December 2025 arXiv papers — page 54

Werner Ballmann, Sugata Mondal, Panagiotis Polymerakis

We extend the Otal-Rosas bound on the number of small eigenvalues of the Laplacian on a hyperbolic surface to the small eigenvalues of pseudo-Laplacians. In the process, we extend the work of Colin de Verdi\`ere on the spectral theory of pseudo-Laplacians to hyperbolic surfaces with more than one cusp.

Do Minh Duc, Quan Xuan Truong, Nguyen Tat Dat, Nguyen Van Vinh

Prompt engineering plays a critical role in adapting large language models (LLMs) to complex reasoning and labeling tasks without the need for extensive fine-tuning. In this paper, we propose a novel prompt optimization pipeline for frame detection in logistics texts, combining retrieval-augmented generation (RAG), few-shot prompting, chain-of-thought (CoT)

Moncef Garouani, Ayah Barhrhouj

Hyperparameters tuning is a fundamental, yet computationally expensive, step in optimizing machine learning models. Beyond optimization, understanding the relative importance and interaction of hyperparameters is critical to efficient model development. In this paper, we introduce MetaSHAP, a scalable semi-automated eXplainable AI (XAI) method, that uses met

Longxiang Shao, Dominik Huesener, Michael Schluse, Juergen Rossmann

The principle of learning from errors is pedagogically powerful but often impractical in industrial settings due to risks to safety and equipment. This paper presents an integrated training approach specifically designed for tufting machine operators. It uses hybrid digital twins, augmented reality (AR), and Petri Net-based modelling to apply the learning fr

Giacomo Nanni

We classify lagrangian fibrations on Nikulin orbifolds, a well studied class of singular irreducible holomorphic symplectic varieties, and prove they verify the SYZ conjecture.

Meng Chu, Senqiao Yang, Haoxuan Che, Suiyun Zhang

Generative models can now produce photorealistic imagery, yet they still struggle with the long, multi-goal prompts that professional designers issue. To expose this gap and better evaluate models' performance in real-world settings, we introduce Long Goal Bench (LGBench), a 2,000-task suite (1,000 T2I and 1,000 I2I) whose average instruction contains 18 to

An-Yao Jin, Rui Guo

The discovery of second harmonic generation (SHG) heralds the emergence of nonlinear optics. In this paper, we focus on the theoretical analysis of the SHG equation under phase-matching conditions. A rich family of soliton solutions are derived via the Riemann-Hilbert (RH) approach, and we characterize breather interactions corresponding to second harmonic s

Yifeng He, Junsheng Zeng, Baolin Tian, Yue Yang

We report the mechanism for the formation of external particle jets on a spherical particle bed subjected to strong explosive loading, revealing a critical dependence on particle size. Under strong explosive loading, the formation of external particle jets is primarily driven by a drag-coupled mechanism. We conducted Eulerian-Lagrangian simulations, with up

Mingxu Zhang, Dazhong Shen, Qi Zhang, Ying Sun

Large Language Models (LLMs) exhibit strong general reasoning but struggle in molecular science due to the lack of explicit chemical priors in standard string representations. Current solutions face a fundamental dilemma. Training-based methods inject priors into parameters, but this static coupling hinders rapid knowledge updates and often compromises the m

Muhammad Raihannafi Fadhel, Chalis Setyadi

We investigate the transverse parton distribution of the proton through the t-dependence of the coherent J/psi differential cross section extracted from HERA measurements in the small-x regime. Employing a simple static Gaussian hot spot model inspired by the large-x three-valence-quark picture of the proton, we introduce three geometric degrees of freedom o

Anna-Maria Gueorguieva, Aylin Caliskan

Large language models (LLMs) have been shown to exhibit social bias, however, bias towards non-protected stigmatized identities remain understudied. Furthermore, what social features of stigmas are associated with bias in LLM outputs is unknown. From psychology literature, it has been shown that stigmas contain six shared social features: aesthetics, conceal

Poonam Sharma, Suman Banerjee

Profit Maximization is one of the key objectives for social media marketing, where the task is to choose a limited number of highly influential nodes such that their initial activation leads to maximum profit. In this paper, we introduce a variant of the Profit Maximization Problem where we consider that instead of nodes, benefits are assigned to some of the

Josephine Chishala, Roberto De Propris, Mirjana Pović

Galaxy mergers are expected to have a profound influence on the star formation histories of galaxies. It is generally expected that mergers are the main drivers of galaxy mass growth through the accretion of mass and the triggering of new star formation episodes, while the shocks and torques induced by the merger may drive gas and dust to central supermassiv

