March 2026 arXiv papers — page 76

Cédric Manouan, Miquilina Anagbah, N'guessan Yves-Roland Douha, João Barros

Africa's participation in modern AI development is constrained by severe infrastructural and policy gaps. Important barriers include limited access to high-performance computing (HPC), restricted cloud access due to payment system mismatches, volatile exchange rates, and strict data sovereignty laws that fragment regional collaboration between African Union

Emanuele Di Salvo, Dirk Schuricht, Joost K. Slingerland, Mikael Fremling

We investigate putative quantum Hall effect states, labeled by their K-matrix equal to (1 1 3), by defining them on the torus and computing their Hall viscosity. Such states have been introduced on the sphere as a phase distinct from Pfaffian and anti-Pfaffian ones. This was done in order to explain certain results on thermal Hall conductivity in favor of pa

Naim Elias Comar, Lucas C. Céleri, Mia Stamatova, Vlatko Vedral

We show that, given an evolving quantum system and the quasiprobability distribution generated by the spatiotemporal generalization of the Born rule in pseudo density-matrices (PDMs), this distribution deviates from the sequential measurements probability distribution, given by the L\"uders von-Neumann distribution, if and only if the non-signaling in time (

Benjamin Husson, Mohammed Belcaïd, Thomas Carle, Claire Pagetti

Convolutional neural networks (CNNs) require a large number of multiply-accumulate (MAC) operations. To meet real-time constraints, they often need to be executed on specialized accelerators composed of an on-chip memory and a processing unit. However, the on-chip memory is often insufficient to store all the data required to compute a CNN layer. Thus, the c

I. Saathoff, J. Larsson

X-ray transients on sub-observation timescales represent a diverse and underexplored class of astrophysical phenomena, from stellar flares and magnetar bursts to extragalactic fast transients and supernova shock breakouts. We present a systematic search for such events across 20,212 Chandra ACIS observations using a new detection pipeline that combines sourc

Timothy M. Chan, Hsien-Chih Chang, Jie Gao, Sándor Kisfaludi-Bak

Recent research on computing the diameter of geometric intersection graphs has made significant strides, primarily focusing on the 2D case where truly subquadratic-time algorithms were given for simple objects such as unit-disks and (axis-aligned) squares. However, in three or higher dimensions, there is no known truly subquadratic-time algorithm for any int

Maël Feurgard, Gautier Hattenberger, Nicolas Durand, Simon Lacroix

Path planning for multiple unmanned aerial vehicles is a difficult task, and even more for a fleet of fixed-wing aircraft. One specific case is the transition to, or between, formation flight patterns, which requires synchronous arrivals while ensuring minimal separation, and ideally maintaining cruise speed. We present a centralized method to solve this pro

Lars-Henrik Eriksson

Satisfiability solving is a common technique for formal verification forming the basis of many proof and model checking systems. Failure to show a proof obligation will produce a counterexample or failure trace with typically many thousands or even millions of boolean variables. Interpreting such a counterexample poses a challenge. Even if the individual var

Chen Tasker, Roy Betser, Eyal Gofer, Meir Yossef Levi

Generative models and vision encoders have largely advanced on separate tracks, optimized for different goals and grounded in different mathematical principles. Yet, they share a fundamental property: latent space Gaussianity. Generative models map Gaussian noise to images, while encoders map images to semantic embeddings whose coordinates empirically behave

Yassine Bougacha, Geoffrey Delhomme, Mélanie Ducoffe, Augustin Fuchs

This paper addresses key challenges in the development of autonomous landing systems, focusing on dataset limitations for supervised training of Machine Learning (ML) models for object detection. Our main contributions include: (1) Enhancing dataset diversity, by advocating for the inclusion of new sources such as BingMap aerial images and Flight Simulator,

Simone Nascivera, Leonard Bauersfeld, Jeff Delaune, Davide Scaramuzza

Resource-constrained autonomous robots rely on sparse direct and semi-direct visual-(inertial)-odometry (VO) pipelines, as they provide a favorable tradeoff between accuracy, robustness, and computational cost. However, the performance of most systems depends critically on hand-tuned hyperparameters governing feature detection, tracking, and outlier rejectio

Woohyeok Kim, Jaesung Rim, Daeyeon Kim, Sunghyun Cho

Burst image restoration aims to reconstruct a high-quality image from burst images, which are typically captured using manually designed exposure settings. Although these exposure settings significantly influence the final restoration performance, the problem of finding optimal exposure settings has been overlooked. In this paper, we present Dynamic Exposure

