March 2026 arXiv papers — page 66

SAGEA Research Team, Basab Jha, Firoj Paudel, Ujjwal Puri

We introduce SAGE Celer 2.6, the latest in our line of general-purpose Celer models from SAGEA. Celer 2.6 is available in 5B, 10B, and 27B parameter sizes and benefits from extensive architectural modifications and further pre-training on an undisclosed model. Using our Inverse Reasoning (IR) pipeline, SAGEA natively trains Celer 2.6 to validate its own logi

Ye Li, Anqi Hu, Yuanchang Ye, Shiyan Tong

Large language models (LLMs) inherently operate over a large generation space, yet conventional usage typically reports the most likely generation (MLG) as a point prediction, which underestimates the model's capability: although the top-ranked response can be incorrect, valid answers may still exist within the broader output space and can potentially be dis

Yeqi He, Liang Li, Jiehua Zhang, Yaoqi Sun

Training generative models with limited data presents severe challenges of mode collapse. A common approach is to adapt a large pretrained generative model upon a target domain with very few samples (fewer than 10), known as few-shot generative model adaptation. However, existing methods often suffer from forgetting source domain identity knowledge during ad

Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster

Generalization is a central concept in machine learning theory, yet for quantum models, it is predominantly analyzed through uniform bounds that depend on a model's overall capacity rather than the specific function learned. These capacity-based uniform bounds are often too loose and entirely insensitive to the actual training and learning process. Previous

Yongheng Han, Bing Wang

We establish the $L^p$-boundedness of the local covariant Riesz transform for differential forms on manifold $M$ with bounded $\|Rm\|$. Let $\Delta_j$ be the Hodge Laplace operator on $j$-forms. For any $p \in (1, \infty)$ and $\kappa>\kappa_0$, we show that the operator $\nabla (\Delta_j + \kappa)^{-1/2}$ is bounded on $L^p(M)$. Consequently, we obtain Cald

Jianfu Chen, Peice Hua, Cai Heng Li, Yanni Wu

This paper presents a classification of locally $2$-homogeneous designs, extending Kantor's classification of 2-transitive symmetric designs (1985).

Mingzhi Hu, Zhengyi Lu, Yong Luo

In this paper, a three-dimensional competitive Lotka-Volterra system with four limit cycles is constructed for class 28 in Zeeman's classification. Combined with existing results -- from Gyllenberg and Yan (2009) for class 27, from Wang, Huang and Wu (2011) for class 29, and from Yu, Han and Xiao (2016) for class 26 -- our finding indicates that there exist

Elisabeth Griesbauer, Leiv Rønneberg, Arnoldo Frigessi, Claudia Czado

We propose stepwise variational inference (VI) with vine copulas: a universal VI procedure that combines vine copulas with a novel stepwise estimation procedure of the variational parameters. Vine copulas consist of a nested sequence of trees built from copulas, where more complex latent dependence can be modeled with increasing number of trees. We propose t

Mattia Merluzzi, Miltiadis C. Filippou, Paolo Di Lorenzo, George C. Alexandropoulos

Wireless systems are expanding their purposes, from merely connecting humans and things to connecting intelligence and opportunistically sensing of the environment through radio-frequency signals. In this paper, we introduce the concept of triple-functional networks in which the same infrastructure and resources are shared for integrated sensing, communicati

Mikhail Khovanov, Louis-Hadrien Robert, Emmanuel Wagner

The aim of this short note is to establish a 2-equivalence between a certain 2-category of foams and that of singular Soergel bimodules of type A.

Ekaterina Bakhmeteva, Alexey Ponomarenko

This paper explores a mechanism for mitigating sovereign risk in emerging markets without risks mutualization. The mechanism involves pooling diversified portfolios of sovereign bonds and issuing them in tranches, with the senior tranche offering low-risk payoffs protected by the subordination of the junior tranches. We argue that this mechanism is feasible

S. Abe, J. Abhir, V. A. Acciari, A. Aguasca-Cabot

The Large High Altitude Air Shower Observatory (LHAASO) Collaboration has recently reported the first detection at TeV energies of a low-luminosity radio galaxy, NGC 4278. The aim of this work is to investigate the high-energy properties of NGC 4278 during the flaring and subsequent quasi-quiescent states with the Florian Goebel Major Atmospheric Gamma Imagi

Maolin Wang, Beining Bao, Gan Yuan, Hongyu Chen

Electronic health records (EHRs) and other real-world clinical data are essential for clinical research, medical artificial intelligence, and life science, but their sharing is severely limited by privacy, governance, and interoperability constraints. These barriers create persistent data silos that hinder multi-center studies, large-scale model development,

