March 2026 arXiv papers — page 124

David Beck-Tiefenbach, Robin Kaiser

We consider the stochastic sandpile model with uniform toppling rule on the integer line. During a uniform toppling, with probability $1/3$ one particle is sent to the right of the toppled vertex, with probability $1/3$ one particle is sent to the left, and with probability $1/3$ two particles are sent out, one to the right and one to the left. We calculate

Jinghang Li, Shichao Li, Qing Lian, Peiliang Li

Recent visual autonomous perception systems achieve remarkable performances with deep representation learning. However, they fail in scenarios with challenging illumination.While event cameras can mitigate this problem, there is a lack of a large-scale dataset to develop event-enhanced deep visual perception models in autonomous driving scenes. To address th

Jinsheng Wei, Fengzhou Guo, Yante Li, Haoyu Chen

Micro-expression (ME) action units (Micro-AUs) provide objective clues for fine-grained genuine emotion analysis. Most existing Micro-AU detection methods learn AU features from the whole facial image/video, which conflicts with the inherent locality of AU, resulting in insufficient perception of AU regions. In fact, each AU independently corresponds to spec

Siting Zhu, Ziyun Lu, Guangming Wang, Chenguang Huang

Open-vocabulary scene understanding is crucial for robotic applications, enabling robots to comprehend complex 3D environmental contexts and supporting various downstream tasks such as navigation and manipulation. However, existing methods require pre-built complete 3D semantic maps to construct scene graphs for scene understanding, which limits their applic

Josep R. Fernández Rull, Liang Liu, Henrik Sjöland, Juan Vidal Alegría

Maintaining robust and stable communication links in high-mobility scenarios is challenging for time-division duplex (TDD) reciprocity-based gigantic MIMO systems due to rapid channel variations, especially in non-line-of-sight (NLOS) conditions. This paper proposes a user equipment (UE) beamforming strategy that enables reliable links in high mobility witho

Michael Gene Dobbins, Seunghun Lee

The transversal ratio of a polytope $P$ is the minimum proportion of vertices of $P$ required to intersect each facet of $P$. The weak chromatic number of $P$ is the minimum number of colors required to color the vertices of $P$ so that no facet is monochromatic. We will construct an infinite family of $d$-polytopes for each $d\geq 5$ whose transversal ratio

Jian Dong, Junming Zhao, Philippe Ben-Abdallah, Linhua Liu

Ballistic transport, realized when the system size is smaller than the mean free path of energy carriers, is traditionally regarded as the ultimate limit for energy transfer. Here, we predict a superballistic radiative heat transport regime that surpasses this limit in dilute chains of plasmonic nanoparticles confined within cavities. This anomalous regime e

Laurent Baratchart, Alexander Borichev, Sylvain Chevillard, Claire Coiffard Marre

We derive lower bounds in best rational approximation of given degree to finite Blaschke products, in the Hardy space $H^2$ of the unit disk. We first consider approximation to $z^N$, and then move on to more general Blaschke products whose zeros are bounded away from the circle. The latter case depends on Fourier coefficients estimates for Blaschke products

Madison Giacofci, Anouar Meynaoui, Alex Podgorny

We introduce a kernel-based two-sample test for comparing probability distributions up to group actions. Our construction yields invariant kernels for locally compact $\sigma$-compact groups and extends classical Haar-based approaches beyond the compact setting. The resulting invariant Maximum Mean Discrepancy (MMD) test is developed in a general framework w

Cecilia Borca, Javier Jiménez Peña, David Marckx, Malgorzata Niemiec

A 2021 study by the ECFA Early-Career Researchers Panel revealed that 71% of 334 respondents used open-source software tools in their instrumentation work, yet 70% reported receiving no training for these tools. In response, the Software and Machine Learning for Instrumentation group was formed in the ECFA Early-Career Researchers Panel to assess the accessi

Ke Yang, Bolin Chen, Yuejie Li, Yueying Hua

Spoken Question Answering (Spoken QA) presents a challenging cross-modal problem: effectively aligning acoustic queries with textual knowledge while avoiding the latency and error propagation inherent in cascaded ASR-based systems. In this paper, we introduce Attention-guided Evidence Grounding (AEG), a novel end-to-end framework that leverages the internal

Marco Artiano, Arpit Babbar, Michael Schlottke-Lakemper, Gregor Gassner

Jin-Xin relaxation is a method for approximating non-linear hyperbolic conservation laws by a linear system of hyperbolic equations with an $\varepsilon$ dependent stiff source term. The system formally relaxes to the original conservation law as $\varepsilon \to 0$. An asymptotic analysis of the Jin-Xin relaxation system shows that it can be seen as a conve