Stefan Volz, Martin Storath, Andreas Weinmann

Least-absolute-deviations (LAD) line fitting is robust to outliers but computationally more involved than least squares regression. Although the literature includes linear and near-linear time algorithms for the LAD line fitting problem, these methods are difficult to implement and, to our knowledge, lack maintained public implementations. As a result, pract

Shidong Wang, Hui Liu, Ru-Shuang Zhao, Baoqiang Lao

Quasi-periodic MicroPulses (QMP) are quasi-periodic microstructural features manifested in individual pulsar radio pulses, the study of which is crucial for understanding pulsar radiation mechanisms. Manual identification of QMP in large-scale pulsar single-pulse datasets remains highly inefficient. To address this, we propose a Dual-Stage Residual Network (

Lingjun Mao, Jiawei Ren, Kun Zhou, Jixuan Chen

LLMs and VLMs are increasingly deployed as embodied agents, yet existing benchmarks largely revolve around simple short-term tasks and struggle to capture rich realistic constraints that shape real-world decision making. To close this gap, we propose DeliveryBench, a city-scale embodied benchmark grounded in the real-world profession of food delivery. Food c

Yi-Lu Luo, Yun-Ping Deng, Yuan Sun

Let $G = (V(G), E(G))$ be a simple connected graph and $\Omega$ a subset of $ V(G)$ with $|\Omega|\geq2$. An $\Omega$-path in $G$ is a path that connects all vertices of $\Omega$. Two $\Omega$-paths $P_i$ and $P_j$ are said to be internally disjoint if $V(P_i)\cap V(P_j)=\Omega$ and $E(P_i)\cap E(P_j)=\emptyset$. Denote $\pi_G(\Omega)$ by the maximum number

Zesen Wang, Yonggang Li, Lijuan Lan

Soft sensing infers hard-to-measure data through a large number of easily obtainable variables. However, in complex industrial scenarios, the issue of insufficient data volume persists, which diminishes the reliability of soft sensing. Generative Adversarial Networks (GAN) are one of the effective solutions for addressing insufficient samples. Nevertheless,

Ryan Boukrouche, Markus Janson

Teegarden's Star is one of the most promising targets for the first observations of LIFE, as a non-transiting rocky planet with similar bulk properties to the Earth, and a relatively quiescent M-dwarf host star. We use LIFEsim, a software developed by the ETH LIFE team, along with thermal emission maps obtained from a suite of three-dimensional global climat

Shuonan Wu, Yuchen Xie, Deng Pan, Lei Zhang

According to the mean-field glass theory, the (free) energy landscape of disordered systems is hierarchical and ultrametric if they belong to the full-replica-symmetry-breaking universality class. However, examining this theoretical picture in three-dimensional systems remains challenging, where the energy barriers become finite. Here, we numerically explore

Valentin Schmidberger, Manuel Eberhardinger, Setareh Maghsudi, Johannes Maucher

Document forgery poses a growing threat to legal, economic, and governmental processes, requiring increasingly sophisticated verification mechanisms. One approach involves the use of plausibility checks, rule-based procedures that assess the correctness and internal consistency of data, to detect anomalies or signs of manipulation. Although these verificatio

Shubham Dey, Sean N. Raymond

We investigate the dynamical stability of potential satellites orbiting the seven planets of the \texttt{TRAPPIST-1} system using a suite of $N$-body simulations. For each planet, we show that moons can remain stable from the Roche limit out to near the theoretical prograde stability boundary at roughly $0.5$ Hill Radii. We quantify how perturbations from ne

Beyza Zayim, Aissiou Ikram, Boukhiar Naima

Breast cancer remains the most common cancer among women and is a leading cause of female mortality. Dynamic contrast-enhanced MRI (DCE-MRI) is a powerful imaging tool for evaluating breast tumors, yet the field lacks a standardized benchmark for analyzing treatment responses and guiding personalized care. We participated in the MAMA-MIA Challenge's Primary

Giovanni Cupini, Paolo Marcellini

As explained in detail in the prologue to this manuscript, boundedness of weak solutions for general classes of elliptic equations in divergence form is a classic tool for achieving higher regularity. We propose here some global boundedness results under general assumptions that can be applied to several cases studied in the recent and extensive literature o

Simone Bnà, Giuseppe Giaquinto, Ettore Fadiga, Tommaso Zanelli

High Performance Computing (HPC) on hybrid clusters represents a significant opportunity for Computational Fluid Dynamics (CFD), especially when modern accelerators are utilized effectively. However, despite the widespread adoption of GPUs, programmability remains a challenge, particularly in open-source contexts. In this paper, we present SPUMA, a full GPU