Weijun Zhuang, Yuqing Huang, Weikang Meng, Xin Li

Large-scale video-language pretraining enables strong generalization across multimodal tasks but often incurs prohibitive computational costs. Although recent advances in masked visual modeling help mitigate this issue, they still suffer from two fundamental limitations: severe visual information loss under high masking ratios and temporal information leakag

Song Liu, Zhaoyang Yin

In this paper, we consider the Cauchy problem of the 3-component Degasperis-Procesi equation. Firstly, we discuss a local well-posedness result and a blow-up criterion in the low besov space. Secondly, we study the blow-up phenomenon by using the method which does not require any conservation law. Finally, we investigate some persistence properties.

Xinxin Li, Xingyu Cui, Jin Qi, Juan Zhang

Discovering governing Partial Differential Equations (PDEs) from sparse and noisy data is a challenging issue in data-driven scientific computing. Conventional sparse regression methods often suffer from two major limitations: (i) the instability of numerical differentiation under sparse and noisy data, and (ii) the restricted flexibility of a pre-defined ca

Boris Betancourt Kamenetskaia, Qianhang Ding, Chris Kouvaris

A strongly self-interacting component of asymmetric dark matter (DM) particles can form compact dark stars (DSs). These objects have a broad spectrum of masses and radii, with distinct evolution histories from both neutron stars and black holes (BHs). We argue that these differences allow a population of DSs to contribute significantly to the astrophysical m

Joachim Gudmundsson, Yuan Sha, Sampson Wong

In the celebrated paper of Henzinger, Klein, Rao and Subramanian (1997), it was shown that planar graphs admit a linear time single-source shortest path algorithm. Their algorithm unfortunately does not extend to Euclidean graph classes. We give criteria and prove that any Euclidean graph class satisfying the criteria admits a linear time single-source short

Lucrezia Cossetti, Luca Fanelli, Fabio Pizzichillo

When studying Dirac operators, it is well known that the phenomenon of Zitterbewegung leads to a lack of convexity of the variance, which creates difficulties in the analysis of dispersive properties. In particular, standard virial methods are harder to implement in the Dirac setting. In this paper, we introduce a new approach based on the center-of-energy o

Shuangwu Qian, Xiaochan Yuan, Pengfei Liu

Dongba paintings, the treasured pictorial legacy of the Naxi people in southwestern China, feature richly layered visual elements, vivid color palettes, and pronounced ethnic and regional cultural symbolism, yet their automatic textual description remains largely unexplored owing to severe domain shift when mainstream captioning models are applied directly.

Zoe R. Jones, Elisabete da Cunha, Andrew Battisti

Spectral energy distribution (SED) models are widely used to infer the physical properties of galaxies from multi-wavelength photometry, but their accuracy is difficult to assess because the true properties of observed galaxies are generally unknown. We address this by fitting synthetic SEDs of ~31,000 star-forming galaxies drawn from the EAGLE cosmological

Gunter Bombaerts

Work on morality in large language models (LLMs) has progressed via constitutional AI, reinforcement learning from human feedback (RLHF) and systematic benchmarking, yet it still lacks tools to connect internal moral representations to regulatory obligations, to design cultural plurality across the full development stack, and to monitor how moral properties

Qirui Wang, Qi Guo, Yiding Sun, Junkai Yang

Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficult for two reasons: natural-language requests are often ambiguous and can be misrouted to visually similar checkpoints, and standard post-training quantization can distort the frag

Anshul Solanki, Sanchit Latawa, Koushik Chakraborty, Navneet Kamboj

Translating Natural Language to SQL (NL2SQL) remains a critical bottleneck for democratization of data in enterprises. Although Large Language Models (LLMs) like Gemini 2.5 and other LLMs have demonstrated impressive zero-shot capabilities, their high inference costs limit deployment at scale. This paper explores the efficacy of fine-tuning both large and sm

Frederic Zagury

The interpretation of ultraviolet Galactic interstellar extinction curves is obscured today by accumulated assumptions, such as a purported link between the 2200 A bump and metallicity, that are not firmly supported by observations. In this paper I define extinction curves as the ratio F*/F0 of the near-infrared-to-ultraviolet spectrum of a reddened star to

Tianyuan Chen, Xiaoli Yan, Zhike Xue, Jincheng Wang

We used high-resolution observations from the New Vacuum Solar Telescope and the Solar Dynamics Observatory to carry out a detailed multiwavelength analysis of the fine structures in the flare ribbon of a C3.9-class flare on 22 April 2021. A segment of the flare ribbon was rooted in a sunspot light bridge and exhibited discrete substructures, which we term "