Zhengbo Zhang, Jinbo Su, Zhaowen Zhou, Changtao Miao

The rapid advancement of Multimodal Large Language Models (MLLMs) has enabled browsing agents to acquire and reason over multimodal information in the real world. But existing benchmarks suffer from two limitations: insufficient evaluation of visual reasoning ability and the neglect of native visual information of web pages in the reasoning chains. To addres

Dylan Sutterlin Guindon, Tor D Wager, Leonie Koban

Pain is strongly influenced by expectations and learning from previous experience, such as in classical conditioning. Conditioned responses and expectations can generalize to perceptually and conceptually related cues, but how generalization influences pain experience and the neurobiological processing of pain remains unclear. We used fMRI and multilevel med

Nicolas Moreno, Elnaz Zohravi, Shaghayegh Hamzehlou, Edgar Patino-Narino

Pressure-sensitive adhesives (PSAs) are soft polymeric materials that exhibit complex rheological and mechanical behavior gov- erned by the interplay between polymer architecture, crosslink density, and entanglement constraints. Predicting their rheological properties from underlying microstructure remains a central challenge in adhesive design. In this work

Yuan Tian, Yi Mei, Mengjie Zhang

The dynamic multi-mode resource-constrained project scheduling problem (DMRCPSP) is of practical importance, as it requires making real-time decisions under changing project states and resource availability. Genetic Programming (GP) has been shown to effectively evolve heuristic rules for such decision-making tasks; however, the evolutionary process typicall

Jinlu Zhang, Qiyun Wang, Baoxiang Du, Jiayi Ji

Character-centric story visualization aims to synthesize coherent image sequences that depict narrative events and interactions while preserving recurring character identities. In expanding story worlds, new user-specified characters must be continually incorporated despite varying customization difficulty and identity conflicts in multi-character scenes, wi

Elisabetta Rocchi, Mohab Safey El Din

Connected components of real algebraic sets are semi-algebraic, i.e. they are described by a boolean formula whose atoms are polynomial constraints with real coefficients. Computing such descriptions finds topical applications in optical system design and robotics. In this paper, we design a new algorithm for computing such semi-algebraic descriptions for re

Ömer Faruk Et, Esra Çekirdek, Rabia Aktaş Karaman

The aim of this paper is to study finite orthogonal polynomials on a cone of revolution and its surface. We define two classes of finite orthogonal polynomials on the solid cone and derive their corresponding differential equations and recurrence relations. Furthermore, we demonstrate that, in the limit case, one of these classes reduces to Laguerre polynomi

Saarang Panchavati, Uddhav Panchavati, Hiroki Nariai, Corey Arnold

Electroencephalography (EEG) is a widely used tool for studying brain function, with applications in clinical neuroscience, diagnosis, and brain-computer interfaces (BCIs). Recent EEG foundation models trained on large unlabeled corpora aim to learn transferable representations, but their effectiveness remains unclear; reported improvements over smaller task

Zihao Zheng, Wen Wu, Chao Zhang, Mengyue Wu

Current Text-to-Speech (TTS) systems typically use separate models for speech-prompted and text-prompted timbre control. While unifying both control signals into a single model is desirable, the challenge of cross-modal alignment often results in overly complex architectures and training objective. To address this challenge, we propose CAST-TTS, a simple yet

Timothée Gavin, Simon Lacroix, Murat Bronz

This article presents a solution to intercept an agile drone by another agile drone carrying a catching net. We formulate the interception as a Competitive Reinforcement Learning problem, where the interceptor and the target drone are controlled by separate policies trained with Proximal Policy Optimization (PPO). We introduce a high-fidelity simulation envi

Rina Veler, Sharon Gannot

We propose an interpretable Batch-EM Unfolded Network for robust speaker localization. By embedding the iterative EM procedure within an encoder-EM-decoder architecture, the method mitigates initialization sensitivity and improves convergence. Experiments show superior accuracy and robustness over the classical Batch-EM in reverberant conditions.

Chenglin Li, Hang Xu, Jianting Chen, Yanfei Zhang

Accurately, efficiently, and stably computing complex fluid flows and their evolution near solid boundaries over long horizons remains challenging. Conventional numerical solvers require fine grids and small time steps to resolve near-wall dynamics, resulting in high computational costs, while purely data-driven surrogate models accumulate rollout errors and

Alexander Kamenshchik, Alessio Marrani, Federica Muscolino

We describe Carroll particles with nonzero energy (i.e., particles that remain at rest) within the framework of two-time (2T) physics developed by Bars and collaborators. In a spacetime with one additional time and one additional space dimension, one can gauge the phase-space symmetry that exchanges generalized coordinates with their conjugate momenta, there

