April 2026 arXiv papers — page 7

Adam Barber

We construct a Lagrangian Floer homology whose chain complex is generically generated by the inscriptions of isosceles trapezoids in a smooth Jordan curve. This is an extension of Greene and Lobb's Jordan Floer homology (arXiv:2404.05179), which we also call Jordan Floer homology. Its non-triviality re-establishes that every smooth Jordan curve inscribes eve

Aadarsh Singh, G. D'Ambrosio, Sudhir K. Vempati

We study the dimension-six SMEFT four-lepton operators in the $\mu$--$\tau$ sector. These operators control both charged-lepton scattering and neutrino self-interactions, the latter being weakly constrained by direct laboratory probes despite their importance for cosmological tensions. We compare three classes of constraints on the Warsaw-basis coefficients

Hyeonseo Jang, Jaebyeong Jeon, Joong-Won Hwang, Kibok Lee

Test-time prompt tuning (TPT) has emerged as a promising technique for enhancing the adaptability of vision-language models by optimizing textual prompts using unlabeled test data. However, prior studies have observed that TPT often produces poorly calibrated models, raising concerns about the reliability of their predictions. Recent works address this issue

Christopher Holder, Anthony Bagnall

Elastic distances like dynamic time warping (DTW) are central to time series machine learning because they compare sequences under local temporal misalignment. Soft-DTW is an adaptation of DTW that can be used as a gradient-based loss by replacing the hard minimum in its dynamic-programming recursion with a smooth relaxation. However, this approach does not

Maofei Chen, Laifu Wang, Yue Qin, Yuan Wang

How code representation format shapes false positive behaviour in cross-language LLM vulnerability detection remains poorly understood. We systematically vary training intensity and code representation format, comparing raw source text with pruned Abstract Syntax Trees at both training time and inference time, across two 8B-parameter LLMs (Qwen3-8B and Llama

Wilder Baldwin, Sepideh Ghanavati

The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe and secure AI have been proposed. In this paper, we present an agentic framework that constructs knowledge graphs (KGs) from AI policy documents and retrieves policy-relevant information to answer questions.

Nhi Ngoc-Yen Nguyen, Anh-Duc Nguyen, Nghia Hieu Nguyen, Kiet Van Nguyen

Scene-text image captioning requires fusing three information streams -- visual features, OCR-detected text, and linguistic knowledge -- to generate descriptions that faithfully integrate text visible in images. Existing fusion approaches treat text as language-agnostic, which fails for Vietnamese: a tonal language where diacritics alter word meaning, OCR er

Yanghao Zhou, Jingyu Ma, Yibo Peng, Zhenguo Sun

Humanoid control systems have made significant progress in recent years, yet modeling fluent interaction-rich behavior between a robot, its surrounding environment, and task-relevant objects remains a fundamental challenge. This difficulty arises from the need to jointly capture spatial context, temporal dynamics, robot actions, and task intent at scale, whi

Ali Najafi, Letizia Iannucci, Mikko Kivelä, Onur Varol

The rapid diversification of social media platforms and the increasing restrictions on official APIs have significantly complicated cross-platform analysis. Researchers are often forced to rely on heterogeneous datasets obtained through web scraping and historical archives; however they often lack structural consistency. Prior to conducting cross-platform so

Jamie Swain, Cyprien Bone, Matthew T. Darby, Ewan Galloway

MAX phases (M$_{n+1}$AX$_n$), precursors to MXenes, span a vast compositional space, motivating efficient computational screening for synthesisable candidates. We employ CrystaLLM$-\pi$, a large language model fine-tuned on 6,179 double transition-metal MAX phases, and demonstrate its ability to generate out-of-sample structures consistent with known experim

Abidemi Kuburat Adedeji, Franklin Tchakounte, Sulaiman Oluwasegun Yusuff

Artificial intelligence (AI) is now embedded in educational, civic, and economic systems worldwide. For African primary and secondary education, this creates a double imperative: to prepare a young population (over sixty per cent of Africans are under twenty-five) for AI-mediated labour markets without uncritically importing curricula designed for other ling

Maykel Marquez-Mijares, German Rojas-Lorenzo, Jesus Rubayo-Soneira, Thu Nhi Tran Caliste

In this study, we present a comprehensive quantitative analysis of the radiation emitted by 855 MeV electrons propagating through an oriented diamond hetero-crystal. The crystal consists of two distinct segments: (i) a straight single-crystal diamond substrate, and (ii) a diamond layer that is periodically doped with boron atoms. The doping profiles were der