Xiu-Cheng Wang, Jun-Jie Zhanga, Nan Cheng, Long-Gang Pang

Modern learning systems work with data that vary widely across domains, but they all ultimately depend on how much structure is already present in the measurements before any model is trained. This raises a basic question: is there a general, modality-agnostic way to quantify how acquisition itself preserves or destroys the information that downstream learne

Myriam Raymond, Lucy Neveux, Antonio A. Casilli, Paola Tubaro

The report highlights the role of Egyptian data workers in the global value chains of Artificial Intelligence (AI). These workers generate and annotate data for machine learning, check outputs, and they connect with overseas AI producers via international digital labor platforms, where they perform on-demand tasks and are typically paid by piecework, with no

Irfan Habib, Deniz Kus, Chaithra Pilakkat

Motivated by a construction of Gorelik and Shaviv, we show that the real roots of a root generated subalgebra associated with a $\pi$-system contained in the positive roots are obtained by successive applications of even and odd reflections to the $\pi$-system, and that they form a real closed subroot system. Using this result, we establish an analogue of Dy

Yunlong Liu, Shuyang Li, Pengyuan Liu, Yu Zhang

Perception research is increasingly modelled using streetscapes, yet many approaches still rely on pixel features or object co-occurrence statistics, overlooking the explicit relations that shape human perception. This study proposes a three stage pipeline that transforms street view imagery (SVI) into structured representations for predicting six perceptual

Bob Aubouin-Pairault, Mazen Alamir, Benjamin Meyer, Rémi Wolf

This study investigates the paradigm of intraoperative analgesic dosage using a data-driven approach based on retrospective clinical data. Remifentanil, an analgesic widely used during anesthesia, presents a dosing challenge due to the absence of an universally accepted indicator of analgesia. To examine how changes in patient state correlate with adjustment

Tiange Luo, Lajanugen Logeswaran, Jaekyeom Kim, Justin Johnson

Low-rank adaptation (LoRA) is widely used for parameter-efficient fine-tuning, but its standard all-token, all-head design ignores the heterogeneous structure of vision language model (VLM) inputs. We introduce \emph{Image-LoRA}, a vision-oriented PEFT recipe that views LoRA as a token-level residual update and applies this update only to visual tokens. Imag

Songpeng Pei, Xiaowan Zhang, Renzhi Su, Yongzhi Cai

We present a multi-wavelength study of the symbiotic recurrent nova (RN) T Coronae Borealis (T CrB) using Swift Burst Alert Telescope (BAT) / X-Ray Telescope (XRT) / UltraViolet Optical Telescope (UVOT) and American Association of Variable Stars Observers (AAVSO) observations from 2005 to 2025. Our analysis spans quiescent, high, and pre-eruption dip states.

J. I. Opadara, M. E. Egwe

This paper considers the properties of Dirichlet Spaces of Homogeneous type which consist of band limited functions that are nearly exponential localizations on $\mathbb{R}^k.$ This is a powerful tool in harmonic analysis and it makes various spaces of functions and distributions more approachable, utilizable and providing non-zero representation of natural

Junyao Ye, Zhen Li, Xi Tang, Shouhuai Xu

Neural code models have been increasingly incorporated into software development processes. However, their susceptibility to backdoor attacks presents a significant security risk. The state-of-the-art understanding focuses on injection-based attacks, which insert anomalous patterns into software code. These attacks can be neutralized by standard sanitization

Na Gao, Chenfei Ye, Yanwu Yang, Anqi Li

Accurate characterization of hippocampal substructure is crucial for detecting subtle structural changes and identifying early neurodegenerative biomarkers. However, high inter-subject variability and complex folding pattern of human hippocampus hinder consistent cross-subject and longitudinal analysis. Most existing approaches rely on subject-specific model

Zihao Luo, Shaohao Rui, Zhenyu Tang, Guotai Wang

Continual self-supervised learning (CSSL) in medical imaging trains a foundation model sequentially, alleviating the need for collecting multi-modal images for joint training and offering promising improvements in downstream performance while preserving data privacy. However, most existing methods still rely on replaying data from previous stages to prevent

Salvador Mengual

Einstein's equations of General Relativity form a highly nonlinear system, so most exact solutions rely on symmetry assumptions. Spherically symmetric spacetimes have been particularly important, providing a tractable yet physically rich setting. Despite extensive study, many open questions remain, especially regarding the physical interpretation of perfect