Zhaoyuan Qiu, Ken Chen, Xiangwei Wang, Yu Xia

Existing instruction-based image editing models perform well with simple, single-step instructions but degrade in realistic scenarios that involve multiple, lengthy, and interdependent directives. A main cause is the scarcity of training data with complex multi-instruction annotations. However, it is costly to collect such data and retrain these models. To a

Takao Inoué

This paper provides a preparatory introduction to sheaves and topoi, written as a conceptual continuation of the author's earlier introduction to torsors and as preparatory background for the author's arXiv paper \emph{Grothendieck Topologies and Sheaf-Theoretic Foundations of Cryptographic Security:\ Attacker Models and $\Sigma$-Protocols as the First Step}

Haijie Li, Ya Wang, Kai Yang, Gang Huang

Accurate reconstruction of global Sea surface temperature (SST), which dominates the air-sea coupling and global climate variability, underpins climate monitoring and prediction. Existing SST reconstruction products primarily provide one deterministic field derived from heterogeneous satellite data and in situ observations, limiting their ability to represen

Xiaohan Ren, Chenxiao Fan, Wenyin Ma, Hongliang He

Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-world clinical settings. However, clinical decision-making is inherently safety-critical, context-dependent, and conducted under evolving evidence. In such situations, reliable LLM performance depends not on factu

Liangbin Huang, Xiaohua Liao, Chaoqun Cui, Shijing Wang

Traditional speaker diarization systems have primarily focused on constrained scenarios such as meetings and interviews, where the number of speakers is limited and acoustic conditions are relatively clean. To explore open-world speaker diarization, we extend this task to the visual media domain, encompassing complex audiovisual programs such as films and TV

Kangxu Wang, Siang Chen, Chenxing Jiang, Shaojie Shen

Single-view RGB-D grasp detection remains a common choice in 6-DoF robotic grasping systems, which typically requires a depth sensor. While RGB-only 6-DoF grasp methods has been studied recently, their inaccurate geometric representation is not directly suitable for physically reliable robotic manipulation, thereby hindering reliable grasp generation. To add

Olayemi R. Oladokun, Taiwo O. Sangodapo

In this paper, we study the concept of complex fuzzy soft matrices. The application of complex fuzzy soft matrices in signals and systems via the cross product of complex fuzzy soft matrices and Fourier transform was carried out. In this application, an algorithm for the identification of a reference signal out of large interest signals detected by a digital

Jinsheng Wei, Zhaodi Xu, Guanming Lu, Haoyu Chen

Micro-gesture recognition (MGR) is challenging due to subtle inter-class variations. Existing methods rely on category-level supervision, which is insufficient for capturing subtle and localized motion differences. Thus, this paper proposes a Fine-Grained Semantic Guidance Learning (FG-SGL) framework that jointly integrates fine-grained and category-level se

Qionglei Chen, Zhen Li

Neither natural nor laboratory laminar flows are perfectly steady. Instead, they are frequently highly unsteady, as illustrated by experimental studies on B\'{e}nard convection. In the paper, we investigate the transition threshold of the Boussinesq equations around a time-dependent monotone shear flow $(U(t,y),0)$ with a constant background temperature $a\i

Hongju Li, Jian Ding, Fuyou Miao, Cheng Wang

Disjunctive Hierarchical Secret Sharing (DHSS)} scheme is a type of secret sharing scheme in which the set of all participants is partitioned into disjoint subsets, and each subset is said to be a level with different degrees of trust and different thresholds. In this work, we focus on the Chinese Remainder Theorem (CRT)-based DHSS schemes due to their abili

Qu-Zhi Li, Chuan Liu, Liuming Liu, Peng Sun

We present a lattice QCD study of the $K^*(892)$ resonance using eight $N_f=2+1$ Wilson-Clover ensembles with three lattice spacings and six pion masses ranging from 135 to 320 MeV. For each ensemble, a large number of finite volume energy levels in the $P$-wave $K\pi$ channel are determined. The energy dependence of the scattering phase shift is then obtain

Mikkel Bengtson Albrechtsen, Jacopo Mauro, Torben Worm

In this paper, we present CTF Pilot, a GitOps-based framework for the deployment and management of Capture The Flag (CTF) competitions. By leveraging Git repositories as the single source of truth for challenge definitions and infrastructure configurations, CTF Pilot enables automated, version-controlled deployments that enhance collaboration among challenge

Chunjiang Mu, Ya Zeng, Qiaosheng Zhang, Kun Shao

Theory of Mind (ToM) refers to the ability to reason about others' mental states, and higher-order ToM involves considering that others also possess their own ToM. Equipping large language model (LLM)-driven agents with ToM has long been considered to improve their coordination in multiagent collaborative tasks. However, we find that misaligned ToM orders-mi