Alexandre Anahory Simoes, Leonardo Colombo

This paper considers the robust control of a catenary robot composed of two quadrotors connected by an inextensible cable. The system is modeled on \(SE(3)\), with the cable treated as a geometric subsystem induced by the UAV configuration rather than as an independent dynamical element. The catenary shape determines configuration-dependent forces that coupl

Yuan Fang, Yuanzhi Cai, Jagannath Aryal, Qinfeng Zhu

In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tuned on domain-specific datasets. However, the performance of these fine-tuned models is often hindered by the large domain gaps (i.e., differences in scenes and modalities) between ImageNet's images and remotel

Zhijun Li, Zhengyun You

The dark photon plays an important role as a portal to dark matter and has been extensively studied on both experimental and theoretical frontiers. However, as no signals have been observed, the whereabouts of the dark photon remain a long-standing open question. With the proposal of a future $\tau-c$ facility, this proceeding reviews and summarizes the curr

Yubo Dong, Danhua Liu, Anqi Li, Zhenyuan Lin

Video snapshot compressive imaging (SCI) enables the reconstruction of dynamic scenes from a single snapshot measurement. Recently, NeRF-based methods have shown promising reconstruction performance. However, such methods typically adopt random ray sampling strategies and fail to capture content structural similarities, resulting in limited reconstruction qu

Bimal Kumar Ray

This paper proposes an algorithm for clipping line segment against an axis-aligned rectangular window. The conventional algorithms for line segment clipping treat the clipping boundary and/or the line segment to be clipped as line. The present algorithm treats the clipping boundary and the line segment to be clipped as line segment and using this strategy, i

Chiheb Ben Hammouda, Michael Samet, Raúl Tempone

The rapid growth of weather-dependent renewable generation increases price volatility and imbalance penalty risk in power markets, creating the need for advanced quantitative trading strategies. We develop a data-driven continuous-time stochastic optimal control framework for intraday electricity trading using stochastic differential equations with drift ter

Chunhui Zhang, Yuxuan Wang, Aoyang Qin, Yi-Long Lu

Current embodied agents are often limited to passive instruction-following or reactive need-satisfaction, lacking a stable, high-order value framework essential for long-term, self-directed behavior and resolving motivational conflicts. We introduce \textit{ValuePlanner}, a hierarchical cognitive architecture that decouples high-level value scheduling from l

Debika Banerjee, Atul Dixit, Rajat Gupta

Let $k\in\mathbb{N}$. Wigert's divisor function $d^{\left(\frac{1}{k}\right)}(j)$ counts the number of representations of $j$ of the form $m^k+mn$ with $m\geq1 , n\geq0$. Let $\mathcal{F}_k(s)$ denote the Dirichlet series of $d^{\left(\frac{1}{k}\right)}(j)$. While $\mathcal{F}_2(s)$ is essentially a well-known special case of the Euler-Zagier double zeta fu

Pieter C. Gort, Lotte J. S. Ewals, Marion W. Tops-Welten, Cris H. B. Claessens

Peritoneal metastases are currently assessed using diagnostic laparoscopy to determine Sugarbaker's Peritoneal Cancer Index (sPCI), which works by dividing the abdomen into 13 regions and scoring each region based on tumor size. A recent consensus study defined 3D regions to facilitate a radiological PCI (rPCI), providing standardized anatomical regions for

Yuyang Li, Yime He, Zeyu Zhang, Dong Gong

Long-term conversational memory requires retrieving evidence scattered across multiple sessions, yet single-pass retrieval fails on temporal and multi-hop questions. Existing iterative methods refine queries via generated content or document-level signals, but none explicitly diagnoses the evidence gap, namely what is missing from the accumulated retrieval s

Kai Gao, Yu Sun, Chang-ai Sun

Template engines are indispensable components in modern software ecosystems, enabling the generation of structured documents and scripts across domains such as web development, Infrastructure as Code, and data engineering. However, the unique architectural characteristics of template engine-based applications (i.e., TE applications), including multi-language

Chao Fei, Hongcheng Guo, Yanghua Xiao

Across millennia, complex societies have faced the same coordination problem of how to organize collective action among cognitively bounded and informationally incomplete individuals. Different civilizations developed different political institutions to answer the same basic questions of who proposes, who reviews, who executes, and how errors are corrected.