Daniel Beckmann, Benjamin Risse

Expert eye movements provide a rich, passive source of domain knowledge in radiology, offering a powerful cue for integrating diagnostic reasoning into computer-aided analysis. However, direct integration into CNN-based systems, which historically have dominated the medical image analysis domain, is challenging: gaze recordings are sequential, temporally den

Yael Naze, Masahiro Tsujimoto, Gregor Rauw, Sean J. Gunderson

A subset of Be stars, typified by the naked-eye star gamma Cas, exhibits unusually bright and hard X-ray emission, the origin of which has remained debated for five decades. We performed high-resolution X-ray spectroscopic monitoring of gamma Cas with the Resolve instrument aboard the X-Ray Imaging and Spectroscopy Mission (XRISM). X-ray lines from the ultra

Swati Saha

This work presents measurements of the transverse-momentum-dependent observable $v_{0}(p_\mathrm{T})$ as a novel probe of radial expansion dynamics in Pb$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV with the ALICE detector. Results are reported for inclusive charged hadrons, pions, kaons, and protons across centrality intervals, using a pseudorapidit

Yeping Li, Gaofeng Wang, Tianfang Wu

This paper investigates the nonlinear stability of Taylor-Couette (TC) flows incorporating the thermal buoyancy within an annular domain characterized by small viscosity $\nu$ and thermal diffusivity $\mu$. It is well established that the buoyancy induced convection significantly impacts practical industrial applications of Taylor-Couette flow \cite{Chen2006

Ran Zhang, Yucong Lin, Zhaoli Su, Bowen Liu

Chest X-ray report generation and automated evaluation are limited by poor recognition of low-prevalence abnormalities and inadequate handling of clinically important language, including negation and ambiguity. We develop a clinician-guided framework combining human expertise and large language models for multi-label finding extraction from free-text chest X

Zaineb Ajra, Grégoire Vergotte, Stéphane Perrey, Lilian Evra

The incorporation of neuroimaging techniques such as electroenchephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has provided new opportunities for the analysis of dynamic brain processes involved in cognitive and motor functions. Despite the great contribution of the open-access neuroimaging datasets to neuroscience studies, they have ma

Ramón González Rodríguez, Brais Ramos Pérez, Ana Belén Rodríguez Raposo

Let $\mathbb{H}=(H_{1},H_{2})$ be a Hopf brace in a symmetric monoidal category ${\sf C}$. In this article it is proved that the category of modules over $\mathbb{H}$ is isomorphic to the category of modules over the smash product algebra $H_{1}\sharp H_{2}$. Furthermore, the category of modules over $\mathbb{H}$ in the sense of Zhu is characterized by the c

Runze Wang

This paper addresses Question 1 posed by Dipendra Prasad in his recent problem list: classify all irreducible smooth representations of an unramified reductive p-adic group such that the space of vectors fixed by the pro-unipotent radical of a hyperspecial maximal compact subgroup, viewed as a representation of the finite reductive group obtained as the quot

G. Fauvel, A. Arefiev, M. Manuel, K. Tangtartharakul

Stacking calorimeters also refered as bremsstrahlung cannons widely used in inertial confinement fusion and ultra-intense laser plasma experiments have become essential diagnostics for characterizing short bursts of high-energy photons and charged particles. Extracting the underlying energy spectrum from these detectors requires solving an ill-posed inverse

E. D. Gomez Anccas, E. A. MacPherson, J. Tegeler, K. Röbert

Synchronisation of parallel grid-forming inverters is crucial for stable operation of future power systems. This includes accurate and robust reactive power sharing under realistic operating conditions such as impedance mismatch and communication constraints. In this work, reactive power sharing by virtue of a distributed control law is investigated under li

Ali Dehghantanha, Sajad Homayoun

Recent AI systems combine large language models with tools, external knowledge via retrieval-augmented generation (RAG), and even autonomous multi-agent decision loops. This agentic AI paradigm greatly expands capabilities - but also vastly enlarges the attack surface. In this systematization, we map out the trust boundaries and security risks of agentic LLM

Abhinav Kumar, David A. Quint, Kinjal Dasbiswas

The collective action of actively contractile units embedded in elastic biopolymer networks plays a crucial role in regulating the network's macroscopic mechanical response. Here, we investigate how the macroscopic boundary stress in model elastic fiber networks depends on the number and nature of embedded contractile units, each exerting an isotropic force