Niklas Roßberg, Sinan Hasirlioglu, Mohamed Essayed Bouzouraa, Wolfgang Utschick

Approval of ADS depends on evaluating its behavior within representative real-world traffic scenarios. A common way to obtain such scenarios is to extract them from real-world data recordings. These can then be grouped and serve as basis on which the ADS is subsequently tested. This poses two central challenges: how scenarios are extracted and how they are g

Keita Tanaka, Megan Eckart, Kotaro Fukushima, Liyi Gu

We report evidence for the resonant scattering effect at the center of the galaxy cluster PKS 0745-191 with XRISM. We analyzed XRISM/Resolve commissioning-phase observations of the distant cluster PKS 0745-191 (z = 0.103) with a 54 ks exposure. The gain drift was corrected using the onboard modulated X-ray source (MXS), and spectra were extracted from all pi

Hongwei Lin, Xun Huang, Chenglu Wen, Cheng Wang

Robust 3D object detection under adverse weather conditions is crucial for autonomous driving. However, most existing methods simply combine all weather samples for training while overlooking data distribution discrepancies across different weather scenarios, leading to performance conflicts. To address this issue, we introduce AW-MoE, the framework that inn

Anna De Liddo, Lucas Anastasiou, Simon Buckingham Shum

This chapter introduces the concept of Collective Intelligence for Deliberative Democracy (CI4DD). We propose that the use of computational tools, specifically artificial intelligence to advance deliberative democracy, is an instantiation of a broader class of human-computer system designed to augment collective intelligence. Further, we argue for a fundamen

Baohang Zhou, Kehui Song, Rize Jin, Yu Zhao

Multimodal information extraction (MIE) constitutes a set of essential tasks aimed at extracting structural information from Web texts with integrating images, to facilitate the structural construction of Web-based semantic knowledge. To address the expanding category set including newly emerging entity types or relations on websites, prior research proposed

Martina Simonotti, Ludovica Pannitto, Eleonora Zucchini, Silvia Ballarè

This paper analyses the implementation of Automatic Speech Recognition (ASR) into the transcription workflow of the KIParla corpus, a resource of spoken Italian. Through a two-phase experiment, 11 expert and novice transcribers produced both manual and ASR-assisted transcriptions of identical audio segments across three different types of conversation, which

Weihua Gao, Wenlong Niu, Jie Tang, Man Yang

Infrared small target detection (IRSTD) methods predominantly formulate the task as pixel-level segmentation, which requires costly dense annotations and is not well suited to tiny targets with weak texture and ambiguous boundaries. To address this issue, we propose Point-to-Mask, a framework that bridges low-cost point supervision and mask-level detection t

Xiaokun Sun, Yubo Wang, Haoyu Cao, Linli Xu

Recently, Multimodal Large Language Models (MLLMs) have demonstrated significant potential in complex visual tasks through the integration of Chain-of-Thought (CoT) reasoning. However, in Video Question Answering, extended thinking processes do not consistently yield performance gains and may even lead to degradation due to ``visual anchor drifting'', where

Yan Xie, Tiansheng Wen, Tangda Huang, Bo Chen

Scaling Transformers to ultra-long contexts is bottlenecked by the $O(n^2 d)$ cost of self-attention. Existing methods reduce this cost along the sequence axis through local windows, kernel approximations, or token-level sparsity, but these approaches consistently degrade accuracy. In this paper, we instead explore an orthogonal axis: feature sparsity. We pr

Haoqing Wen, Michele D'Amico, Matteo Oldoni, Federica Fieramosca

Model training for Device-Free Localization (DFL) and Radio-Frequency (RF) sensing heavily relies on large-scale datasets, which are difficult, expensive, and time-consuming to obtain through measurements. This paper proposes a fast 2.5-dimensional Finite Element Method (2.5-D FEM) for computing the scattering fields of a Body of Revolution (BoR) human model

Nadia Ott

We apply the supergeometric analogue of Artin's algebraicity criteria to prove algebraicity for four moduli problems in supergeometry: supercurves, super Riemann surfaces, stable supercurves, and stable super Riemann surfaces. The algebraicity of the moduli of (stable) super Riemann surfaces is known but we give a new proof by verifying the super Artin condi

Junxin Wang, Dai Guan, Weijie Qiu, Zhihang Li

Vision-language process reward models (VL-PRMs) are increasingly used to score intermediate reasoning steps and rerank candidates under test-time scaling. However, they often function as black-box judges: a low step score may reflect a genuine reasoning mistake or simply the verifier's misperception of the image. This entanglement between perception and reas

