,263 dimensions total), blended with

Xiaomeng Wang, Junyang Zhang

In a graph $\Gamma$, a perfect code is an independent set $C$ with the property that every vertex not in $C$ is adjacent to a unique vertex in $C$, and a total perfect code is a set $C$ of vertices of $\Gamma$ such that every vertex of $\Gamma$ is adjacent to a unique vertex in $C$. We classify these codes for generalized Petersen graphs.

Yifei Deng, Chenglong Li, Yuyang Zhang, Guyue Hu

Text-aerial person retrieval aims to identify targets in UAV-captured images from eyewitness descriptions, supporting intelligent transportation and public security applications. Compared to ground-view text--image person retrieval, UAV-captured images often suffer from degraded visual information due to drastic variations in viewing angles and flight altitu

Yafan Yang, Zufeng Zuo, Jingyu Wan, Shuyu Sun

Literature values of disjoining pressure in liquid nanofilms from different molecular simulation methods show significant discrepancies. We demonstrate that these arise from neglecting long-range dispersion interactions and inconsistent definitions of film thickness in the original Peng method. A key insight is that long-range dispersion affects surface tens

Yao Qi, Duo Chen, Qingyu Hai, Xiaoyan Li

Experimental results demonstrate a viable strategy for tuning the superconducting properties of MgB2 through the incorporation of an electroluminescent inhomogeneous phase, revealing an interfacial light-phonon-electron synergistic mechanism that enhances superconductivity in conventional phonon-mediated systems. By introducing GaP electroluminescent inhomog

Nalan Wang, Lin Chen, Zhiwei Song

Whether the sets of absolutely separable (AS) and absolutely two-qutrit positive-partial-transpose (AP) states are the same has been an open problem in entanglement theory for decades. Since they are both convex sets, we investigate the boundary and extreme points of full-rank two-qutrit AP states with exactly three distinct eigenvalues. We show that every b

Chia-Min Chang, Yu-Hsiang Cheng, Tzee-Ming Huang

For two time series $\{ (Y_t, Z_t^Y) \}_{t}$ and $\{(X_t, Z_t^X)\}_{t}$, the directional dependence of $\{ X_t \}_{t}$ on $\{ Y_t \}_{t}$ while removing the impact of $Z_t^X$ on $X_t$ and the impact of $Z_t^Y$ on $ Y_t$ can be measured by cross-quantilograms. When the two time series are obeserved over two periods of time, it can be of interest to learn whet

Qinghui Chen, Zekai Zhang, Zaigui Zhang, Kai Zhang

High inter-class similarity, extreme scale variation, and limited computational budgets hinder reliable visual recognition across diverse real-world data. Existing vision-centric and cross-modal approaches often rely on rigid fusion mechanisms and heavy annotation pipelines, leading to sub-optimal generalization. We propose the Distilled Large Language Model

Masanori Asakura, Saiei-Jaeyeong Matsubara-Heo

For a generic one-parameter degeneration of projective hypersurfaces, we show that the periods of the limiting mixed Hodge structure are generated by certain special values of logarithm, Gamma and Dirichlet $L$-functions. Our proof is based on the analytic continuation of solutions to the GKZ system.

Dong Hyun David Lee, Hyeong Jun Lee, Taek Jung Kim, Min Yong Jeong

The van der Waals (vdW) ferromagnet 1T-CrTe2 is an emerging spintronics platform, notable for its high Curie temperature (Tc) and intriguing transport properties. However, the fundamental interplay between the electron correlations and magnetism underlying its high Tc still remains elusive. Here, using density functional theory plus dynamical mean-field theo

Wojciech Szumiński, Andrzej J. Maciejewski

We study the integrability of a two-dimensional Hamiltonian system with a gyroscopic term and a non-homogeneous potential composed of two homogeneous components of different degrees. The model describes the motion of a particle in a plane under the combined influence of a central (Kepler-type) potential, a uniform magnetic field, and a superposition of homog