Hirotaka Yoneda, Masataka Yoneda

We study the problem of online coloring for graphs with large odd girth. The best previously known algorithm uses $O(n^{1/2})$ colors, which was discovered by Kierstead in 1998. This algorithm works when the odd girth is 7 or more. In this paper, we provide the following: for every $\varepsilon > 0$, there exists a constant $g' \in \{3, 5, 7, \dots\}$ such t

Hongzhi Zhu, Wei Xu, Xiaohu You

This paper proposes a bitwise over-parameterized neural network (ONN) decoder for polar-coded transmission and develops a tractable theoretical performance analysis framework. By modeling each synthesized message channel as an individual supervised regression task, the proposed decoder preserves the successive structure of polar decoding while enabling a com

F. Laytimi, D. S. Nagaraj

On the flag variety $ \mathcal{F}l_s(E)$ associated to a vector bundle $E,$ , a sequence $s$ and a partition $a,$ there is a line bundle $\it Q^a_s$ on $ \mathcal{F}l_s(E).$ The aim of this paper is to prove the following conjecture: $Q^a_s $ on $ \mathcal{F}l_s(E)$ is big if only if $\pi_*(Q^a_s)=S_a(E)$ on X is big. The "if" part is proven here, the "only

Michele Pellegrino, Parvathy K. Kannan, Gustav Amberg, Shervin Bagheri

Incorporating molecular-scale effects in the description of contact line motion is essential for accurately capturing all sources of energy dissipation in wetting dynamics. This holds particularly true in the cases where contact line friction dominates, and hydrodynamics models struggle to achieve regularisation due to the negligible Navier slip. We perform

Kairui Zhou, Shengkai Lin, Wei Zhang, Shizhen Zhao

Layer-7 (L7) proxies are critical to modern cloud-native systems, yet their performance is increasingly bottlenecked by copying entire payloads across the kernel-user boundary. Existing approaches reduce this overhead but typically sacrifice compatibility with unmodified POSIX applications, introduce new APIs, or require specialized environments. We show tha

Rogério Almeida Gouvêa, Gian-Marco Rignanese

While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them are required. We introduce VibroML, an open-source Python toolkit driven by foundational MLIPs that shifts the paradigm from stabi

Arsène Ferrière

In recent years, radio detection of ultra-high-energy cosmic rays (UHECRs), with energies above $10^{18}$ eV, has become an established technique. The radio emissions can be simulated with high accuracy using Monte Carlo codes such as ZHAireS and CoREAS. These simulations are essential but are computationally intensive. In this work, we present a machine-lea

Sucharita Biswas

Partially ordered patterns (POPs) generalize classical permutation patterns and have been extensively studied in the contexts of permutations, words, compositions, and partitions. Burstein, Han, Kitaev, and Zhang established the shape-Wilf-equivalence for individual claw-shaped POPs. In this paper, we extend their result by proving that certain families of c

Fabian Mies, Duuk Sikkens

The fractional stable motion is a prototypical stochastic process exhibiting both heavy tails and long-range dependence, parameterized via a stability index $\alpha$ and a Hurst exponent $H$. We consider a nonstationary extension where the Hurst exponent is a function of time, and potentially random. The construction admits the standard linear fractional sta

Jonathan Krönke, Arie Staal, Jonathan F. Donges, Johan Rockström

The Amazon rainforest is considered one of the core tipping elements in the climate system with a potential tipping point from rainforest to savannah between 2 and 6 {\deg}C of global warming. However, ongoing deforestation constitutes an additional major threat to the Amazon rainforest that acts simultaneously to undermine the stability of the rainforest. B

Uttam Cadambi Padmanaban, Craig Thompson, Bharathram Ganapathisubramani, Sean Symon

The full-field reconstruction of three-dimensional (3D) turbulent flows from sparse experimental measurements remains a significant challenge, particularly for flows exhibiting complex 3D flow separation. In this work, we address this challenge for the case of stall cells - spanwise coherent structures that form on the suction surface of wings at post-stall

Shinichi Inoue, Rui Li, Kentaro Kubo, Yinghao Ho

A double-transmon coupler (DTC) enables a fast, high-fidelity CZ gate between two highly detuned, fixed-frequency transmon qubits. Moreover, a recently proposed capacitively shunted DTC (CSDTC) realizes a small residual ZZ interaction over a wide flux-bias range around zero flux, eliminating the necessity of static flux biasing while maintaining high CZ-gate

Shuang-Jie Liu, Gao-Feng Wei, Yu-Liang Zhao, Feng-Chu Zhou

Within an extended isospin- and momentum-dependent Boltzmann-Uehling-Uhlenbeck transport model, we study the protons, $K^+$ mesons and $\Lambda$ hyperons production in Au+Au collisions at $\sqrt{s_{\rm NN}}=3$ GeV. For the collision in 0-10% centrality, we study the transverse momentum spectra and rapidity dependent mean transverse momentum for protons. For