Youming Chen, Wenchuan Hu

Let $C_{p,d}(\mathbb{P}^n)$ denote the Chow variety of effective algebraic $p$-cycles of degree $d$ in complex projective space $\mathbb{P}^n$. In this paper, we compute the rational Lawson homology groups $L_qH_k(C_{p,d}(\mathbb{P}^n))_\mathbb{Q}$ for $0 \leq 2q\leq k \leq 2d$. Additionally, we prove that the rational Lawson homology groups of a natural com

Zhi Zeng, Chong Han, Emil Björnson

Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) promises ultra-high throughput, while its highly directional beams demand rapid and accurate beam tracking driven by precise user-state estimation. Moreover, large array apertures at high frequencies induce near-field propagation effects, where far-field modeling becomes inaccurate and ne

Zvi N. Badash, Yonatan Belinkov, Moti Freiman

Large language models (LLMs) are often confidently wrong, making reliable uncertainty estimation (UE) essential. Output-based heuristics are cheap but brittle, while probing internal representations is effective yet high-dimensional and hard to transfer. We propose a compact, per-instance UE method that scores cross-layer agreement patterns in internal repre

Duc T. Nguyen, Hoang-Long Nguyen, Huy-Hieu Pham

Automated white blood cell (WBC) classification is essential for leukemia screening but remains challenged by extreme class imbalance, long-tail distributions, and domain shift, leading deep models to overfit dominant classes and fail on rare subtypes. We propose a hybrid framework for rare-class generalization that integrates a generative Pix2Pix-based rest

Linda Blot, Théo Gayoux, Fabian Schmidt, Pier Stefano Corasaniti

We present the first cosmological simulations that consistently include nonlinear clustering dark energy evolved as a fluid with the numerical hydrodynamics code Nefertiti. Dark energy perturbations become fully nonlinear on small scales, developing significant density fluctuations without exhibiting the catastrophic instabilities previously reported. We sho

Johannes Gradl, Niklas Hofmann, Leonard Weigl, Stiven Forti

Understanding how defects influence charge separation in WS$_2$-graphene heterostructures is crucial for future applications in light harvesting and detection. Previous studies have reported widely varying lifetimes for the charge-separated state, all supposedly linked to electron trapping at sulphur vacancies. The exact impact of these defects, however, has

Jingyu Liu, Shirong Lin

Cavity optomechanics has enabled slow-to-fast light conversion, but traditional optomechanic systems suffer from limited tunability due to fixed mechanical frequencies. To address this constraint, we introduce a magnon degree of freedom into an optomechanical system, constructing a system that integrates photons, phonons, and magnons. We establish the theore

Jiancheng Dong, Pengyue Jia, Derong Xu, Jiawei Cheng

LLMs typically linearize 2D tables into 1D sequences to fit their autoregressive architecture, which weakens row-column adjacency and other layout cues. In contrast, purely visual encoders can capture spatial cues, yet often struggle to preserve exact cell text. Our analysis reveals that these two modalities provide highly distinct information to LLMs and ex

Song Tae-Eun

Cross-Context Review (CCR) improves LLM verification by separating production and review into independent sessions. A natural extension is multi-turn review: letting the reviewer ask follow-up questions, receive author responses, and review again. We call this Dynamic Cross-Context Review (D-CCR). In a controlled experiment with 30 artifacts and 150 injected

Zeqiang Wei, Kai Jin, Kuan Song, Xiuzhuang Zhou

Current SSM-based light field super-resolution (LFSR) methods often fail to fully leverage the complementarity among various LF representations, leading to the loss of fine textures and geometric misalignments across views. To address these issues, we propose RASLF, a representation-aware state-space framework that explicitly models structural correlations a

Yao Liang, Xin Weng, Tingting Sun

This study provides a comprehensive strategic analysis of infrastructure energy investment in the context of the global low-carbon transition. Integrating quantitative panel data analysis across 15 countries (2010-2023), detailed case studies of Germany, the United States, China, and the European Union, and scenario simulations through 2050, we examine how p

Jiyang Huang, Hongru Chen, Wei Lin, Jia Wan

Semi-supervised crowd analysis is a prominent area of research, as unlabeled data are typically abundant and inexpensive to obtain. However, traditional point-based annotations constrain performance because individual regions are inherently ambiguous, and consequently, learning fine-grained structural semantics from sparse anno tations remains an unresolved

Charbel Abi Hana, Kameel Amareen, Mohamad Mostafa, Dmitry Slepichev

This work presents a comprehensive benchmark evaluation of visual odometry (VO) and visual SLAM (VSLAM) systems for mobile robot navigation in real-world logistical environments. We compare multiple visual odometry approaches across controlled trajectories covering translational, rotational, and mixed motion patterns, as well as a large-scale production faci

Andrew Qing He, Wei Cai

In this paper, we extend the Weak Adversarial Neural Pushforward Method to the Fokker--Planck equation on compact embedded Riemannian manifolds. The method represents the solution as a probability distribution via a neural pushforward map that is constrained to the manifold by a retraction layer, enforcing manifold membership and probability conservation by