Aurélien Cordonnier, Yohann Lebouazda, Xavier Leoncini, Guilhem Dif-Pradalier

This study examines the stability of Vlasov equilibrium solutions for magnetically confined plasmas, derived through the principle of maximum entropy. By treating the toroidal limit as a perturbation from an analytical cylindrical solution, we demonstrate that these equilibria align well with the inviscid magnetohydrodynamic (MHD) description. Using the aspe

Samir Orujov, Ilgar Ismayilov, Jeyhun Huseynzade

Has broadband become a necessity good immune to price changes? Using a 15-year panel of 33 European countries (2010--2024) and two-way fixed effects with Driscoll--Kraay standard errors, we document a fundamental transformation in broadband demand. Pre-COVID, Eastern Partnership countries exhibited highly elastic demand ($\varepsilon = -0.61$, p$<$0.001) --

Jerry Wang, Ting Yiu Liu

We present an interactive framework for evaluating whether large language models (LLMs) exhibit genuine "understanding" in a simple yet strategic environment. As a running example, we focus on Rock-Paper-Scissors (RPS), which, despite its apparent simplicity, requires sequential reasoning, adaptation, and strategy recognition. Our system positions the LLM as

Gabriele Mancini, Giuseppe Mario Rago, Giusi Vaira

In this paper we will consider multi-peaks positive solutions for a class of slightly subcritical or slightly supercritical elliptic problems on an annulus with Dirichlet boundary conditions. By using the explicit form of the Green function and of the Robin function on the annulus, we prove that the annulus becomes thinner and thinner when the number of bump

Guillaume Sérieys, Alain Trouvé

L^p spaces of mappings taking values in arbitrary metric spaces, which we call nonlinear Lebesgue spaces, play an important role in several fields of mathematics. For instance, membership in these spaces is typically required for transport maps in optimal transport theory and for stochastic processes in probability theory. Nonlinear Lebesgue spaces also aris

Jun-Qin Long, Rui-Hui Lin, Xiang-Hua Zhai

We systematically investigate static plane symmetric configurations in $f(Q)$ gravity. For vacuum regions, we discuss the constancy of the nonmetricity scalar $Q$ and derive general vacuum solutions, which correspond effectively to Taub-(anti) de Sitter spacetimes with a cosmological constant determined by the specific $f(Q)$ model. By matching a singular th

Tao Zhang, Ziqian Zeng, Hao Peng, Huiping Zhuang

Long Chain-of-Thought (CoT) reasoning has significantly advanced the capabilities of Large Language Models (LLMs), but this progress is accompanied by substantial memory and latency overhead from the extensive Key-Value (KV) cache. Although KV cache quantization is a promising compression technique, existing low-bit quantization methods often exhibit severe

Yixuan Yang, Chuntao Li, Renhong Gao, Yingnuo Qiu

The integration of stimulated Raman scattering (SRS) and second order nonlinearity in non-centrosymmetric photonic microresonators presents a highly promising solution for developing on-chip coherent light sources with exceptional bandwidth and flexible tunability. Our study introduces an innovative methodology leveraging cavity polygon modes within an X-cut

Can Güngör

We present a deep study of the long-term X-ray light curve of 4U 1608-52 by investigating the fast rising exponential decay (FRED) outbursts, low intensity state (LIS) and quiescent intervals. By calibrating the onset times of the outbursts, we identify three distinct classes for the FRED-type events: (i) the long-high outbursts, exceeding ~50 d in duration

Prameshwar Thiyagarajan, Chad A. Williams

In many real-world network environments, several types of cyberattacks occur at very low rates compared to benign traffic, making them difficult for intrusion detection systems (IDS) to detect reliably. This imbalance causes traditional evaluation metrics, such as accuracy, to often overstate model performance in these conditions, masking failures on minorit

Qi He, Chunyu Qu

Rising AI electricity demand and persistent landfill methane emissions constitute coupled constraints on U.S. digital infrastructure and decarbonization. While China has achieved a rapid 'de-landfilling' transition through centralized coordination, the U.S. remains structurally 'locked in' to landfilling due to fragmented governance and carbon accounting inc

Maryem Jemri

In this work, we derive a new class of charged black holes by introducing Dunkl derivatives in the four dimensional spacetime. To construct such solutions, we first compute the Ricci tensor and the Ricci scalar using the Christoffel symbols. Substituting them into the modified Einstein field equations via extended Dunkl derivations, we obtain the metric func

Naoko Kamada, Seiichi Kamada

The notion of a welded link was introduced by Fenn, Rim\'anyi, and Rourke as an analogue of welded braids. A welded link is defined as an equivalence class of link diagrams that may contain virtual crossings, where the equivalence is generated by the classical and virtual Reidemeister moves together with the welded moves. In this paper, we introduce a parall