Haocheng Huang, Yuchen Chen, Weisong Sun, Peizhuo Lv

Constructing and curating high-quality code datasets requires significant resources, making them valuable intellectual property. Unfortunately, these datasets currently face severe risks of unauthorized use. Although digital watermarking offers a post hoc mechanism for copyright authentication, existing methods are predominantly based on the co-occurrence pa

Riz Fernando Noronha, Kunihiko Kaneko, Koichi Fujimoto

Arabidopsis roots show oscillatory growth patterns on homogeneous agar surfaces, whereas other plants, such as maize, do not. Although several explanations have been proposed, a simple and general model that makes testable predictions across species has been lacking. Roots sense gravity and correct their growth direction towards the vertical. Motivated by re

Hiroyuki Deguchi, Katsuki Chousa, Yusuke Sakai

The hubness problem, in which hub embeddings are close to many unrelated examples, occurs often in high-dimensional embedding spaces and may pose a practical threat for purposes such as information retrieval and automatic evaluation metrics. In particular, since cross-modal similarity between text and images cannot be calculated by direct comparisons, such a

Sebastiano Franchini, Alexis Carrillo, Edoardo Sebastiano De Duro, Riccardo Improta

We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents"), verbs (``Events"), and objects (``Targets") from texts. Grounded in cognitive network science and artificial intelligence, TEA Nets are implemented as an open-source Python library. We test TEA Nets in three case studies, demonstrating the framew

José Álamos, Thomas C. Schmidt, Matthias Wählisch

LoRa has become a widely adopted wireless modulation scheme in LPWANs due to its low cost, long range, and minimal transmission power. However, collisions between frames of the same spreading factor -- common in dense LoRa deployments -- prevent conventional LoRa receivers from detecting and correctly decoding frames. Recent work has introduced methods to im

Ricardo Luna Gutierrez, Sahand Ghorbanpour, Ejaz Rahman, Varchas Gopalaswamy

Inertial Confinement Fusion (ICF) holds transformative promise for sustainable, near-limitless clean energy, yet remains constrained by prohibitively high costs and limited experimental opportunities. This paper presents Human-in-the-Loop Meta Bayesian Optimization (HL-MBO), a framework that integrates expert knowledge with few-shot, uncertainty-aware machin

K. Abe, S. Abe, J. Abhir, A. Abhishek

Cygnus X-3 is a microquasar composed of a compact object of unknown nature closely orbiting around a Wolf-Rayet star. The particularities of this source make it a unique case among microquasars. This fact, together with its recent establishment as a PeV particle accelerator, makes Cygnus X-3 a very interesting target for the investigation of the physical pro

Javier de Lucas, Julia Lange, Xavier Rivas, Cristina Sardón

This article develops a Hamilton--Jacobi theory for non-conservative classical field theories, with particular emphasis on dissipative systems, in the framework of co-oriented k-contact geometry. We introduce evolution k-contact k-vector fields, extending the contact evolution formalism to field theories, and analyse the corresponding Hamilton--De Donder--We

Pedro F. C. de Carvalho, Zijie Liu, Md Umar Hashmi, Dirk Van Hertem

The incorporation of fairness into the distribution network (DN) planning and operation has become a key goal of recent studies. The cost of implementing fairness, denominated the price of fairness (PoF), covers the efficiency that is renounced for attaining social cohesion through fair outcomes. Locational disparity makes fairness schemes emerge to level th

Hao Wu, Qichun Liu, Yuanbin Fan, Yulong Liu

Magnon-polaritons provide a room-temperature platform for investigating nonlinear cavity quantum electrodynamics in the microwave domain, but experimentally observing controlled transitions among distinct nonlinear attractors remains challenging in conventional passive systems, where strong external driving is usually required. Here we report the observation

Buqing Ou, Frederike Dümbgen

Policy optimization in high-dimensional continuous control for robotics remains a challenging problem. Predominant methods are inherently local and often require extensive tuning and carefully chosen initial guesses for good performance, whereas more global and less initialization-sensitive search methods typically incur high rollout costs. We propose TFM-S3

Xiaokun Luan, Yihao Zhang, Pengcheng Su, Feiran Lei

Large Language Model (LLM) watermarking is crucial for establishing the provenance of machine-generated text, but most existing methods rely on a centralized trust model. This model forces users to reveal potentially sensitive text to a provider for detection and offers no way to verify the integrity of the result. While asymmetric schemes have been proposed