Vivek Mishra, S. Das

In the present article an endeavor is made to solve the variable order fractional diffusion equations using a powerful method viz., Homotopy Analysis method. It is demonstrated how the method can be used while solving approximately two types of variable order fractional diffusion equations having physical importance. Numerical simulation results show that th

Armand Rousselot, Joran Wendebourg, Ullrich Köthe

The performance of machine learning models is determined by the quality of their learned features. They should be invariant under irrelevant data variation but sensitive to task-relevant details. To visualize whether this is the case, we propose a method to analyze feature extractors by sampling from their fibers -- equivalence classes defined by their invar

Ralf Tönjes, Chunming Zheng, Wenping Cui, Benjamin Lindner

We analyze states of stationary activity in randomly coupled quadratic integrate-and-fire neurons using stochastic mean-field theory. Specifically, we consider the two cases of Gaussian random coupling and Cauchy random coupling, which are representative of systems with light- or with heavy-tailed synaptic strength distributions. For both, Gaussian and Cauch

Cecilia Holmgren, Jasper Ischebeck, Svante Janson

We consider additive functionals $X_n(\phi)$ with small toll functions on split trees and a generalization of split trees, which we call fractional split trees, where the split vector does not need to sum up to 1. These additive functionals encompass e.g. the number of nodes, number of leaves and the number of fringe trees of a certain size. We show converge

Aniruddha Venkata

Crossing symmetry suggests that deep inelastic scattering and semi inclusive electron-positron annihilation are governed by analytic continuations of a single forward amplitude. Drell, Levy, and Yan proposed that the hadronic tensor admits analytic continuation and demonstrated, in reasonable models, that connected contributions to the cross-section continue

Gianluca Fontanesi, Luca Barbieri, Lorenzo Galati Giordano, Alfonso Fernandez Duran

This manuscript presents a comprehensive analysis of predictive modeling optimization in managed Wi-Fi networks through the integration of clustering algorithms and model evaluation techniques. The study addresses the challenges of deploying forecasting algorithms in large-scale environments managed by a central controller constrained by memory and computati

Crédo Roselin Fanou, Kaïs Ammari, Islam Boussaada

In this work, we study the stabilization of the wave equation using an internal delayed potential. Interestingly, the stabilization mechanism is entirely induced by the delay, since exponential stabilization cannot be achieved in its absence. We first prove the well-posedness of the associated initial--boundary value problem. Then, thanks to the parametric a

Keyeun Lee, Sang Jung Kim

Cross-cutting commenting on social media is often imagined as a path to deliberation, yet exposure to opposing views frequently fuels hostility. To explain this dynamic, we introduce the concept of partisan warriors--commenters who cross ideological lines primarily to launch uncivil attacks against out-partisans. We analyze a large corpus of YouTube comments

Benxu Tang, Yunfan Ren, Yixi Cai, Fanze Kong

Determining the occupancy status of locations in the environment is a fundamental task for safety-critical robotic applications. Traditional occupancy grid mapping methods subdivide the environment into a grid of voxels, each associated with one of three occupancy states: free, occupied, or unknown. These methods explicitly maintain all voxels within the map

Zeshan Khan, Muhammad Atif Tahir

Gastrointestinal (GI) tract image analysis plays a crucial role in medical diagnosis. This research addresses the challenge of accurately classifying and segmenting GI images for real-time applications, where traditional methods often struggle due to the diversity and complexity of abnormalities. The high computational demands of this domain require efficien

Sunghwan Moon, Anwesa Dey, Souvik Roy

In photoacoustic tomography (PAT), a hybrid imaging modality that is based on the acoustic detection of optical absorption from biological tissue exposed to a pulsed laser, a short pulse laser generates an initial pressure proportional to the absorbed optical energy, which then propagates acoustically and is measured on the boundary. To account for the signi

Vincent Bruneau, Nicolas Frantz, François Nicoleau

This paper is devoted to the definition and analysis of the spectral shift function (SSF) associated with non-self-adjoint perturbations of self-adjoint operators. Motivated by applications in scattering theory, we consider both trace-class and relatively trace-class perturbations. We extend the Lifshits-Kre__n trace formula to non-self-adjoint operators und

Manuela Bechara Cannizza, Michel Albonico

Energy efficiency has become a growing concern in software development, leading to the need for tools designed to measure energy consumption. While several energy measurement tools are available as open-source projects, their characteristics and adoption remain underexplored. This work presents an empirical study based on a Mining Software Repositories (MSR)