Mohamad Maassarani

Given two seprable irreducible polynomials $P_1$ and $P_2$ over a filed $\mathbb{K}$. We show that the rings $\mathbb{K}[X]/(P_1^n)$ and $\mathbb{K}[X]/(P_2^n)$ are isomorphic if and only if their residue fields $\mathbb{K}[X]/(P_1)$ and $\mathbb{K}[X]/(P_2)$ are isomorphic. Partial results in this direction are obtained for the case where the polynomials ar

Chenxi Huangfu, Hui Fu, Bo Li, ZhengHua Huang

Coronal cavities, often associated with prominences, are crucial structures in understanding coronal heating and the eruption mechanism of Coronal Mass Ejections (CMEs). Previous studies have identified their lower density, higher temperature, and flux rope structures. However, spectroscopic observations are still relatively scarce. In this study, we utilize

Anthony Bertrand, Engelbert Mephu Nguifo, Violaine Antoine, David Hill

Reproducibility is essential in machine learning because it ensures that a model or experiment yields the same scientific conclusion. For specific algorithms repeatability with bitwise identical results is also a key for scientific integrity because it allows debugging. We decomposed several very popular clustering algorithms: K-Means, DBSCAN and Ward into t

Leming Zhou, Zuo Wang, Zhigang Liu

Due to the insufficient diagnosis and treatment capabilities at the grassroots level, there are still deficiencies in the early identification and early warning of acute exacerbation of Chronic obstructive pulmonary disease (COPD), often resulting in a high prevalence rate and high burden, but the screening rate is relatively low. In order to gradually impro

Fabrizio Tavecchio, Dawoon E. Kim, Gabriel Emery, Ioannis Liodakis

Multiwavelength polarimetry is a powerful tool to probe magnetic field and flow geometries in the relativistic jets of blazars. In this respect, particularly interesting are the sources whose synchrotron emission covers a broad range of frequencies, from radio to X-rays, such as the BL Lac objects of the HSP type. Previous measurements including radio, optic

Olivier Merchiers, Aapo Varpula, Kirsi Tappura, Pierre-Olivier Chapuis

Thermal-radiation detectors such as bolometers -- often found as thin, suspended films -- are intrinsically limited by their optical absorption properties and by their intrinsic thermal conductive and radiative losses. We analyze the impact of the photon energy exchange between the film and a substrate located close to each other, noticing that the associate

Joe Depellette, Ewa Rej, Richa Cutting, Mika A. Sillanpää

An increasing number of studies are moving towards the combination of quantum mechanics and gravity, where studying gravity from a very small source mass is a viable starting point. Preparing for such experiments, investigations of weak gravitational forces have employed mechanical resonators to detect time-dependent gravitational forces from actuated source

Marios Thoma, Zenonas Theodosiou, Harris Partaourides, Vassilis Vassiliades

Walking has always been a primary mode of transportation and is recognized as an essential activity for maintaining good health. Despite the need for safe walking conditions in urban environments, sidewalks are frequently obstructed by various obstacles that hinder free pedestrian movement. Any object obstructing a pedestrian's path can pose a safety hazard.

Gabriel Alcaras, Donato Ricci

This article examines what it means to use Large Language Models in everyday work. Drawing on a seven-month longitudinal qualitative study, we argue that LLMs do not straightforwardly automate or augment tasks. We propose the concept of configuration work to describe the labor through which workers make a generic system usable for a specific professional tas

Zhongfeng Xu, Wei Zhu, Lionel Freire, Noëlle Billon

Laser powder bed fusion (L-PBF) of semi-crystalline polymers such as polyamide-12 (PA12) has found increasing use in various industrial applications. However, achieving high dimensional accuracy remains a significant challenge. Despite the seemingly straightforward layer-by-layer manufacturing concept, the L-PBF process involves complex thermal histories and

Suman Kumar Mondal, Takashi Shimonishi, Soumen Mondal, Prasanta Gorai

We report ALMA continuum and molecular line observations at 0.1 pc resolution toward the super star cluster (SSC) candidate H72.97-69.39 in the N79 region of the LMC. The continuum emission has a sharp peak around the SSC candidate but is also widely distributed. We identify two continuum sources at the northern (N79S-1) and northwestern (N79S-2) positions o

Jun Takeshita, Yuichiro Cho, Haruhisa Tabata, Yoshio Takahashi

Saturn's ice-covered moon Enceladus may host a subsurface ocean with biologically relevant chemistry. Plumes released from this ocean preserve information on its chemical state, and previous analyses suggest weakly to strongly alkaline pH (approximately pH 8--12). Constraining the pH requires identification of pH-sensitive minerals in plume deposits. Several