Yi Guo

In this paper, we aim at estimating the quarticity of continuous It\^{o} semimartingales. Instead of using some classical estimators, we introduce a more intuitive one and establish a central limit theorem (CLT) for it, with a convergence rate of $1/\sqrt{\Delta_n}$ in the sense of stable convergence. Moreover, we compare the asymptotic variance of this esti

Biel Pons Zaragoza, Junaid Khan, Rohit Sarma Sarkar, Sahar Ben Rached

In multi-core quantum computing architectures, waveguide-mediated interconnects are essential for facilitating fast, high-fidelity quantum state transfer between qubits located in different chips. However, optimizing these systems typically relies on computationally expensive numerical simulations that offer limited physical insight. In this work, we derive

Stepanov Sergey

We develop a harmonic gauge on the space of Riemannian metrics and study its role in the variational and flow-theoretic structure of geometric analysis. We prove that the harmonic gauge eliminates divergence-type terms in the first variation of the Hilbert-Einstein functional and induces a natural elliptic structure for the second variation. As a consequence

Jian Wang, Mark Williams

We construct pulse-type approximate solutions to nonlinear hyperbolic equations near diffractive points, allowing arbitrary (even infinite) order of grazing. We show that in low regularity spaces and the high frequency limit, such solutions can be approximated by a sum of incoming and reflected pulses constructed using incoming and reflected phases and profi

Emilia Milano, Alistair Plum, Yves Scherrer, Christoph Purschke

Detecting language ideologies is a valuable yet complex task for understanding how identities are constructed through discourse. In Luxembourg's multicultural and multilingual society, language ideologies reflect more than simple preferences: they carry deep cultural and social meanings, shaping identities and social belonging. Following recent developments

Rongji Huang, Yifeng Ye, Gerui Wang, Mingchao Wan

Due to regulatory compliance and governance management, modern (permissioned) blockchains require flexible endorsement, which allows the endorsement policy for each contract or state object to be individually defined. To enable flexible endorsement, Hyperledger Fabric employs an execute-order-validate (EOV) paradigm, in which transactions first undergo specu

Marco Battestini, Jules Morand, Giulio Bordieri, Marta Missiaggia

In conventional radiotherapy, the probability of controlling tumor growth is quantified using Tumor Control Probability (TCP) models. Instead, the probability of experiencing a side effect after the irradiation of healthy tissues and organs is typically assessed using the concept of Normal Tissue Complication Probability (NTCP), an additional crucial metric

Maxime Roumesy, François Ménard, Gaspard Duchêne, Ryo Tazaki

The evolution of protoplanetary disks, especially in the early stages of planetary formation, as dust grows, is the cornerstone of the birth of planets. The mechanisms involved in the growth of sub-micrometric dust grains into planetesimals within a very short time frame are a challenging field of study, while the initial conditions remain relatively undefin

Kathrin Korte, Joachim Winter Pedersen, Eleni Nisioti, Sebastian Risi

To preserve previously learned representations, continual learning systems must strike a balance between plasticity, the ability to acquire new knowledge, and stability. This stability-plasticity dilemma affects how representations can be reused across tasks: shared structure enables transfer when tasks are similar but may also induce interference when new l

Paul Baird

We study systems of {\sigma}-algebras ordered by refinement and introduce the notion of an endogenous probability measure, invariant under admissible refinement transformations. We prove existence and structural properties of such measures on finite systems and show how refinement operators induce a natural dynamical structure on the lattice of {\sigma}-alge

Bohai Zhang, Wenjie Chen, Mu Li, Kaixing Long

Accurate CT-MRI registration of the cervical spine is essential for preoperative planning because this region is anatomically complex,highly variable,and vulnerable to injury of the vertebral arteries and spinal cord. However,cervical CT-MRI registration remains underexplored,particularly for rigid-deformable hybrid modeling,and the lack of high-quality anno

Dahua Gao, Yubo Dong, Anqi Li, Zhenyuan Lin

Conventional push-broom hyperspectral imaging suffers from slow acquisition speeds, precluding real-time object detection; in contrast, snapshot spectral imaging enables instantaneous hyperspectral images (HSIs) capture, making real-time object detection feasible, yet its potential is often compromised by time-consuming post-capture reconstruction. To addres