Hanna Blazhko, Michał Wojtylak

Rigorous, non-asymptotic bounds for the Puiseux expansion of the eigenvalue at infinity are given. Error analysis is provided. Further, the expected value of the eigenvector condition number of a randomly perturbed matrix is estimated. The latter result is applied to the Cayley transform of the linear pencil. Numerical simulations illustrating the theoretica

Antonino Armato, Christian Kehl, Sebastian Fischer

Accurate and reliable safety metrics are paramount for functional safety verification of ASICs in automotive systems. Traditional FMEDA (Failure Modes, Effects, and Diagnostic Analysis) metrics, such as SPFM (Single Point Fault Metric) and LFM (Latent Fault Metric), depend on the precision of failure mode distribution (FMD) and diagnostic coverage (DC) estim

Jochen Mannhart

Recent studies have identified materials and devices whose behavior lies beyond the scope of conventional electronic-structure theory. Such theories are formulated entirely in terms of Hamiltonian evolution and therefore describe only unitary dynamics and thus only a restricted class of quantum systems. In contrast, electron systems that incorporate quantum

Yuze Qin, Qingyong Li, Zhiqing Guo, Wen Wang

Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of large-scale atmospheric context, leading to performance degradation at longer lead times. While integrating meteorological variables predicted by weather foundation models offers a potential remedy, existing architectu

J. Wang, S. Jin, D. W. Xu, WeiKang Zheng

The evolutionary role of the so-called ``changing-look'' (CL) active galactic nucleus (AGN), which is characterized by spectral-type transitions within $\sim10$ yr, has been suggested in the past few years. By focusing on CL-AGNs having spectra similar to those of broad-line Seyfert 1 galaxies, some authors have proposed that CL-AGNs tend to be at a special

Tiberiu Harko, Shahab Shahidi

We investigate the influence of boundary terms in gravitational field theories, by considering that in the Einstein-Hilbert action the boundary can be described by a non-metric Weyl-type geometry. The gravitational action and the the field equations, are thus generalized to include new geometrical terms, coming from the non-metric nature of the boundary, and

Ting Peng

This paper is accountable only to explicitly stated physical assumptions and strict logical inference. Its goal is to run a rigorous stress test of second-law claims within the Clausius framework. We work directly with \textbf{Clausius's entropy definition} for an isolated composite with energy-form conversion. Heat is withdrawn from a cold releasing subsyst

Murad Badshah, Haifa I. Alrebdi, Sana Raza Khan, Muhammad Ajaz

We present a systematic simulation study of identified hadron production in minimum bias Au+Au collisions at sqrt(sNN) = 6, 7, and 8 GeV. The event samples were generated with three modern frameworks based on different microscopic pictures: EPOS-LHC, EPOS-4, and the purely hadronic transport model SMASH. We compare observables that probe baryon stopping, tra

Esther Bosch, Michael Scholz, Anke Sauerländer-Biebl, Klas Ihme

Shifting travel from private cars to public transport is critical for meeting climate and related mobility goals, yet passengers will only choose transit if it offers a consistently positive experience. Previous studies of passenger satisfaction have largely relied on retrospective surveys, which overlook the dynamic and spatially differentiated nature of tr

Etienne Boulais, Richard D. Braatz

We present a new way to construct analytical solutions for flow in complex microfluidic channel networks, as well as planar disordered media. Using a combination of Schwarz-Christoffel maps and segmentation techniques inspired by integrated circuit analysis, we build a library of base building blocks which can be reassembled to model complex geometries, in t

Jiaqi Shang, Haojin Wu, Yinyi Lai, Zongyu Li

Deformable image registration plays a fundamental role in medical image analysis by enabling spatial alignment of anatomical structures across subjects. While recent deep learning-based approaches have significantly improved computational efficiency, many existing methods remain limited in capturing long-range anatomical correspondence and maintaining deform

J. P. McCarthy

Progress on the conjecture of Banica and Bichon that the classical permutation group is a maximal quantum subgroup of the quantum permutation group remains limited to a handful of small-parameter results. By Tannaka--Krein duality, any counterexample to this Maximality Conjecture must arise from a category strictly intermediate between the category $\mathcal

A. V. Ivanov, V. A. Nikiforov

This paper presents numerical values for auxiliary integrals and coefficients of the beta function in the three-loop approximation for a four-dimensional model with a quartic interaction, using a special type of regularization function. The values are compared to previously obtained results.