Zihao Zheng, Hangyu Cao, Jiayu Chen, Sicheng Tian

Vision-Language-Action (VLA) models are mainstream in embodied intelligence but face high inference costs. Edge-Cloud Collaborative (ECC) deployment offers an effective fix by easing edge-device computing pressure to meet real-time needs. However, existing ECC frameworks are suboptimal for VLA models due to two challenges: (1) Diverse model structures hinder

Yixian Gao, Songshuo Li, Yang Yang

We consider an inverse problem in information diffusion modeled by random walks on combinatorial graphs. The problem concerns reconstruction of vertex centrality from the distribution of the first passage times observed on a subset of vertices. We adapt the boundary control method to obtain a direct algorithm that computes the unobserved vertex centrality. T

Xiaoran Zhang, Jian Ding, Yuxing Duan, Haoyue Liu

Turbulence mitigation (TM) is highly ill-posed due to the stochastic nature of atmospheric turbulence. Most methods rely on multiple frames recorded by conventional cameras to capture stable patterns in natural scenarios. However, they inevitably suffer from a trade-off between accuracy and efficiency: more frames enhance restoration at the cost of higher sy

Leonardo Aguirre, José A. Capitán, David Alonso

Many natural ecosystems harbor large numbers of coexisting species competing for far fewer distinct resources, in apparent defiance of the competitive exclusion principle. Various mechanisms have been proposed to explain this apparent paradox, among the most prominent being competition--colonization trade-offs, environmental heterogeneity, and ecological neu

Lichen Wang, Shijia Hua, Yuyuan Liu, Liang Zhang

Addressing both natural and societal challenges requires collective cooperation. Studies on collective-risk social dilemmas have shown that individual decisions are influenced by the perceived risk of collective failure. However, existing feedback evolving game models often focus on a single feedback mechanism, such as the coupling between cooperation and ri

Soudeep Ghoshal, Himanshu Buckchash, Sarita Paudel, Rubén Ruiz-Torrubiano

From customer feedback to social media, understanding human sentiment in text is central to how machines can interact meaningfully with people. However, despite notable progress, accurately capturing sentiment remains a challenging task, which continues to motivate further research in this area. To this end, we introduce Non-Differential Transformer (NDT). I

Loris Ferrari

The quantum corrections to the behavior of a semi-classical gas can be expressed as a power series of the ratio $eta$ between the cube of De Broglie's thermal wavelength and the specific volume. The connection between $eta$ and the multioccupancy of quantum states is the aim of the present work. By means of a chemical/physical approach it is possible to asso

Hongyu Wang, Yuhan Jing, Yibing Shi, Enjin Zhou

Proper parameter configuration is a prerequisite for the success of Evolutionary Algorithms (EAs). While various adaptive strategies have been proposed, it remains an open question whether all control dimensions contribute equally to algorithmic scalability. To investigate this, we categorize control variables into numerical parameters (e.g., crossover and m

Wancheng Xu, Lang Cui, Tao An, Sándor Frey

Unveiling the launching and driving mechanisms of powerful jets in active galactic nuclei (AGNs) is crucial for understanding the co-evolution of supermassive black holes (SMBHs) and their host galaxies. 1156+295 is a blazar at a redshift of z=0.729 and exhibits significant variability in long-term radio monitoring. Using multi-frequency Effelsberg single-di

Yong Wang, Qifan Shen, Bao Zhang, Zijun Huang

Millimeter-wave (mmWave) radar enables contactless respiratory sensing,yet fine-grained monitoring is often degraded by nonstationary interference from body micromotions.To achieve micromotion interference removal,we propose mmWave-Diffusion,an observation-anchored conditional diffusion framework that directly models the residual between radar phase observat

Masaaki Harada, Keito Yamaguchi

Recently, double Toeplitz codes have been introduced as a generalization of double circulant codes. In this paper, we study the average weight enumerators of double Toeplitz codes. As an application, we consider the existence of double Toeplitz codes over $\mathbb{F}_q$ with some specified minimum weights for $q \in \{2,3,4\}$. We also give a classification

Yifan Yang, Lei Zou, Wendy Jepson

In the immediate aftermath of natural disasters, rapid situational awareness is critical. Traditionally, satellite observations are widely used to estimate damage extent. However, they lack the ground-level perspective essential for characterizing specific structural failures and impacts. Meanwhile, ground-level data (e.g., street-view imagery) remains large