Wanting Yu, Shuiying Xiang, Xingxing Guo, Shangxuan Shi

Photonic computing shows great potential for signal processing and artificial intelligence (AI) acceleration due to its ultra-high speed, low energy consumption, and inherent parallelism. Existing photonic computing research has mainly focused on convolutional neural networks (CNNs) and fully connected neural networks (FCNNs), which are well suited for tasks

Mehdi Ramezani, Sina Asadiyan Zargar, Sadegh Salami, Abolfazl Bahrampour

We propose a Hamiltonian-based quantum state preparation method implemented via a shallow parametrized quantum circuit. The approach learns the parameters of a diagonal Hamiltonian through a classical training phase, while the quantum circuit itself performs only fixed-depth Hamiltonian evolution and mixing operations. With oracle access to the learned Hamil

Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi

Hybrid quantum and classical learning aims to couple quantum feature maps with the robustness of classical neural networks, yet most architectures treat the quantum circuit as an isolated feature extractor and merge its measurements with classical representations by direct concatenation. This neglects that the quantum and classical branches constitute distin

Naichuan Zheng, Xiahai Lun, Weiyi Li, Yuchen Du

Graph Convolutional Networks (GCNs) demonstrate strong capability in modeling skeletal topology for action recognition, yet their dense floating-point computations incur high energy costs. Spiking Neural Networks (SNNs), characterized by event-driven and sparse activation, offer energy efficiency but remain limited in capturing coupled temporal-frequency and

Guangjin Pan, Ayça Özçelikkale, Christian Häger, Musa Furkan Keskin

The growing integration of distributed integrated sensing and communication (ISAC) with closed-loop control in intelligent networks demands efficient information transmission under stringent bandwidth constraints. To address this challenge, this paper proposes a unified framework for goal-oriented semantic communication in distributed SCC systems. Building u

Taylan Yildiz, B. Tanatar

We investigate localization and persistent currents in a helical tight-binding lattice subject to two independent magnetic fluxes and a quasiperiodic on-site potential. Working with non-interacting, spinless fermions under periodic boundary conditions, we solve the model by exact diagonalization and study localization with both inverse and normalized partici

Mohamed Guessoum, Nathan Marliere, Charbel Cherfan, Remi Geiger

We present two methods to achieve real-time inertial phase compensation in atom interferometers. Both methods, based on jumps of the position of the retroreflection mirror or frequencies of Raman lasers, demonstrate similar state-of-the-art performance on our cold atom gyroscope, comparable to that of the reference method based on optical phase jumps. These

Dazhen Deng, Sen Yang, Yuchen He, Yuan Tian

Current chart-related tasks, such as chart generation (NL2Chart), chart schema parsing, chart data parsing, and chart question answering (ChartQA), are typically studied in isolation, preventing models from learning the shared semantics that link chart creation and interpretation. We introduce CycleChart, a consistency-based learning framework for bidirectio

Filippo Fabiani, Barbara Franci

We establish finite sample certificates on the quality of solutions produced by data-based forward-backward (FB) operator splitting schemes. As frequently happens in stochastic regimes, we consider the problem of finding a zero of the sum of two operators, where one is either unavailable in closed form or computationally expensive to evaluate, and shall ther

Jeffrey T. H. Wong, Cheng Zhang, Louis Mahon, Wayne Luk

Attention sinks are tokens, often the beginning-of-sequence (BOS) token, that receive disproportionately high attention despite limited semantic relevance. In this work, we identify a class of attention sinks, which we term secondary sinks, that differ fundamentally from the sinks studied in prior works, which we term primary sinks. While prior works have id

Bingyang Kelvin Liu, Ziyu Patrick Chen, David P. Woodruff

Current autoregressive language models couple high-level reasoning and low-level token generation into a single sequential process, making the reasoning trajectory vulnerable to compounding expression errors. We propose JEPA-Reasoner, a novel architectural paradigm that decouples these tasks using a Joint-Embedding Predictive Architecture (JEPA) for pure lat

Taylan Yildiz, B. Tanatar

We study the localization properties of the quasiperiodic one-dimensional helical chain with two tunneling paths: nearest-neighbor and a long-range hop that connects sites of consecutive helical turns. Using exact diagonalization, we quantify localization employing the inverse participation ratio (IPR) and the normalized participation ratio (NPR), and combin

Pierre Jehel, Pierre-Étienne Gautier, Judicaël Dehotin, Flavien Viguier

The management of railway infrastructure projects can be supported by collaborative digital platforms. A survey was carried out to identify the needs and expectations of the various stakeholders involved in the design and construction of railway infrastructure projects regarding collaborative platforms. These needs and expectations can then be translated int