Iosif Sakos, Antonios Varvitsiotis, Georgios Korpas, Wayne Lin

In the absence of error correction, noisy intermediate-scale quantum devices are operated by training parametrized quantum circuits (PQCs) so as to minimize a suitable loss function. Finding the optimal parameters of those circuits is a hard optimization problem, where global guarantees are known only for highly structured cases of limited practical relevanc

Yuki Suganuma, Gakuto Kusuno, Hikaru Watanabe, Rikuto Oiwa

We report Raman optical activity in pyrite FeS$_2$, which hosts an electric toroidal octupolar symmetry. A clear and reproducible sign reversal of the circular intensity difference is observed between neighboring $\{111\}$ faces under cross-circular polarization. The signal appears only for the doubly degenerate $E_g$ phonon mode and is absent for other mode

Martin Latorre, Gaspar De la Barrera, Roberto E. Troncoso, Alvaro S. Nunez

Spin currents can be generated through various mechanisms, including the piezospintronic effect, which arises when strain or lattice distortions induce a change in the dipolar spin moment, causing a pure spin current without necessarily being accompanied by net charge transport. This opens new possibilities for low-power information processing and novel devi

Arnault Pachot, Thierry Petit

This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited observability. The framework converts natural-language application descriptions into bounded environmental estimates and supports a comparative online observatory of current market models. Rather than claiming dir

Xu Liu, Yongheng Zhang, Qiguang Chen, Yao Li

Recently, Interleaved-modal Chain-of-Thought (ICoT) reasoning has achieved remarkable success by leveraging both multimodal inputs and outputs, attracting increasing attention. While achieving promising performance, current ICoT methods still suffer from two major limitations: (1) Static Visual Thought Positioning, which statically inserts visual information

Quentin Baghi, Stanislas Babak, Leor Barack, Jean-Baptiste Bayle

This document sets out the conventions used for data simulations, waveforms, and analysis pipelines within the Distributed Data Processing Centre (DDPC) of the Laser Interferometer Space Antenna (LISA). It can also be considered a best practice guide for all publications related to the LISA mission. Topics covered include time-to-frequency transformations, g

Ruta Serpytyte

The fields of HCI and Participatory design have been turning to care ethics as a suitable ethos to approach current polycrisis with. Similar calls for relationality can be witnessed in public administration research and practice, albeit its current logic being built on privatisation and marketisation of services, managerialism and customer-focus; all of whic

Emma Hannula, Jana de Wiljes, Matthew T. Moores, Heikki Haario

Bayesian inference is a powerful tool for parameter estimation and uncertainty quantification in dynamical systems. However, for nonlinear oscillator networks such as Kuramoto models, widely used to study synchronization phenomena in physics, biology, and engineering, inference is often computationally prohibitive due to high-dimensional state spaces and int

Yongchan Park, Yong Soo Lee, Hansol Kim, Jaepil Park

Integrated visible photonic engines for solid-state quantum defects provide a foundation for scalable quantum networks. While miniaturization is advancing, active manipulation remains limited by the difficulty of achieving simultaneous milliwatt-scale visible light generation and high-contrast modulation. Despite extensive efforts, the concurrent chip-scale

Jaymin Bhan, JiHong Jeon, SangYeop Jeong

Recent text-driven motion generation methods span both discrete token-based approaches and continuous-latent formulations. MotionGPT3 exemplifies the latter paradigm, combining a learned continuous motion latent space with a diffusion-based prior for text-conditioned synthesis. While rectified flow objectives have recently demonstrated favorable convergence

Matthew S. Clement, Nathan A. Kaib, Andre Izidoro, Rogerio Deienno

It is thought that, sometime after their formation, the solar system's giant planets experienced a dynamical instability that caused their orbits to excite, diverge, and ejected one or more objects with masses comparable to the ice giants. A key feature of this model is that the planets experience encounters with other planetary bodies, and these encounters

Harsh Wadhwa, Rahul Bhowmick, Naipunnya Raj, Rajiv Sangle

Quantum machine learning models generally lack principled design guidelines, often requiring full resource-intensive training across numerous choices of encodings, quantum circuit designs and initialization strategies to find effective configuration. To address this challenge, we develope the Quantum Bias-Expressivity Toolbox ($\texttt{QBET}$), a framework f

Gaia Caringi, Piercesare Secchi

This work develops a multivariate extension of the Fixed Rank Kriging (FRK) framework for spatial prediction in settings where multiple spatial processes may provide complementary information. The goal is to preserve the computational efficiency, the ability to operate without assuming stationarity over the domain, and the spatial support flexibility of FRK,