Shixiang Liu, Zhifan Li, Hanming Yang, Jianxin Yin

Existing high-dimensional online learning methods often face the challenge that their error bounds, or per-batch sample sizes, diverge as the number of data batches increases. To address this issue, we propose an asynchronous decomposition framework that leverages summary statistics to construct a surrogate score function for current-batch learning. This fra

Manoel Siqueira, Raquel Freitag

This paper investigates morphosyntactic covariation in Brazilian Portuguese (BP) to assess whether dialectal origin can be inferred from the combined behavior of linguistic variables. Focusing on four grammatical phenomena related to pronouns, correlation and clustering methods are applied to model covariation and dialectal distribution. The results indicate

Guilherme E. L. Pexe, Lucas A. M. Rattighieri, Leandro A. Passos, Douglas Rodrigues

Finding the minimum spanning tree (MST) of a graph is an important task in computer vision, as it enables a sparse and low-cost representation of connectivity among elements (such as superpixels, points, or regions), which is useful for tasks such as segmentation, reconstruction, and clustering. In this work, we propose and evaluate a fully quantum pipeline

Linuka Ratnayake, Danidu Dabare, Sanuja Rupasinghe, Warren Jayakumar

Intelligent control of RF transceivers adapting to dynamic operational conditions is essential in the modern and future communication systems. We propose a multi-agent neurosymbolic AI system, where AI agents are assigned for circuit components. Agents have an internal model and a corresponding control algorithm as its constituents. Modeling of the IF amplif

Jiarong Liang, Zhiheng Lyu, Zijie Liu, Xiangchao Chen

Executable software engineering data is valuable for training SWE agents, but scaling it remains difficult for two reasons: only a small fraction of real repository changes yield verifiable, high-signal task instances, and naively building repository-specific environments quickly becomes the dominant systems cost. We present SWE-Next, an execution-grounded f

Sumesh VP

The Ramayana is among the most influential literary traditions of South and Southeast Asia, transmitted across numerous linguistic and cultural contexts over two millennia. Despite extensive scholarship on regional Ramayana traditions, computational resources enabling systematic cross-linguistic analysis remain limited. This paper introduces the IWLV Ramayan

Ruiqing Wang, Kai Zhang, Yuanzhi Zhu, Hanshu Yan

Diffusion- and flow-based models have advanced Real-world Image Super-Resolution (Real-ISR), but their multi-step sampling makes inference slow and hard to deploy. One-step distillation alleviates the cost, yet often degrades restoration quality and removes the option to refine with more steps. We present Mean Flows for Super-Resolution (MFSR), a new distill

Prudence Djagba, Kevin Haudek, Clare G. C. Franovic, Leonora Kaldaras

Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories particularly those capturing advanced reasoning remains a challenge. This study investigates augmentation strategies to improve transformer-based text classification of student responses to a physical science

Sumit Tapas Chongder

Classical supply chain risk models treat node failures as statistically independent events, systematically underestimating cascade probabilities when supplier dependencies are strongly correlated. At n=40 nodes, the full correlated failure distribution requires O(2^n) classical samples, a regime where exact simulation demands 17.6 TB of memory and over 369,0

Mikhail Lebyodkin, Maxim Gussev, Jamieson Brechtl, Tatiana Lebedkina

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structur

Parisa Omidmand, Saeid Ataei

Organizations increasingly adopt AI technologies to accelerate their performance and capacity to adapt to market dynamics. This study examines how organizations implement AI in experimental methodologies such as growth hacking, lean startup, design thinking, and agile methodology to enhance efficiency and effectiveness. We performed a systematic literature r

Zhuobin Yang, Yeyao Bao, Liangfu Lv, Jian Zhang

Spiking Neural Networks (SNNs) are promising for energy-efficient, real-time edge computing, yet their performance is often constrained by the limited adaptability of conventional leaky integrate-and-fire (LIF) neurons. Existing LIF models struggle with restricted information capacity and susceptibility to noise, leading to degraded accuracy and compromised