Parviz Zolfaghari, Ehsan Varasteh, Koray Kavakli, Arda Gulersoy

We present a vision simulator device (Katsim), a compact near-eye optical display designed for assessing postoperative corrected vision, preoperative intraocular lens (IOL) assessment, and objective IOL characterization. The system forms a virtual image using an amplitude-modulated LCoS spatial light modulator (AM-SLM), RGB LED illumination, and a high-speed

Hugo Parada, Nicolas Vanspranghe

We show that the energy of classical solutions to the wave equation with hyperbolic boundary condition (i.e., dynamic Wentzell boundary condition) and damping on the boundary decays like 1/t. In fact we allow mixed boundary conditions: a possibly empty, disjoint part of the boundary may be kept at rest provided that the dynamic part satisfies the geometric c

Luca Reggiani, Arnaldo Spalvieri

The paper analyzes energy allocation in a scenario where the position of a moving target is tracked by exploiting the Time-of-Arrivals of bandwidth-constrained signals received by or transmitted from a fixed number of anchors located at known positions. The signal of each anchor is generated by transmitting a sequence of known symbols, allowing for amplitude

Qi-Nan Wang, Ding-Kun Lian, Hua-Xing Chen, Wei Chen

We investigate the heavy quarkonium hybrid mesons with exotic quantum numbers $J^{PC}=2^{+-}$ via QCD sum rule method. We construct the currents with three Lorentz indices and calculate the correlation functions up to dimension six at the leading order of $\alpha _{s}$. The states with $J^{PC}=2^{+-}$ are extracted by constructing the corresponding projectio

Yu-Sen An, Wei-Hao Zhang

The black hole horizon can induce chaotic motion of particles around the black hole. The original integrable motion of particles can transit to the chaotic motion when approaching black hole horizon. In this work, we consider the black hole background where quantum conformal anomaly correction is taken into account. We use Poincare section and Lyapunov expon

Alessandro Lucca, Francesco Corso, Francesco Pierri

Subtitles are essential for video accessibility and audience engagement. Modern Automatic Speech Recognition (ASR) systems, built upon Encoder-Decoder neural network architectures and trained on massive amounts of data, have progressively reduced transcription errors on standard benchmark datasets. However, their performance in real-world production environm

Patricio Guzmán, Hugo Parada, Christian Calle-Cárdenas

This paper studies the rapid stabilization of a multidimensional heat equation in the presence of an unknown spatially localized disturbance. A novel multivalued feedback control strategy is proposed, which synthesizes the frequency Lyapunov method (introduced by Xiang [41]) with the sign multivalued operator. This methodology connects Lyapunov-based stabili

Wendong Bu, Kaihang Pan, Yuze Lin, Jiacheng Li

Large language models (LLMs) have unified diverse linguistic tasks within a single framework, yet such unification remains unexplored in human motion generation. Existing methods are confined to isolated tasks, limiting flexibility for free-form and omni-objective generation. To address this, we propose OmniMoGen, a unified framework that enables versatile m

Paul-Emile Paradan

This is a monograph devoted to the study of Kirwan's real polytopes, i.e., in the context where there are involutions on the group and on the symplectic manifold. This work brings together and completes the two preprints I had already written on this subject (arXiv:2012.08837, arXiv:2111.13399).

Riccardo Bonalli, Benoît Bonnet-Weill, Laurent Pfeiffer

In this article, we propose a novel characterization of law-invariant and coherent risk measures, based on a generalized optimal transport problem in which the second marginal of the admissible plans is not fixed, but required to lie within a target set of probability measures. One of the main contributions of this work is a general representation formula fo

Yin Jun Phua

The search for reliable indicators of consciousness has fragmented into competing theoretical camps (Global Workspace Theory (GWT), Integrated Information Theory (IIT), and Higher-Order Theories (HOT)), each proposing distinct neural signatures. We adopt a synthetic neuro-phenomenology approach: constructing artificial agents that embody these mechanisms to

Geraud Nangue Tasse, Matthew Riemer, Benjamin Rosman, Tim Klinger

Recent success in developing increasingly general purpose agents based on sequence models has led to increased focus on the problem of deploying computationally limited agents within the vastly more complex real-world. A key challenge experienced in these more realistic domains is highly non-Markovian dependencies with respect to the agent's observations, wh

Xiaolan Cai, Mathieu O'Neil, Stefano Zacchiroli

This article explores the role of unrecognised labour in corporate innovation systems via an analysis of researcher coding and discursive contributions to R, one of the largest statistical software ecosystems. Studies of online platforms typically focus on how platform affordances constrain participants' actions, and profit from their labour. We innovate by