Ryutaro Miya, Kazuyoshi Fushinobu, Tatsuya Kawaguchi

We propose PureCLIP-Depth, a completely prompt-free, decoder-free Monocular Depth Estimation (MDE) model that operates entirely within the Contrastive Language-Image Pre-training (CLIP) embedding space. Unlike recent models that rely heavily on geometric features, we explore a novel approach to MDE driven by conceptual information, performing computations di

Jonathan Washburn, Milan Zlatanović, Elshad Allahyarov

We study functions satisfying the composition law $F(xy)+F(x/y)=P(F(x),F(y))$ with a symmetric polynomial combiner $P$. We prove that symmetry together with a quadratic degree bound on $P$ forces a composition law of d'Alembert type. We establish a degree mismatch exclusion criterion showing that symmetric polynomial combiners with $\mbox{deg} P(u,v) \ge 3$

Moonsoo Park, Seulbeen Je, Donghyeon Park

In recommender systems, large language models (LLMs) have gained popularity for generating descriptive summarization to improve recommendation robustness, along with Graph Convolution Networks. However, existing LLM-enhanced recommendation studies mainly rely on the internal knowledge of LLMs about item titles while neglecting the importance of various facto

E. Strizhevsky, Y. Klein, R. Hartmann, S. Francoual

We directly observe far-field correlations of x-ray photon pairs generated by spontaneous parametric down-conversion (SPDC). Using an energy-resolved, two-dimensional photon counting detector we record the full ring-shaped emission of both photons across a broad bandwidth and extract pair correlations directly from raw events without imposing angular constra

Ke Wang, Qiang Zhang

For a surface group $\pi_1(\Sigma_g)=\langle c_1,\dots , c_{2g}\mid c_1\cdots c_{2g}c_1^{-1}\cdots c_{2g}^{-1}\rangle$ with genus $g\geq 2$, we provide an explicit bound $n-1\leq \mathrm{CL}(2n)=\mathrm{CL}(2n+1)\leq n+8g-1$ for the conjugator length function $\mathrm{CL}:\mathbb N\to\mathbb N$ of $\pi_1(\Sigma_g)$ via a detailed analysis of conjugation redu

Ryosuke Hori, Jyun-Ting Song, Zhengyi Luo, Jinkun Cao

We propose Ground Reaction Inertial Poser (GRIP), a method that reconstructs physically plausible human motion using four wearable devices. Unlike conventional IMU-only approaches, GRIP combines IMU signals with foot pressure data to capture both body dynamics and ground interactions. Furthermore, rather than relying solely on kinematic estimation, GRIP uses

Mudasar Bashir, Andrew Sanchez, Pranaba Muduli, Artur Useinov

This work presents a unified theoretical framework for spin-resolved electron transport in magnetic point contacts (PCs) in nanoscale dimensions. This work advances existing research by presenting a model which seamlessly transitions between Sharvin ballistic and Maxwell-Holm diffusive limits across the wide range of relevant contact sizes without incorporat

Qi Wei, Jianfeng Tao, Haoyang Tan, Hongyu Nie

Numerical optimal control has long been split between globally structured but dimensionally intractable Hamilton--Jacobi--Bellman (HJB) methods and scalable but local trajectory optimization. We introduce Featurized Occupation Measures (FOM), a finite-dimensional primal--dual interface for coupling numerical optimal control solvers with explicit HJB subsolut

Heng-Tong Ding

I review recent lattice results on strongly interacting matter under extreme conditions, with emphasis on the finite-temperature QCD transition at $\mu_B=0$, its approach toward the chiral limit and the fate of the $U_A(1)$ anomaly, as well as recent constraints on the QCD phase boundary and the possible critical endpoint at $\mu_B>0$. I also discuss selecte

Md. Naeemur Rahman, Md. Alamin Hossain Pappu, Md. Islahur Rahman Ebon, Abdul Kuddus

A systematic survey and subsequent research have been made on MoTe2-based n-CdS/p-MoTe2/p+-CGS device in solar cell and photodetector field. The optimization has been established by altering the various properties of each constituent layer through numerical computation. The performance of the MoTe2 photonic device has been probed with and without CGS back su

Ryuji Hashimoto, Masahiro Kaneko, Ryosuke Takata, Takehiro Takayanagi

Opinion dynamics (OD) studies how individual opinions evolve and generate collective patterns such as consensus and polarization. While recent work explores OD using populations of LLM-based agents focusing on opinion exchange, it typically does not incorporate individuals' lived experiences, such as economic outcomes of past decisions, which play a critical