Kyudan Jung, Jihwan Kim, Minwoo Lee, Soyoon Kim

Recent advancements in text-to-speech technologies enable generating high-fidelity synthetic speech nearly indistinguishable from real human voices. While recent studies show the efficacy of self-supervised learning-based speech encoders for deepfake detection, these models struggle to generalize across unseen speakers. Our quantitative analysis suggests the

Sergey Kryzhevich, Yiwei Zhang

Given a dynamical system, we study the so-called space of shift functions thus introducing another vision on bifurcations and chaos. As an application of the obtained results, we give a partial solution to an open problem formulated in \cite{Misiurewicz1}: to describe all the one-dimensional maps with all the periodic orbits having the same mean value. Moreo

Yuan Qiu, Wei Li, Wei Zhang, Yi Zhou

State of health (SoH) is widely used for battery management, but it is a single scalar and offers limited interpretability. Two batteries with similar SoH can exhibit very different degradation behaviors and the lack of interpretability hinders optimal battery operation. In this paper, we propose IBAM for interpretable battery aging modelling with a neural-a

Sudip Laudari

Echo State Networks (ESNs) are a reservoir computing framework widely used for nonlinear time-series prediction. However, despite their effectiveness, randomly initialized reservoirs often contain redundant nodes, leading to unnecessary computational overhead and reduced efficiency. In this work, we propose a graph centrality-based pruning approach that inte

Canqun Xiang, Chen Yang, Jiaoyan Zhao

Capsule networks (CapsNets) are superior at modeling hierarchical spatial relationships but suffer from two critical limitations: high computational cost due to iterative dynamic routing and poor robustness under input corruptions. To address these issues, we propose IBCapsNet, a novel capsule architecture grounded in the Information Bottleneck (IB) principl

S. Al Ghafri, Y. Estaremi, S. Shamsigamchi

We provide complete characterisations of nuclear weighted composition operators between two distinct $L^p(\mu)$-spaces, where $1\leq p<\infty$. As a consequence, when the underlying measure space is non-atomic, the only nuclear weighted composition operator between $L^p(\mu)$-spaces is the zero operator.

Jianwei Chen, Zhengyang Miao, Wenjie Cai, Jiaxue Tang

Integrating structural and functional connectomes remains challenging because their relationship is non-linear and organized over nested modular hierarchies. We propose a hierarchical multiscale structure-function coupling framework for connectome integration that jointly learns individualized modular organization and hierarchical coupling across structural

Riccardo Fantoni

We solve numerically exactly a simple toy model to quantum general relativity or more properly to path integral on a curved space. We consider the thermal equilibrium of a quantum many body problem on the sphere, the surface of constant positive curvature. We use path integral Monte Carlo to measure the kinetic energy, the internal energy and the static stru

Kai Li, Shiyu Zhao

Vision-based policies are widely applied in robotics for tasks such as manipulation and locomotion. On lightweight mobile robots, however, they face a trilemma of limited scene transferability, restricted onboard computation resources, and sensor hardware cost. To address these issues, we propose a knowledge distillation approach that transfers knowledge fro

Yicai Xing

Contemporary societies face a severe crisis of demographic reproduction. Global fertility rates continue to decline precipitously, with East Asian nations exhibiting the most dramatic trends -- China's total fertility rate (TFR) fell to approximately 1.0 in 2023, while South Korea's dropped below 0.72. Simultaneously, the institution of marriage is undergoin

A. Ommi, Y. Estaremi

We provide a characterisations of nuclear weighted conditional expectation operators between different $L^p(\mu)$-spaces. As a consequence, when the underlying measure space is non-atomic, the only nuclear weighted conditional expectation operator between different $L^p(\mu)$-spaces is the zero operator.