Vivek Mishra, S. K. Agrawal

"Synchronization of two dynamical systems" is the term used to describe the phenomenon when two or more systems gradually change their states or behaviors to become similar or identical. This can happen in a lot of fields, such as physics, engineering, biology, and economics. Synchronization finds applications in neurology and communication systems. It is pr

Yiling Wu

Large language models are the first systems to achieve high cognitive performance without clearly undergoing representation genesis: the transition from a non-representing physical system to one whose states guide behavior in a content-sensitive way. Prior cognitive systems had already made this transition before we could examine it, and philosophy of mind t

Federico Maccagno, Jasleen Kaur, Benjamin H. November, Layan Ansari

Band structure engineering in surface acoustic wave (SAW) metamaterials could advance both classical telecommunications and quantum information processing. However, no imaging technique has demonstrated the necessary capability to resolve sub-$\mu$m traveling SAWs across wide GHz bandwidths. Existing methods capture only fragments of the dispersion at discre

Dylan Bellier, Gregory Faraut, Yan Monier, Philipp Schlehuber-Caissier

In recent years the theory of Higher Dimensional Automata (HDA) has seen significant advances from a theoretical point of view, reflecting standard automata theory. There have also been first attempts to use the mathematical framework provided by HDAs to known problems, in particular Petri Net analysis. However real-world applications are still lacking and i

A. Acharyya, F. Aharonian, C. Arcaro, H. Ashkar

Recent observational efforts using imaging atmospheric Cherenkov telescopes (IACTs) have led to firm detections of very-high-energy (VHE) signals from bright gamma-ray bursts (GRBs), often at moderate redshifts. This work presents 15 years of H.E.S.S. GRB observations and examines their implications through population comparisons and selected modelling cases

Yujiao Jiang, Quanli Shen, Ziyang Tang

We prove an asymptotic formula for the second moment of the first derivative of quadratic twists of modular $L$-functions with three leading order main terms. It improves the previous result of Kumar et al. with the first main term. The proof is based on the large sieve type inequality established by Li, with a key input that we convert the problem into comp

Jin-Cheng Deng, Yong Ru, Xin-Yue Wan, Tai-Fu Feng

We investigate the strong decays of the recently observed hidden-charm pentaquarks \(P_{\psi}^N(4312)\), \(P_{\psi}^N(4440)\), and \(P_{\psi}^N(4457)\), as well as \(P_{\psi s}^\Lambda(4338)\) and \(P_{\psi s}^\Lambda(4459)\), within the molecular framework using the effective Lagrangian approach. We construct the effective Lagrangians describing the S-wave

T. Hvozd, M. Hvozd, M. Holovko

Accurate descriptions of reference systems are a central task in liquid-state theories for the study of more complex systems. Using scaled particle theory (SPT), we derive a fully analytical description of the thermodynamic properties of a hard-sphere (HS) fluid confined in size-polydisperse HS random porous media, extending the existing approaches to higher

Yiling Wu

Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural properties of representational systems: operability, consistency, structural preservation, and compositionality. These

Kuangzhe Xu, Yu Shen, Longjie Yan, Yinghui Ren

The proliferation of Generative Artificial Intelligence has transformed benign cognitive offloading into a systemic risk of cognitive agency surrender. Driven by the commercial dogma of "zero-friction" design, highly fluent AI interfaces actively exploit human cognitive miserliness, prematurely satisfying the need for cognitive closure and inducing severe au

Yi-Hao Chen, Wenchao Wang, Jose Enrique Antonio-Lopez, Rodrigo Amezcua-Correa

Raman scattering underlies a broad range of spectroscopic and light-generation techniques, yet its conventional description, based on the Raman gain spectrum, accurately describes only long-pulse, steady-state dynamics. We present a time-domain theoretical approach that provides a unified and physically-transparent description of Raman interactions across al

Fernando Albiac, José L. Ansorena, Miguel Berasategui, Pablo M. Berná

We investigate the problem of improving the greedy-type constant of a basis by means of an equivalent renorming of the ambient Banach space. Our main result shows that if a Banach space admits an unconditional and bidemocratic basis whose fundamental function satisfies certain regularity properties, then the space can be renormed so that the basis becomes is

Hanwen Liu

We prove that for any nonlinear $f \in C^{1,\alpha}([0,1])$, the union of lines covering its graph has a Hausdorff dimension of at least $1+\alpha$, and this dimension bound is sharp. We then apply these geometric results to mathematical physics, proving that spacetime observability sets for conservation laws with $\alpha$-H\"older initial wave speeds posses