Hailiang Tang, Tisheng Zhang, Liqiang Wang, Xin Ding

Real-time LiDAR-visual-inertial odometry and mapping is crucial for navigation and planning tasks in intelligent transportation systems. This study presents a pose-only bundle adjustment (PA) LiDAR-visual-inertial odometry (LVIO), named PA-LVIO, to meet the urgent need for real-time navigation and mapping. The proposed PA framework for LiDAR and visual measu

Qiwei Feng

In this paper, we first consider linear 2D and 3D convection-diffusion-reaction equations $-\nabla\cdot (\kappa \nabla u) + {\bm v} \cdot \nabla u + \lambda u = \phi$ and $u_t - \nabla\cdot (\kappa \nabla u) + {\bm v} \cdot \nabla u + \lambda u = \phi$, where all $\kappa>0, {\bm v}, \lambda, \phi$ are smooth variable functions. We derive fourth-order compact

Kiarn T. Laverick, Samyak P. Prasad, Pascale Senellart, Maria Maffei

We analyze qubit-qubit entanglement from an energetic perspective and reveal an energetic trade-off between quantum coherence and entanglement. We decompose each qubit internal energy into a coherent and an incoherent component. The qubits' coherent energies are maximal if the qubit-qubit state is pure and separable. They decrease as qubit-qubit entanglement

Nathan Abitbol, Alex Hansen, Alberto Rosso, Laurent Talon

We study the flow of a Bingham yield-stress fluid in a pore network model where the throats have radii drawn from a uniform distribution. We consider the case in which a fraction of the largest radii is blocked. The fluid can flow only through the percolating cluster that exists when the fraction is above the percolation threshold. Two distinct flow regimes

Nils Lid Hjort

The Olympic 500 meter sprint competition is the `Formula One event' of speed skating, and is watched by millions of television viewers. A draw decides who should start in inner lane and who in outer lane. Many skaters dread the last inner lane, where they need to tackle heavier centrifugal forces than their companions in the last outer lane, at maximum speed

Yesung Cho, Dongmyung Shin, Sujeong Hong, Jooyeon Lee

Prostate cancer is one of the most frequently diagnosed malignancies in men worldwide. However, precise prediction of biochemical recurrence (BCR) after radical prostatectomy remains challenging due to the multifocality of tumors distributed throughout the prostate gland. In this paper, we propose a novel AI framework that simultaneously processes a series o

Kaixuan Du, Meng Cao, Hang Zhang, Yukun Wang

Current label-free RLVR approaches for large language models (LLMs), such as TTRL and Self-reward, have demonstrated effectiveness in improving the performance of LLMs on complex reasoning tasks. However, these methods rely heavily on accurate pseudo-label estimation and converge on spurious yet popular answers, thereby trapping in a dominant mode and limiti

Jun-Xiao Hui, T. H. Hansson, Egor Babaev

A key property of topologically ordered systems, such as Quantum Hall states, is the existence of excitations obeying fractional quantum statistics - anyons. We develop a theory for multicomponent counterflow states where an ordinary Laughlin quasiparticle can split into fractional vortices carrying fractions of its charge and statistical angle. There are tw

Advika Rajapakse

Lipshitz-Sarkar defined a stable homotopy type refining Khovanov homology, producing cohomology operations $\text{Sq}^i$ on the Khovanov homology $Kh(L)$ of a link $L$. Later, Mor\'an proposed a sequence of cup-i products on the $\mathbb{F}_2$-coefficient cochain complex of any augmented semi-simplicial object in the Burnside category. Applied to the Khovano

Jian Zhou, Junbo Pang, Hong Shen, Jinniu Hu

We investigate nuclear pasta phases appearing in hot neutron-star matter based on the compressible liquid-drop model, where the matter consists of a dense liquid phase and a dilute gas phase separated by a sharp interface. The surface tension is calculated self-consistently from the Thomas-Fermi approximation, and it depends on temperature and isospin asymme

Hang Lv, Sheng Liang, Hao Wang, Yongyue Zhang

Realizing personalized intelligence faces a core dilemma: sending user history to centralized large language models raises privacy concerns, while on-device small language models lack the reasoning capacity required for high-quality generation. Our pilot study shows that purely local enhancements remain insufficient to reliably bridge this gap. We therefore

Johannes Hechtl, Philipp Schmitt, Georg von Wichert, Wolfram Burgard

While vision-language-action (VLA) models have shown great promise for robot manipulation, their deployment on rigid industrial robots remains challenging due to the inherent trade-off between compliance and responsiveness. Standard Behavior Cloning (BC) approaches predict discrete poses at low frequencies, omitting the velocity and acceleration feedforward