Jay Verma Trivedi, Pankaj S. Joshi

We construct a generalized class of Joshi-Malafarina-Narayan (JMN) naked singularity spacetimes that arise as equilibrium end states of gravitational collapse with non-vanishing tangential pressure. The generalization introduces density inhomogeneity through a radially dependent mass function $F(r)=(M_0+M_n r^n)r^3$, leading to a two-parameter family of solu

Shijun Li, Yashuang Zhao, Shaopeng Xu, Shengjun Li

We consider the Keller-Segel system with logical source \begin{align*} \begin{cases} u_t = \nabla \cdot (\phi(u)\nabla u) - \nabla \cdot (\psi(u)\nabla v)+f(u), & x \in \Omega, \; t > 0, v_t = \Delta v - v + u, & x \in \Omega, \; t > 0, \end{cases} \end{align*} in a smooth bounded domain \(\Omega \subset \mathbb{R}^n\) with \(n \geq 2\), the Neumann initial-

Tianyi Huang, Caden Yang, Emily Yin, Eric Wang

Retrieval-augmented language models can retrieve relevant evidence yet still commit to answers before explicitly checking whether the retrieved context supports the conclusion. We present PAVE (Premise-Grounded Answer Validation and Editing), an inference-time validation layer for evidence-grounded question answering. PAVE decomposes retrieved context into q

P Sangeerth, Abolfazl Lavaei, Pushpak Jagtap

This paper introduces the notion of stochastic simulation-gap function, which formally quantifies the gap between an approximate mathematical model and a high-fidelity stochastic simulator. Since controllers designed for the mathematical model may fail in practice due to unmodeled gaps, the stochastic simulation-gap function enables the simulator to be inter

Haricharan Balasundaram, Karthick Krishna Mahendran, Rahul Vaze

The problem of constrained online convex optimization is considered, where at each round, once a learner commits to an action $x_t \in \mathcal{X} \subset \mathbb{R}^d$, a convex loss function $f_t$ and a convex constraint function $g_t$ that drives the constraint $g_t(x)\le 0$ are revealed. The objective is to simultaneously minimize the static regret and c

Ruixiang Liu, Zhenlong Li, Ali Khosravi Kazazi

The rapid growth in the volume, variety, and velocity of geospatial data has created data ecosystems that are highly distributed, heterogeneous, and semantically inconsistent. Existing data catalogs, portals, and infrastructures still rely largely on keyword-based search with limited semantic support, which often fails to capture user intent and leads to wea

Juncheng Chen, Tiancheng Lai, Xingpeng Wang, Bingxin Liao

Time-of-Flight (ToF) cameras possess compact design and high measurement precision to be applied to various robot tasks. However, their limited sensing range restricts deployment in large-scale scenarios. Depth completion has emerged as a potential solution to expand the sensing range of ToF cameras, but existing research lacks dedicated datasets and struggl

Xinhai Sun, Xiang Shi, Menglin Zou, Wenlong Huang

The development of embodied AI systems is increasingly constrained by the availability and structure of physical interaction data. Despite recent advances in vision-language-action (VLA) models, current pipelines suffer from high data collection cost, limited cross-embodiment alignment, and poor transfer from internet-scale visual data to robot control. We p

Balaji Dinesh Gangireddi, Aniketh Garikaparthi, Manasi Patwardhan, Arman Cohan

Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks. In addition, they also rely on weak update mechanisms, such as full-prompt rewrites or unstructured merges, which cause knowledge loss and unstable adaptation. These limitations are magnified in research-coding workflows, which involve heterogeneous repos

Yash V. Mandlecha

The Casimir effect for photons and Dirac fermion fields, and its generalization to $(D+1)$-dimensional spacetime in the continuum, is studied. We implement MIT bag boundary conditions on the lattice by treating the system as a confined fermionic slab with perfectly conducting parallel plates. Using the formalism developed for lattice fermions, we compute the

Ken'ichi Tatematsu, Atsushi Nishimura, Hideo Ogawa, Nami Sakai

Although the deuterium fraction is known to be a powerful evolutionary tracer, its variation within individual molecular cloud cores is still poorly understood. The northern $\int$-shaped filament and 20 individual starless cores in the Orion A and B clouds were mapped in the deuterated molecules of DNC and DCO$^+$ with the Receiver 7BEE installed on the Nob

Akshay Prasadan, Donald Estep, Derek Bingham

Recent work has developed a non-parametric Bayesian approach to the calibration of a computer model, which abstractly amounts to the inversion of a pushforward of stochastic input parameters by a smooth map. The framework has been used in several complex scientific applications, motivating our investigation on the continuity of the solution operator with res