Alexander S. Kuznetsov, Valentino Pistore, Lutz Schrottke, Klaus Biermann

Active frequency comb generation and waveform control are central challenges in the terahertz (THz) domain. In THz quantum cascade lasers (QCLs), these functions have typically been achieved through active bias modulation, which alters the operating point of the device and imposes severe limitations on its flexibility. To address these challenges, we propose

David Ohlin, Anders Rantzer, Emma Tegling

The paper shows that positive linear systems can be stabilized using positive Luenberger-type observers. This is achieved by structuring the observer as monotonically converging upper and lower bounds on the state. Analysis of the closed-loop properties under linear observer feedback gives conditions that cover a larger class than previous observer designs.

Ku-Yu Fan

This paper concerns the $p$-adic multiple zeta values of integer indices that may contain zero or negative components. We introduce the admissibility and regularizability conditions for integer indices. We define the $p$-adic multiple zeta values associated with admissible integer indices to be finite rational linear combinations of $p$-adic multiple zeta va

Georgios Pavlidis, Ioannis Kastanas

The increasing use of artificial intelligence (AI) by public authorities introduces both opportunities for innovation and significant challenges for the administrative rule of law. This article examines how the EU AI Act interacts with the fundamental principles of administrative law, with a particular focus on administrative discretion, the duty to state re

Georgios Pavlidis

The EU AI Act constitutes an important development in shaping the Union's digital regulatory architecture. The Act places fundamental rights at the heart of a risk-based governance framework. The article examines how the AI Act institutionalises a human-centric approach to AI and how the AI Act's provisions explicitly and implicitly embed the protection of r

F. Iwase

The non-Hermitian skin effect (NHSE), which drives bulk states toward system boundaries, modifies bulk-boundary correspondence and complicates the identification of topological edge modes. Although breaking translational symmetry is known to influence this behavior, a systematic comparison of different structural classes remains limited. Here we investigate

Yaolun Zhang, Ruohui Wang, Jiahao Wang, Yepeng Tang

Video understanding with multimodal large language models (MLLMs) remains challenging due to the long token sequences of videos, which contain extensive temporal dependencies and redundant frames. Existing approaches typically treat MLLMs as passive recognizers, processing entire videos or uniformly sampled frames without adaptive reasoning. Recent agent-bas

Wanying Mo, Jijia Lai, Xiaoming Wang

Browser agents built on LLMs can act in web interfaces, yet most remain confined to a single chat surface (e.g., a sidebar). This mismatch with real browsing can increase context-switching and reduce user control. We introduce \textbf{IntentWeave}, a design space of ten spatial paradigms for embedding agentic assistance across a browser, organized as a progr

Yihuan Huang, Jun Xue, Liu Jiajun, Daixian Li

Audio-Visual Speech Recognition (AVSR) has achieved remarkable progress in offline conditions, yet its robustness in real-world video conferencing (VC) remains largely unexplored. This paper presents the first systematic evaluation of state-of-the-art AVSR models across mainstream VC platforms, revealing severe performance degradation caused by transmission

Jia-Han Shih, Simon M. S. Lo, Ralf A. Wilke

Single-index models or time-to-event models are frequently applied in empirical research. These models are non-identifiable in presence of unknown (dependent) censoring or competing risks and do not give informative results in empirical analysis unless rather strong, non-testable restrictions hold. Little is known, whether the known robustness properties of

Ryoma Suzuki, Zhiyang Qi, Michimasa Inaba

To address the critical scarcity of high-quality, publicly available counseling dialogue datasets, we created Multilingual KokoroChat by translating KokoroChat, a large-scale manually authored Japanese counseling corpus, into both English and Chinese. A key challenge in this process is that the optimal model for translation varies by input, making it impossi

Georgios Pavlidis

As artificial intelligence (AI) technologies continue to advance, effective risk assessment, regulation, and oversight are necessary to ensure that AI development and deployment align with ethical principles while preserving innovation and economic competitiveness. The adoption of the EU AI Act marks an important step in this direction, establishing a harmon

Shaobo Ju, Baiyang Song, Tao Chen, Jiapeng Zhang

Due to the great saving of computation and memory overhead, token compression has become a research hot-spot for MLLMs and achieved remarkable progress in image-language tasks. However, for the video, existing methods still fall short of high-ratio token compression. We attribute this shortcoming to the insufficient modeling of temporal and continual video c