Yomali Lokugama, Charith Dissanayake, Saman Atapattu, Kandeepan Sithamparanathan

This paper investigates energy-efficient inter-satellite communication in Low Earth Orbit (LEO) networks, where satellites exchange both buffered and newly generated data through half-duplex inter-satellite links (ISLs). Due to orbital motion and interference-prone directional asymmetry, the achievable ISL capacities in opposite directions vary dynamically,

Juhani Merilehto

We review thirteen generative systems and five supporting datasets for quantum circuit and quantum code generation, identified through a structured scoping review of Hugging Face, arXiv, and provenance tracing (January-February 2026). We organize the field along two axes: artifact type (Qiskit code, OpenQASM programs, circuit graphs); crossed with training r

Gengxin Sun, Ruihao Yu, Liangyi Yin, Yunqi Yang

Ensuring robust and fair interview assessment remains a key challenge in AI-driven evaluation. This paper presents CoMAI, a general-purpose multi-agent interview framework designed for diverse assessment scenarios. In contrast to monolithic single-agent systems based on large language models (LLMs), CoMAI employs a modular task-decomposition architecture coo

Gengzhi Yang, Jiaqi Leng, Xiaodi Wu, Lin Lin

Non-Hermitian many-body systems can be spectrally unstable, so small perturbations may induce large eigenvalue shifts. The pseudospectrum quantifies this instability and provides a perturbation-robust diagnostic. For inverse-polynomially small $\epsilon$, we show that deciding whether a point $z\in\mathbb{C}$ is $\epsilon$-close to the spectrum is PSPACE-har

Stan Koobs, Nick W. Koning

Equivalence testing compares the hypothesis that an effect $\mu$ is large against the alternative that it is negligible. Here, `large' is classically expressed as being larger than some `equivalence margin' $\Delta$. A longstanding problem is that this margin must be specified but can rarely be objectively justified in practice. We lay the foundation for an

Nikolaos D. Tantaroudas, Ilias Karachalios

Identification of worst-case gust loads is a critical step in the certification of very flexible aircraft, yet the computational cost of nonlinear full-order simulations renders exhaustive parametric searches impractical. This paper presents a reduced-order model (ROM) based methodology for rapid worstcase gust identification that achieves computational spee

Yiming Huang, Baixiang Huang, Beilei Cui, Chi Kit Ng

Feed-forward 3D reconstruction has revolutionized 3D vision, providing a powerful baseline for downstream tasks such as novel-view synthesis with 3D Gaussian Splatting. Previous works explore fixing the corrupted rendering results with a diffusion model. However, they lack geometric concern and fail at filling the missing area on the extrapolated view. In th

Jingyu Peng, Hongyu Chen, Jiancheng Dong, Maolin Wang

Safety alignment in large language models (LLMs) is commonly implemented as a single static policy embedded in model parameters. However, real-world deployments often require context-dependent safety rules that vary across users, regions, and applications. Existing approaches struggle to provide such conditional control: parameter-level alignment entangles s

Ziyuan Xie, Weipeng Xu, Dazhi Zhao, Wenchang Zhang

Disordered metamaterials are promising for programming physical properties across diverse applications, yet their inverse design remains challenging due to the non-intuitive structure-property relationships and large design spaces. Recent generative approaches, particularly diffusion models, have shown potential in high-dimensional inverse design tasks. Howe

Zhifei Chen, Lata Yi, Liming Nie, Yangyang Zhao

Software development relies heavily on traceability links between various software artifacts to ensure quality and facilitate maintenance. While automated traceability recovery techniques have advanced for different artifact pairs, the field remains fragmented with an incomplete overview of artifact associations, ambiguous linking techniques, and fragmented

Xinxin Jin, Zhengwei Ni, Zhengguo Sheng, Victor C. M. Leung

As Large Language Models (LLMs) transition from information providers to embodied agents in the Internet of Things (IoT), they face significant challenges regarding reliability and interaction efficiency. Direct execution of LLM-generated commands often leads to entity hallucinations (e.g., trying to control non-existent devices). Meanwhile, existing iterati

Yongyu Mu, Jiali Zeng, Fandong Meng, JingBo Zhu

Through encouraging self-exploration, reinforcement learning from verifiable rewards (RLVR) has significantly advanced the mathematical reasoning capabilities of large language models. As the starting point for RLVR, the capacity of supervised fine-tuning (SFT) to memorize new chain-of-thought trajectories provides a crucial initialization that shapes the su

Samuel Monter, Lars T. Stutzer, Sarah A. M. Loos, Clemens Bechinger

We experimentally and theoretically study the thermodynamically optimal control of interacting multiple-particle systems, focusing on collections of colloidal particles individually confined in optical traps. We investigate protocols that transport the system between prescribed trap configurations within a fixed time in the most energy efficient way. For Mar