Jakub Martinka, Mikołaj Martyka, Biman Medhi, Jiří Pittner

Nonadiabatic molecular dynamics is a key technique for investigating a broad range of photochemical and photophysical processes. Among the established approaches, surface hopping schemes are widely used and can be easily integrated with various quantum chemistry programs or machine learning models. We present a flexible framework in MLatom that includes a ne

Yuanqian Fang, Wei Su, Xinyu Wang, Yongcheng Wu

Long-lived particle (LLP) is one of the well-motivated targets for current collider experiments searching for the physics beyond the Standard Model. In recent years, many dedicated detectors have been developed for such scenarios which are designed to extend the sensitivity to weakly coupled particles with macroscopic $c\tau$. In this work, we investigate th

Ruikai Li, Xinrun Li, Mengwei Xie, Hao Shan

Online High-Definition (HD) map construction is pivotal for autonomous driving. While recent approaches leverage historical temporal fusion to improve performance, we identify a critical safety flaw in this paradigm: it is inherently ``spatially backward-looking." These methods predominantly enhance map reconstruction in traversed areas, offering minimal imp

Jose Gustavo Buenaventura Carreon, Floris Erich, Roman Mykhailyshyn, Tomohiro Motoda

We present a cross robot visuomotor learning framework that integrates diffusion policy based control with 3D semantic scene representations from D3Fields to enable category level generalization in manipulation. Its modular design supports diverse robot camera configurations including UR5 arms with Microsoft Azure Kinect arrays and bimanual manipulators with

Haoran Yang, Yinan Zhang, Wenjie Zhang, Dongxia Wang

Nowadays, industrial hybrid modeling which integrates both mechanistic modeling and machine learning-based modeling techniques has attracted increasing interest from scholars due to its high accuracy, low computational cost, and satisfactory interpretability. Nevertheless, the existing industrial hybrid modeling methods still face two main limitations. First

I. Adachi, N. Akopov, D. Augueste, J. Bonis

We report on the design, operation, and performance of a novel proximity-focusing Ring Imaging Cherenkov (RICH) detector equipped with a multilayer focusing aerogel radiator, developed for the forward region of the Belle II spectrometer at the SuperKEKB $e^+e^-$ collider. The system achieves effective separation of charged pions, kaons, and protons across th

Hanya Pan, Astrid M. Veronig, Rui Liu

In the standard model, magnetic reconnection at a vertical current sheet above the flare arcade is key to explaining many aspects of solar eruptions. The supra-arcade region is where the vertical current sheet is supposedly located, and X-ray/EUV emission therein reflects underlying energy release and transport processes, therefore providing valuable insight

Rodrigue Desmorat, Anthony Gravouil, Boris Kolev

This article develops a unified variational framework for configurational (or material) forces in both Classical (3D, non-relativistic) and Relativistic (4D) Continuum Mechanics. Configurational forces describe the evolution of material defects-such as cracks, dislocations, and interfaces-which move relative to the material rather than through physical space

Francis Bach

We consider supervised learning problems in which set predictions provide explicit uncertainty estimates. Using Choquet integrals (a.k.a. Lov{\'a}sz extensions), we propose a convex loss function for nondecreasing subset-valued functions obtained as level sets of a real-valued function. This loss function allows optimal trade-offs between conditional probabi

Didier Henrion

We revisit Stengle's classical univariate polynomial optimization example $min 1 - x^2 s.t. (1 - x^2)^3 \geq 0$ whose constraint description is degenerate at the minimizers. We prove that the moment-SOS hierarchy of relaxation order $r \geq 3$ has the exact value $-1/r(r - 2)$. For this we construct in rational arithmetic a dual polynomial sum-of-squares (SO

Will Donovan, Luyu Zheng

The 3-fold cyclic quotient singularity denoted $\tfrac{1}{7}(1,2,4)$ admits a crepant resolution X with three exceptional Hirzebruch surfaces intersecting pairwise along curves. We show that the derived category D(X) carries a faithful action of a quiver braid group, where the relevant quiver is a 3-cycle encoding the intersection data.

Matteo Fael, Jack Jenkins, Enrico Lunghi, Zachary Polonsky

We present updated and comprehensive Standard Model predictions for the inclusive rare decay $B \to X_s \nu\bar{\nu}$. Using a state-of-the-art determination of the short-distance coefficient, including NLO QCD and electroweak effects, and implementing a consistent treatment of heavy-quark masses and power corrections within the kinetic scheme, we compute th