Kurt Mehlhorn, Romina Nobahari

We revisit Gabow's $O(\sqrt{n} m)$ maximum cardinality matching algorithm (The Weighted Matching Approach to Maximum Cardinality Matching, Fundamenta Informaticae, 2017). It adapts the weighted matching algorithm of Gabow and Tarjan~\cite{GT91} to maximum cardinality matching. Gabow's algorithm works iteratively. In each iteration, it constructs a maximal nu

Yuxuan Lai, Xiajing Wang, Chen Zheng

Rhetoric recognition is a critical component in automated essay scoring. By identifying rhetorical elements in student writing, AI systems can better assess linguistic and higher-order thinking skills, making it an essential task in the area of AI for education. In this paper, we leverage Large Language Models (LLMs) for the Chinese rhetoric recognition task

Chen Zheng, Yuxuan Lai, Haoyang Lu, Wentao Ma

The handwriting of Chinese characters is a fundamental aspect of learning the Chinese language. Previous automated assessment methods often framed scoring as a regression problem. However, this score-only feedback lacks actionable guidance, which limits its effectiveness in helping learners improve their handwriting skills. In this paper, we leverage vision-

Zhe Zhang, Jing Li, Wanli Xue, Xu Cheng

Assuming that neither source data nor source model parameters are accessible, black-box domain adaptation (BBDA) represents a highly practical yet challenging setting, where transferable knowledge is limited to the predictions of a black-box source model. Existing approaches exploit such knowledge via pseudo-label refinement or by leveraging vision-language

Shengrong Gu, Ye Wang, Song Wu, Rui Ma

Diffusion Transformers (DiTs) excel at generation, but their global self-attention makes controllable, reference-image-based editing a distinct challenge. Unlike U-Nets, naively injecting local appearance into a DiT can disrupt its holistic scene structure. We address this by proposing the first training-free framework specifically designed to tame DiTs for

Yuki Hashimoto, Kazuharu Bamba, Sanjay Mandal

We examine the validity of classical energy conditions in nonsingular bouncing cosmological solutions arising in quadratic curvature gravity minimally coupled to a scalar field. Focusing on the null, weak, strong, and dominant energy conditions, we perform a systematic analysis under two distinct formulations of the energy-momentum tensor. In the first appro

Richard de Grijs

Speculation about Martian canals was a recurring feature of late nineteenth-century popular astronomy. This paper examines how colonial newspapers used humour to negotiate the epistemic uncertainty and interpretive excess associated with canal theory. Drawing on over one thousand metropolitan and regional Australian newspapers published between 1877 and 1899

Richard de Grijs

Between 1875 and 1899, Mars occupied a prominent and recurring position in newspaper reporting across Europe, North America and beyond. Although the scientific and cultural dimensions of this "Mars excitement" have been well studied in metropolitan contexts, far less attention has been paid to how planetary astronomy circulated through colonial press systems

Richard de Grijs

[Abridged] In the late nineteenth century, Mars emerged as one of the most intensively reported astronomical objects in the popular press, driven by favourable oppositions, improved telescopic capabilities and growing speculation regarding planetary habitability. I examine how Mars was interpreted in Australian newspapers between the 1870s and 1899, focusing

Shaoxin Zhong, Yuchen Su, Michael Witbrock

Mitigating elderly loneliness requires policy interventions that achieve both adaptability and auditability. Existing methods struggle to reconcile these objectives: traditional agent-based models suffer from static rigidity, while direct large language model (LLM) controllers lack essential traceability. This work proposes a three-layer framework that separ

Seongju Jang, Francis Baek, SangHyun Lee

Due to the ever-changing nature of construction, many tasks on sites occur in an improvisational manner. Existing mobile construction robot studies remain limited in addressing improvisational tasks, where task-required locations, timing of task occurrence, and contextual information required for task execution are not known in advance. We propose an agent t

Jiangxu Huang, Chengjie Zhan, Zhenhua Chai, Changsheng Huang

In this work, we first propose a diffuse interface model for simulating N phase flows with solid liquid phase change. In this model, a phase field approach is adopted to capture multiphase fluid interfaces, and an enthalpy based formulation is used to describe the phase change. The volume changes resulting from density differences during phase change are inc

Dengshan Liu, Huihui Xie, Pengxiang Du, Tianshuai Shang

The influence of pressure on finite-nuclear-size corrections to atomic energy levels and electron-capture decay rate is investigated in confined hydrogenlike ions. The ions are modeled inside an impenetrable spherical cavity, with a Gaussian distribution used to represent the nuclear charge distribution. For each confinement radius used to simulate external