Faisal Etminan

The possible bound state of the $c\bar{c}+n+^{10}$Be system, representing a hypothetical charmonium-nucleus configuration, is investigated. The analysis is conducted within a three-cluster framework, in which the binary subsystems are treated as $n+^{10}\textrm{Be}$, $^{10}\textrm{Be}+c\bar{c}$, and $c\bar{c}+n$. The hyperspherical harmonics method is employ

Yuichi Yoshida

For a connected weighted hypergraph, we give a randomized almost-linear-time solver for the Poisson problem for the cut-based hypergraph Laplacian in the natural input size $P=\sum_{e\in E}|e|$, the sum of hyperedge sizes. For every fixed constant $C>0$, our randomized algorithm runs in $P^{1+o(1)}$ time and, with high probability over its internal randomnes

Jingyeong Hwang, Jaesang Lee, Jiin Bang, Younghyun Lee

Biological neurons perform arithmetic computations - including additive integration and divisive gain modulation - through synaptic conductance changes and shunting inhibition, enabling context-dependent information processing that far exceeds simple threshold-and-fire models. Replicating these capabilities in compact hardware remains a fundamental challenge

Sébastien Le Bihan, Anton Dmytriiev, Andreas Zech

The blazar 3C 279 is well known for its rapid and large-amplitude variability. On 20 December 2013, the source exhibited an orphan {\gamma}-ray flare characterized by a flux-doubling timescale of a few hours, a very hard spectrum, a time-asymmetric light curve with a slow decay, and no significant optical variability. We propose a new interpretation of this

Vinayak, Ajeet Kumar

One-dimensional periodic rod networks are the structures that are obtained by periodically assembling its microstructural unit, a network of rods itself, in just one direction. In this work, we present a scheme for obtaining the nonlinear constitutive response of such structures when homogenized macroscopically as a continuum rod. To accurately capture arbit

Aoi Matsuda, Fumio Machida, David Lo

Machine learning (ML)-based API recommendation helps developers efficiently identify suitable APIs to complement the application code. However, code datasets used to train ML models often exhibit a long-tail distribution, leading to unreliable API recommendations, especially for infrequently used API methods at the tail of the distribution. To address this i

Xinjie Mao, Songming Zhang, Qianhong Wen, Xiangyu Wen

Virtual cell (VC) models aim to predict cellular responses to any perturbations in silico and have emerged as a promising approach for drug discovery and precision medicine. Yet, a clear gap still remains: while models routinely reported impressive results on standard benchmarks, it is unclear whether their predictions are truly meaningful in practice. This

Yinqi Sun

We present a rank-$23$ algorithm for general $3\times3$ matrix multiplication that uses $56$ additions/subtractions and $23$ multiplications, for a total of $79$ scalar operations in the standard bilinear straight-line model. This improves the recent sequence of $60$-, $59$-, and $58$-addition rank-$23$ schemes. The algorithm works over arbitrary associative

Chengcao Yang

We propose a paradigm shift toward open-ended curriculum self-play: rather than learning to answer on a fixed prompt set, a unified policy learns to question: generating verifiable problems, solving them, and turning verifier feedback into self-improvement without human-annotated solutions. We introduce ANCORA, in which the policy alternates between a Propos

Bruno Buonomo, Eleonora Messina, Claudia Panico, Mario Pezzella

We present EPITIME (EPidemic Integral models TIMe profile Explorer), a computational framework for the simulation of two classes of integral epidemic models: an age of infection model and an information dependent behavioural model. The framework combines structure preserving Non-Standard Finite Difference discretizations with modular implementations in MATLA

Chang-Chih Meng, Yu-Ren Lu, Guan-Yu Lin, Tsung Tai Yeh

Integrated Circuit (IC) verification consumes nearly 70% of the IC development cycle, and recent research leverages Large Language Models (LLMs) to automatically generate testbenches and reduce verification overhead. However, LLMs have difficulty generating testbenches correctly. Unlike high-level programming languages, Hardware Description Languages (HDLs)

Oscar Johansson, Jürgen Börstler, Nauman bin Ali

Context: Many organizations are keen to incorporate generative~AI (GenAI) into their software development processes. Technology acceptance models, such as the Unified Theory of Acceptance and Use of Technology (UTAUT), are traditionally used to identify individual-level barriers to the acceptance of new technologies and can facilitate the transition to GenAI

Jihoon Lee, Seungeun Oh, Jihong Park, Seong-Lyun Kim

Despite the rise of token communication (TokCom) as a new paradigm beyond traditional bit communication, existing approaches have primarily adopted artificial intelligence (AI)-centric designs that rely on semantic recovery via large models. Meanwhile, their physical-layer designs, such as token-bit mapping and power allocation, remain conventional and do no