Yingnuo Qiu, Chuntao Li, Renhong Gao, Xiaochao Luo

Stimulated Brillouin microlasers offer chip-scale light sources with high spectral purity and low phase noise--key attributes for applications spanning precision metrology, quantum technologies, and coherent information processing. However, simultaneously bringing both pump and scattered waves into resonance often compromises photon confinement or modal volu

Andreas Sauter, Yuyue Zhao, Jacopo Urbani, Wenxiang Hu

Scientific idea generation is a cornerstone of autonomous knowledge discovery, yet the iterative evolution required to transform initial concepts into high-quality research proposals remains a formidable challenge for Large Language Models (LLMs). Existing Reinforcement Learning (RL) paradigms often rely on rubric-based scalar rewards that provide global qua

Kojiro Tanaka, Yoshitomo Maeda, Ryota Tomaru, Lia Corrales

We report the presence of a highly ionized absorber in the transient, eclipsing low-mass X-ray binary AX J1745.6-2901, observed from Feb. 26 to 29, 2024 with XRISM's Resolve and Xtend instruments. During a soft/high state without dips, Resolve's high spectral resolution (E/dE ~ 1000, full width at half maximum) revealed narrow velocity widths (sigma ~ 110 km

Longyu Zhou, Supeng Leng, Tianhao Liang, Jianping Yao

The development of Artificial Intelligence (AI) has enabled agentic robots an appealing paradigm for various applications, such as research and rescue in complex environment. In this context, the next wireless communication technology facilitates robot cooperation for efficient environment sensing and exploration. However, traditional AI solutions cannot alw

Yuren Cai, Guangyi Wang, Zongqing Li, Li Li

Diffusion models deliver high-fidelity generation but remain slow at inference time due to many sequential network evaluations. We find that standard timestep conditioning becomes a key bottleneck for few-step sampling. Motivated by layer-dependent denoising dynamics, we propose Multi-layer Time Embedding Optimization (MTEO), which freeze the pretrained diff

Shuo Wang, Ziyu Chen, Ming Tang

Fine-tuning large language models (LLMs) with backpropagation achieves high performance but incurs substantial memory overhead, limiting scalability on resource-constrained hardware. Zeroth-order (ZO) optimization provides a memory-efficient alternative by relying solely on forward passes, yet it typically suffers from slow or unstable convergence due to hig

Yaxuan Wang, Yifan Xiang, Ke Li, Xun Zhang

We present Triple Zero Path Planning (TZPP), a collaborative framework for heterogeneous multi-robot systems that requires zero training, zero prior knowledge, and zero simulation. TZPP employs a coordinator--explorer architecture: a humanoid robot handles task coordination, while a quadruped robot explores and identifies feasible paths using guidance from a

Jaeyoung Kim

Belle and Belle II experiments have collected $e^+e^-$ collision data with center-of-mass energies at or near the $\Upsilon(4S)$ resonance. Using total $1.4\,\mathrm{ab}^{-1}$ combined dataset, we present new measurements of branching fractions for $\Xi_c^{0/+}$ and $\Lambda_c^+$ baryons, including several first observations. Additionally, we report the init

Kaustav Chatterjee, Niklas Budinger, Kian Latifi Yaghin, Lucas Borg Clausen

Reliable quantum memory is essential for scalable quantum networks and fault-tolerant photonic quantum computing. We present a quantitative analysis of an all-optical quantum memory architecture in which a Gottesman-Kitaev-Preskill (GKP) encoded qubit is stored in a fibre loop and periodically stabilized using teleportation-based error correction. By modelli

Pengfei Cao, Mingxuan Yang, Yubo Chen, Chenlong Zhang

Understanding why real-world events occur is important for both natural language processing and practical decision-making, yet direct-cause inference remains underexplored in evidence-rich settings. To address this gap, we organized SemEval-2026 Task 12: Abductive Event Reasoning (AER).\footnote{The task data is available at https://github.com/sooo66/semeval

Huaibing Xie, Guoliang Zhao, Yang Liu, Shihan Dou

As real-world tasks grow increasingly complex, long-context reasoning has become a core capability for Large Language Models (LLMs). However, few studies explore which data types are effective for long-context reasoning and why. We find that structured table data with periodic structures shows strong potential for long-context reasoning. Motivated by this ob