Kohsuke Kubota, Mitsuhiro Takahashi, Yuta Saito

Optimizing survival outcomes, such as patient survival or customer retention, is a critical objective in data-driven decision-making. Off-Policy Evaluation~(OPE) provides a powerful framework for assessing such decision-making policies using logged data alone, without the need for costly or risky online experiments in high-stakes applications. However, typic

Teng Yan, Zhengyang Pei, Chengyu Shi, Yue Yu

Deploying Vision-Language-Action (VLA) models on resource-constrained edge platforms encounters a fundamental conflict between high-latency semantic inference and the high-frequency control required for dynamic manipulation. To address the challenge, this paper presents Agile-VLA, a hierarchical framework designed for industrial pose reorientation tasks on e

Timothy M. F. Hirsch, Xiaoya Jin, Nicolas P. Mauranyapin, Nishta Arora

Solitons are universal nonlinear excitations that appear in settings as varied as optics, water waves, and quantum gases [1-5]. While reduced models of soliton dynamics are well established, their validity and dynamical behaviour in strongly nonlinear regimes with frequent interactions remain largely unexplored experimentally. Progress has been constrained b

Liang-Bi Wu, Yu-Sen Zhou, Zhe Yu, Ming-Fei Jia

We present a study of virtual absorption modes (VAMs) in Schwarzschild-de Sitter (SdS) spacetime under semi-open boundary conditions, where the VAMs correspond to total transmission modes (TTMs) with the reflection amplitude being vanished. Our numerical analysis reveals that as the reflectivity $|\mathcal{K}|$ decreases, the VAM spectra migrate systematical

Yang-Yang Yan, Wei-Jie Sheng

This paper investigates the propagation phenomena of a monotone bistable reaction-diffusion system in an exterior domain of R2. By constructing suitable sub- and supersolutions, we establish the existence and monotonicity of an entire solution originating from a V-shaped traveling front. It is further shown that, under the complete propagation condition, thi

Di Gao, Jiangshan Lan, Duojie Jia, Xingbo Zhao

We apply the light-cone QCD sum rules with chiral currents to compute transition form factors of the semileptonic decay of the charmed and bottom scalar mesons $D/B$ to $a_{0}(980)l^{+}\nu_{l}$ $(l=e$, $\mu)$, where the scalar meson $a_{0}(980)$ are firstly regarded as two quark states, and contributions from the tetraquark component are then added via prope

Xiaoming Du, Weibiao Wang

For every Sol manifold $M$, we determine the $\mathbb{Z}_2$-Thurston norm of every element in $H_2(M;\mathbb{Z}_2)$. Each Sol manifold is either a torus bundle over the circle or a torus semi-bundle, thus corresponds to a torus map. We discuss the action of this torus map on a curve complex for the torus, whose edges connect curve classes of intersection num

Zhicheng Qiu, Jiarui Meng, Tong-an Luo, Yican Huang

We propose SLARM, a feed-forward model that unifies dynamic scene reconstruction, semantic understanding, and real-time streaming inference. SLARM captures complex, non-uniform motion through higher-order motion modeling, trained solely on differentiable renderings without any flow supervision. Besides, SLARM distills semantic features from LSeg to obtain la

Pengsen Liu, Maosen Zeng, Nan Tang, Kaiyuan Li

Combining Large Language Models (LLMs) with Reinforcement Learning (RL) enables agents to interpret language instructions more effectively for task execution. However, LLMs typically lack direct perception of the physical environment, which limits their understanding of environmental dynamics and their ability to generalize to unseen tasks. To address this l

Riki Toshio, Shota Kanasugi, Jun Fujisaki, Hirotaka Oshima

We introduce STAR-magic mutation, an efficient protocol for implementing logical rotation gates on early fault-tolerant quantum computers. This protocol judiciously combines two of the latest state preparation protocols: transversal multi-rotation protocol and magic state cultivation. It achieves a logical rotation gate with a favorable error scaling of $\ma

Yang-Yang Yan, Wei-Jie Sheng

This paper is concerned with the interaction between a planar traveling front and a compact obstacle for monotone bistable reaction-diffusion systems in exterior domains. By constructing appropriate sub- and supersolutions, we first establish the existence, uniqueness and monotonicity of the entire solution emanating from a planar traveling front. In particu

Ziliang Wang, Jiahua Wu, Jun Yang, Shintaro Yamasaki

Topology optimization (TO) can be viewed as seeking an optimal solution in the design space of a given TO problem. For weakly non-linear TO problems, e.g., compliance minimization, sensitivity-based methods typically converge well, whereas for strongly non-linear problems, e.g., maximum stress minimization, stabilization strategies such as stabilization term