Aygun Baltaci, Irshad A. Meer, Mustafa Ozger, Cicek Cavdar

Future uncrewed aerial vehicle (UAV) systems increasingly combine heterogeneous communication technologies, such as low-latency aerial mesh, terrestrial cellular, and satellite links, to improve robustness and coverage. Multipath transport is a natural mechanism for aggregating these links, yet its ability to support real-time UAV services in highly heteroge

Janos Pach

Let $k\ge 2$ be fixed integer, $0<c<1$ a constant. Consider a graph $G$ with $n$ vertices and average degree $cn$. We answer a question of Simon Griffiths by showing that $G$ has $k$ vertices such that their neighborhoods together cover at least $\min(1-(1-c)^{k},\sqrt{c})n$ vertices. This result is essentially tight.

Daisy R Bradley, Elizabeth J Cross

Machine learning continues to emerge as an important tool to be utilised within structural engineering and structural health monitoring, due to its ability to accurately and quickly perform both regression and classification tasks. However, a purely data driven approach has its limitations, particularly where we lack data from relevant environmental and oper

Nicholas Sadjoli, Tim Siefken, Atin Ghosh, Yifan Mai

Current Large Language Model (LLM) evaluation frameworks utilize the same static prompt template across all models under evaluation. This differs from the common industry practice of using prompt optimization (PO) techniques to optimize the prompt for each model to maximize application performance. In this paper, we investigate the effect of PO towards LLM e

Yiru Wang, Anqing Jiang, Shuo Wang, Yuwen Heng

Open-loop evaluation offers fast, reproducible assessment of autonomous driving planners, but its ability to predict real closed-loop driving performance remains questionable. Prior work has shown that traditional open-loop metrics such as Average Displacement Error (ADE) and Final Displacement Error (FDE) exhibit no reliable correlation with closed-loop Dri

Philipp Rieder, Julia La Roche, Orkun Furat, Annalena Kuhn

Peptide nanofibrils (PNFs) and peptide amphiphiles (PAs) are promising tools for enhancing viral transduction and gene transfer. However, quantitative insight into how their supramolecular architecture governs virion-cell interactions is limited. Here, we introduce a framework for the acquisition, processing, and statistical analysis of scanning transmission

Teddy Gonzales, Chayim Lowen

We investigate several aspects of the Bialynicki-Birula decomposition of a smooth complete $\mathbb{G}_m$-variety with finite fixed locus. Our results include novel characterizations of when the Bialynicki-Birula decomposition is filterable or forms a stratification, showing that these properties are invariant under reversing the $\mathbb{G}_m$-action. We ad

Petter Törnberg, Michelle Schimmel

Large language models (LLMs) are commonly evaluated for political bias based on their responses to fixed questionnaires, which typically place frontier models on the political left. A parallel literature shows that LLMs are sycophantic: they adapt their answers to the views, identities, and expectations of the user. We show that these findings are linked: st

Nanse Esaki, Gyungchoon Go, Se Kwon Kim

We theoretically demonstrate that quantum fluctuations inherent to antiferromagnets can generate scalar spin chirality at zero temperature even in coplanar ordered magnets. In a kagome antiferromagnet with coplanar ground-state spin configurations, the quantum-fluctuation-induced scalar spin chirality is shown to arise at zero temperature when an effective t

Mykola Pochekai

We formulate and prove Parseval-Rayleigh identities for graded Artinian Gorenstein algebras over fields of positive characteristic. Specializing the general result, we provide an alternative proof of the Parseval-Rayleigh identities of generic Artinian reductions of Stanley-Reisner rings of oriented simplicial spheres.

Ke Xu, Zhongyuan Lian

We present WaferSAGE, a framework for wafer defect visual question answering using small vision-language models. To address data scarcity in semiconductor manufacturing, we propose a three-stage synthesis pipeline incorporating structured rubric generation for precise evaluation. Starting from limited labeled wafer maps, we employ clustering-based cleaning t

Matteo Cozzi, Jack Thompson

We establish a half-space theorem \`a la Hoffman and Meeks for nonlocal minimal surfaces. Differently from the classical case, our result holds in every dimension.