Bahar Dibaei Nia, Farzan Farnia

Efficient selection among multiple generative models is increasingly important in modern generative AI, where sampling from suboptimal models is costly. This problem can be viewed as a multi-armed bandit (MAB) task. Under diversity-aware evaluation scores, a non-degenerate mixture of generators can outperform any individual model, distinguishing this MAB set

Niloofar Aminikalibar, Farzaneh Farhadi, Maria Chli

The transition to Electric Vehicles (EVs) demands intelligent, congestion-aware infrastructure planning to balance user convenience, economic viability, and traffic efficiency. We present a joint optimisation framework for EV Charging Station (CS) placement and pricing, explicitly capturing strategic driver behaviour through coupled non-atomic congestion gam

Mogens Plessen

A method for trajectory smoothing for UAV reference path planning is presented. It is derived based on the dynamics of a Dubins airplane model, and involves a decoupling step, spatial modeling and linear programming. The decoupling step enables algebraic control laws for flight-path angle and speed control. Only for roll angle control an optimization step is

Bram Lentjes, Babette A. J. de Wolff

In this paper, we introduce the notion of a characteristic operator for closable linear operators and explore their connected spectral properties via equivalence. Additionally, we develop an explicit scheme for constructing characteristic operators for a broad class of closable linear operators which are commonly encountered in periodic evolution equations.

Zekai Wu, Jiabao Jin, Peng Cheng, Xiaoyao Zhong

As the state-of-the-art methods for high-dimensional data retrieval, Approximate Nearest Neighbor Search (ANNS) approaches with graph-based indexes have attracted increasing attention and play a crucial role in many real-world applications, e.g., retrieval-augmented generation (RAG) and recommendation systems. Unlike the extensive works focused on designing

Lanqing Zhi, Hongwei Wang, Lingxiang Li, Zhi Chen

This paper studies wideband channel estimation for OFDM systems assisted by extremely large RIS (XL-RIS). Due to the large aperture of XL-RISs, the user equipment may operate in the near-field region, while the base station-XL-RIS link remains in the far field, leading to a cascaded channel with hybrid near-field and far-field characteristics. Moreover, wide

Xi Wang, Xu Yang, Donghao Sun, Cheng Deng

Long-tail class incremental learning (LT CIL) remains highly challenging because the scarcity of samples in tail classes not only hampers their learning but also exacerbates catastrophic forgetting under continuously evolving and imbalanced data distributions. To tackle these issues, we exploit the informativeness and scalability of language knowledge. Speci

Shivang Jindal, Sarunas Kaubrys, Alexei Latyntsev

We construct a vertex coproduct on the Kontsevich--Soibelman cohomological Hall algebra (CoHA) of a quiver with potential, following Joyce (2018). We show it forms a vertex bialgebra. By applying a vertex algebraic analogue of Majid--Radford bosonisation, we form an extension of the CoHA of quivers with potential which incorporates a Cartan part. In the case

Ruilin Zhang, Haiyang Zheng, Hongpeng Wang

Image clustering is a crucial but challenging task in multimedia machine learning. Recently the combination of clustering with deep learning has achieved promising performance against conventional methods on high-dimensional image data. Unfortunately, existing deep clustering methods (DC) often ignore the importance of information fusion with a global percep

J. A. Valgoma

This study presents the development and validation of an independent software tool based on the Varian Eclipse Scripting API (ESAPI) for multi-modal brachytherapy Quality Assurance (QA). The tool addresses GEC-ESTRO HDR protocols and LDR positional uncertainty analysis. Engineered in C#, the application interfaces with BrachyVision, Vitesse, and Variseed, en

Yang Liu, Boan Chen, Yuanyuan Meng, Jing Liu

As embodied perception systems increasingly bridge digital and physical realms in interactive multimedia applications, the need for privacy-preserving approaches to understand human activities in physical environments has become paramount. Video anomaly detection is a critical task in such embodied multimedia systems for intelligent surveillance and forensic

Tian Xia

Model merging has emerged as a practical approach to combine capabilities of specialized large language models (LLMs) without additional training. In the Long-to-Short (L2S) scenario, merging a base model with a long-chain-of-thought reasoning model aims to preserve reasoning accuracy while reducing output length. Existing methods rely on Task Arithmetic and

Jonathan Staaf Scragg

Self-driving laboratories (SDLs), by combining automation with machine learning-guided experiment selection, have the potential to transform experimental materials science. To date, most SDLs have been optimisation-driven, designed to rapidly converge on performance metrics, by embedding multiple mechanistic layers within platform-specific surrogate models.