Chunhao Cai, Yiwu Shang, Weilin Xiao, Cong Zhang

We study boundary inference at $H=3/4$ for mixed fractional Brownian motion and mixed fractional Ornstein--Uhlenbeck models under high-frequency observation. This boundary is economically important because it separates the critical and supercritical regimes of mixed fractional dynamics. We make three contributions. First, we identify the exact critical first

Minkey Chang, Jae-Young Kim

We propose the Identifiable Variational Dynamic Factor Model (iVDFM), which learns latent factors from multivariate time series with identifiability guarantees. By applying iVAE-style conditioning to the innovation process driving the dynamics rather than to the latent states, we show that factors are identifiable up to permutation and component-wise affine

Xinhang Chen, Zhihuan Wei, Yang Hu, Zhiguo Zeng

BACKGROUND: General aviation fleet expansion demands intelligent health monitoring under computational constraints. Real-world aircraft health diagnosis requires balancing accuracy with computational constraints under extreme class imbalance and environmental uncertainty. Existing end-to-end approaches suffer from the receptive field paradox: global attentio

A. Cabrera-Martínez, J. L. López-Carmona, A. Serrano-Díaz

Let $G$ be a nontrivial connected graph with vertex set $V(G)$. A set of vertices $D\subseteq V(G)$ is called a total outer-independent dominating set of $G$ if every vertex of $G$ is adjacent to at least one vertex in $D$, and $V(G)\setminus D$ is an independent set of $G$. The total outer-independent domination number of $G$, denoted by $\gamma_t^{oi}(G)$,

Yue Ma, Xinyu Wang, Qianli Ma, Qinghe Wang

In this paper, we tackle the problem of performing consistent and unified modifications across a set of related images. This task is particularly challenging because these images may vary significantly in pose, viewpoint, and spatial layout. Achieving coherent edits requires establishing reliable correspondences across the images, so that modifications can b

Chunxiao Li, Lijun Li, Jing Shao

The rapid advancement of Vision-Language Models (VLMs) has brought their safety vulnerabilities into sharp focus. However, existing red teaming methods are fundamentally constrained by an inherent linear exploration paradigm, confining them to optimizing within a predefined strategy set and preventing the discovery of novel, diverse exploits. To transcend th

Evagoras Makridis, Themistoklis Charalambous

Sequential decision-making under uncertainty often involves multiple agents learning which actions (arms) yield the highest rewards through repeated interaction with a stochastic environment. This setting is commonly modeled by cooperative multi-agent multi-armed bandit problems, where agents explore and share information without centralized coordination. In

Minkey Chang

We study whether a risk-sensitive objective from asset-pricing theory -- recursive utility -- improves reinforcement learning for portfolio allocation. The Bellman equation under recursive utility involves a certainty equivalent (CE) of future value that has no closed form under observed returns; we approximate it by $K$-sample Monte Carlo and train actor-cr

Linwei Tao, Haoyang Luo, Minjing Dong, Chang Xu

Confidence calibration assumes a unique ground-truth label per input, yet this assumption fails wherever annotators genuinely disagree. Post-hoc calibrators fitted on majority-voted labels, the standard single-label targets used in practice, can appear well-calibrated under conventional evaluation yet remain substantially miscalibrated against the underlying

Herbert Batte, Florian Luca, Pantelimon Stănică

Let $k\ge 2$ and $\{L_n^{(k)}\}_{n\geq 2-k}$ be the sequence of $k$-Lucas numbers whose first $k$ terms are $0,\ldots,0,2,1$ and each term afterwards is the sum of the preceding $k$ terms. In this paper, we solve the Diophantine equation $L_n^{(k)}=(p+1)p^\mathfrak{a}-1$, for a Mersenne or Fermat prime $p=2^{\ell}\pm 1$, and positive integers $n\ge 2$, $k\ge

Yunuo Cen, Daniel Ebler, Xuanyao Fong

Efficient solutions for satisfiability modulo theories (SMT) are integral in industrial applications such as hardware verification and design automation. Existing approaches are predominantly based on conflict-driven clause learning, which is structurally difficult to parallelize and therefore scales poorly. In this work, we introduce FourierSMT as a scalabl

Vinesh Vijayan, P Satishkumar, Dinesh Wankhade. R Sumathi

We investigate parametric modulation of the nonlinear coupling in the Henon Heiles system, which directly modifies intrinsic resonance structure in a manner complementary to additive forcing. Canonical perturbation theory in extended phase space yields normal forms predicting resonance tongues scaling as $\sqrt{\varepsilon}$ near commensurate frequencies. Me

Wei Luo, Haiming Yao, Wenyong Yu

Industrial anomaly detection plays a crucial role in ensuring product quality control. Therefore, proposing an effective anomaly detection model is of great significance. While existing feature-reconstruction methods have demonstrated excellent performance, they face challenges with shortcut learning, which can lead to undesirable reconstruction of anomalous

Marco Barchiesi, Duvan Henao, Carlos Mora-Corral, Rémy Rodiac

We exhibit a Lavrentiev gap phenomenon for the neo-Hookean energy in three-dimensional nonlinear elasticity. More precisely, we construct boundary data for which the infimum of the neo-Hookean energy over deformations satisfying a natural regularity and invertibility condition is strictly larger than the infimum over the weak $H^1$-closure of that class. The

Vasiliy A. Es'kin, Mikhail E. Smorkalov

Current large language models (LLMs) primarily rely on linear sequence generation and massive parameter counts, yet they severely struggle with complex algorithmic reasoning. While recent reasoning architectures, such as the Hierarchical Reasoning Model (HRM) and Tiny Recursive Model (TRM), demonstrate that compact recursive networks can tackle these tasks,

Amber Yijia Zheng, Yu-Shan Tai, Raymond A. Yeh

Recent advances in machine unlearning have focused on developing algorithms to remove specific training samples from a trained model. In contrast, we observe that not all models are equally easy to unlearn. Hence, we introduce a family of deep semi-parametric models (SPMs) that exhibit non-parametric behavior during unlearning. SPMs use a fusion module that

Yang Li, Yule Liu, Xinlei He, Youjian Zhao

Although Large Language Models (LLMs) have evolved from text generators into the cognitive core of modern AI systems, their inherent lack of authorization awareness exposes these systems to catastrophic risks, ranging from unintentional data leakage to unauthorized command execution. Existing defense mechanisms are fundamentally decoupled from internal reaso

Rohan Sequeira, Stavros Damianakis, Umar Iqbal, Konstantinos Psounis

Agentic computing systems, while immensely capable, raise serious security, privacy, and safety concerns. A key issue is that the full set of functionalities offered by these systems, combined with their probabilistic execution flows, is not known beforehand. Given this lack of characterization, it is challenging to validate whether a system has successfully

Li Dong, Feibo Jiang, Kezhi Wang, Cunhua Pan

Low-Altitude Wireless Networks (LAWNs), composed of Unmanned Aerial Vehicles (UAVs) and mobile terminals, are emerging as a critical extension of 6G. However, applying Large Language Models in LAWNs faces three major challenges: 1) Computational and energy constraints; 2) Communication and bandwidth limitations; 3) Real-time and reliability conflicts. To add

P. S. Sidorov, N. A. Vlasov, I. S. Terekhov, A. I. Milstein

The scheme of experiment for studying electron scattering in the field of a magnetic monopole in two dimensional electron gas is proposed. The differential scattering cross section is obtained in the eikonal approximation. For unpolarized initial electron, the differential cross section coincides with that in the field of an infinitely long solenoid, up to r

Hao Wu, Yang Huang, Huawei Zhang, Guangze Sun

It has long been predicted that the Milky Way (MW) will eventually merge with Andromeda (M31), a view reinforced by \textit{HST} measurements indicating a small M31 transverse velocity. However, using updated \textit{Gaia}-based proper motions (PMs) and including the dynamical influence of the Large Magellanic Cloud (LMC) and M33, Sawala et al. reported an M

Haoyuan Xu, Chang Li, Xinyan Ma, Xianhao Ou

Tool use enables large language models (LLMs) to access external information, invoke software systems, and act in digital environments beyond what can be solved from model parameters alone. Early research mainly studied whether a model could select and execute a correct single tool call. As agent systems evolve, however, the central problem has shifted from

Wei Luo, Haiming Yao, Zhenfeng Qiang, Xiaotian Zhang

Unsupervised anomaly detection is vital in industrial fields, with reconstruction-based methods favored for their simplicity and effectiveness. However, reconstruction methods often encounter an identical shortcut issue, where both normal and anomalous regions can be well reconstructed and fail to identify outliers. The severity of this problem increases wit

Prateek Sancheti, Kamalakar Karlapalem, Kavita Vemuri

Interlocking directorships-where individuals simultaneously serve on the boards of multiple corporations-can facilitate the exchange of expertise and strategic alignment but also present risks, including conflicts of interest, economic 'oligarchy', and regulatory non-compliance. In contexts such as large, family-controlled corporate conglomerates in India, t