Victor Jüttner, Erik Buchmann

Smart homes are increasingly targeted by cyberattacks, yet residents often lack guidance when incidents occur. Since affected residents are likely to seek help from trustworthy sources, this paper asks: What actionable cybersecurity guidance do governments provide to smart home users whose systems have been compromised? To answer this question, we conduct an

Giulio Bresciani, Angelo Vistoli, Tianzhi Yang

We introduce the notion of a neutral representation of a finite group, or finite group scheme, $G$; a representation $V$ with the property that if a gerbe $\mathcal{G}$ over a field $k$ that is a form of the classifying stack $\mathcal{B} G$ admits a vector bundle that is a form of $V$, then it is neutral, that is, $\mathcal{G}(k)$ is not empty. We give some

Yi Wang, Haofei Zhang, Qihan Huang, Anda Cao

Large Vision-Language Models (LVLMs) excel in visual understanding and reasoning, but the excessive visual tokens lead to high inference costs. Although recent token reduction methods mitigate this issue, they mainly target single-turn Visual Question Answering (VQA), leaving the more practical multi-turn VQA (MT-VQA) scenario largely unexplored. MT-VQA intr

Zelin Liu, Xiangfu Yu, Jie Huang, Ge Wang

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors, of which 15-25% develop metastatic disease with 5-year survival rates reported as low as 34%. PPGL may indicate hereditary syndromes requiring stricter, syndrome-specific treatment and surveillance, but clinicians often fail to recognize these associations in routine care. Clinical

Guillaume Bied, Philippe Caillou, Bruno Crépon, Christophe Gaillac

Recommendation systems (RSs) are increasingly used to guide job seekers on online platforms, yet the algorithms currently deployed are typically optimized for predictive objectives such as clicks, applications, or hires, rather than job seekers' welfare. We develop a job-search model with an application stage in which the value of a vacancy depends on two di

Jinhui Ren, Huaiming Li, Yabin Liu, Tao Li

High-fidelity vehicle drag evaluation is constrained less by solver runtime than by workflow friction: geometry cleanup, meshing retries, queue contention, and reproducibility failures across teams. We present a contract-centric blueprint for self-evolving coding agents that discover executable surrogate pipelines for predicting drag coefficient $C_d$ under

Nils Lid Hjort

The usual parametric models for survival data are of the following form. Some parametrically specified hazard rate $\alpha(s,\theta)$ is assumed for possibly censored random life times $X_1^0,\ldots,X_n^0$; one observes only $X_i=\min\{X_i^0,c_i\}$ and $\delta_i=I\{X_i^0\le c_i\}$ for certain censoring times $c_i$ that either are given or come from some cens

Rui Yang Tan, Yujia Hu, Roy Ka-Wei Lee

Multimodal Large Language Models (MLLMs) extend text-only LLMs with visual reasoning, but also introduce new safety failure modes under visually grounded instructions. We study comic-template jailbreaks that embed harmful goals inside simple three-panel visual narratives and prompt the model to role-play and "complete the comic." Building on JailbreakBench a

Hunmin Do, Taejun Yoon, Kiyong Jung

While Multi-Agent Debate (MAD) research has advanced, its efficacy in coordinating complex stakeholder interests such as travel planning remains largely unexplored. To bridge this gap, we propose MIND (Multi-agent Inference for Negotiation Dialogue), a framework designed to simulate realistic consensus-building among travelers with heterogeneous preferences.

Yiming Shao, Qiyu Dai, Chong Gao, Guanbin Li

Novel view synthesis (NVS) through non-planar refractive surfaces presents fundamental challenges due to severe, spatially varying optical distortions. While recent representations like NeRF and 3D Gaussian Splatting (3DGS) excel at NVS, their assumption of straight-line ray propagation fails under these conditions, leading to significant artifacts. To overc

Mugurel Barcau, Cristian Lupascu, Vicentiu Pasol, George C. Turcas

The present work investigates a type of morphisms between encryption schemes, called bridges. By associating an encryption scheme to every such bridge, we define and examine their security. Inspired by the bootstrapping procedure used by Gentry to produce fully homomorphic encryption schemes, we exhibit a general recipe for the construction of bridges. Our m

Neelmani Vispute, Aditya Kadam

As AI agents transition from human-supervised copilots to autonomous platform infrastructure, the ability to analyze their reasoning behavior across populations of investigations becomes a pressing infrastructure requirement. Existing operational tooling addresses adjacent needs effectively: state checkpoint systems enable fault tolerance; observability plat