Nannan Li, Xing Gao

We establish an It\^o-type formula for finite $p$-variation paths with jumps for arbitrary $p\geq 1$. The formula is stated in a fully pathwise form and separates the reduced rough integral from explicit left- and right-jump correction terms. In the c\`adl\`ag case, only the left-jump correction remains, while in the continuous case, both jump correction ter

Muhammet Anil Yagiz, Fahrettin Horasan, Ahmet Hasim Yurttakal

Integrity of audit logs produced by Internet of Things (IoT) devices is a prerequisite for post-incident forensics, regulatory compliance, and operational accountability. While blockchain-backed logging infrastructures can satisfy this requirement, they introduce consensus overhead, network dependencies, and deployment complexity that are often prohibitive a

Ruoxiao Cao, Wentao Yu, Zixin Wang, Shenghui Song

Flexible-antenna systems, which use a small number of radio frequency (RF) chains to dynamically access a large set of candidate antenna locations, have emerged as a hardware-efficient architecture for 6G networks. Acquiring accurate channel state information (CSI) is critical for these systems, but it typically incurs a prohibitive pilot overhead that scale

Xiancong Wu, Hongguang Wang, Hao Tong, Rui Luo

The long-standing assumption of symmetric radio emission beams from the two magnetic poles of pulsars is challenged by observational evidence of asymmetry and underfill. Direct testing of this symmetry remains difficult for most pulsars. As an indirect test, we collected polarization profiles of 11 interpulse pulsars observed with the Five-hundred-meter Aper

Ali Aghazadeh Ardebili, Massimo Stella

Large Language Models (LLMs) can strongly shape social discourse, yet datasets investigating how LLM outputs vary across controlled social and contextual prompting remain sparse. Cognitive Digital Shadows (CDS) is a 190,000-record synthetic corpus supporting analyses of LLM-generated discourse. Each CDS record is generated by one of 19 LLMs, prompted to shad

James F. E. Croft, Brian K. Kendrick, Jeremy M. Hutson

We use coupled-channel calculations to explore the nature of near-threshold bound states in a simplified model of Rb+KRb. This is a prototype for systems with very strong coupling at short range and chaotic behavior for the short-range states. We find that there are states with strong long-range character that exist close to threshold and probably persist to

George Dunn

Order picking travel dominates much of warehouse effort, and exact routing is especially valuable when storage is scattered so pick locations are not fixed in advance. We address the single picker routing problem (SPRP) and its scattered-storage variant (SPRP-SS) in single-block and two-block rectangular warehouses. We propose two mixed-integer linear progra

Junyi Ma, Erhang Zhang, Haoran Yang, Ditao Li

A critical bottleneck hindering further advancement in embodied AI and robotics is the challenge of scaling robot data. To address this, the field of learning robot manipulation skills from human video data has attracted rapidly growing attention in recent years, driven by the abundance of human activity videos and advances in computer vision. This line of r

Pengna Li, Kangyi Wu, Shaoqing Xu, Fang Li

Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unseen 3D environments. We argue that adapting VLMs to VLN requires endowing them with two complementary capabilities for acquiring such awareness, namely backward action reasoning (why) and forward transition pre

Zoe Himwich

We construct the multilevel correlation kernel for the rising GUE eigenvalue process starting from a fixed initial configuration $x^{(m)}$, and show that it converges on short time scales (as quickly as $\text{polylog}(m)$) to the extended semi-discrete sine kernel. As an application, we show fixed-energy universality of bulk local statistics of complex Herm

Jiacheng Liu, Zichen Tang, Zhongjun Yang, Xinyi Hu

People commonly leverage structured content to accelerate knowledge acquisition and research problem solving. Among these, roadmaps guide researchers through hierarchical subtasks to solve complex research problems step by step. Despite progress in structured content generation, the roadmap generation task has remained unexplored. To bridge this gap, we intr

Wu Wang, Ke Zhang, Ke-Mi Xu, Jin-Bo Hu

We present a comprehensive theoretical investigation of hyperfine-resolved excitation and detection of the low-energy isomeric state of $^{229}$Th in trapped $^{229}\mathrm{Th}^{3+}$ ions. Using a quantum master equation approach, we quantitatively analyze the dependence of the isomeric population on laser linewidth, detuning, and irradiation time, showing t

Yan Lin, Jilin Hu, N. M. Anoop Krishnan, Morten M. Smedskjaer

Amorphous (disordered) materials are solids that have shown great potential in various domains, including energy storage, thermal management, and advanced materials. Unlike crystalline materials that can be described by unit cells containing a few to hundreds of atoms, amorphous materials require larger simulation cells with at least hundreds to thousands of

Takaaki Nomura, Hiroshi Okada

We propose a novel mechanism to explain the naturally small vacuum expectation values (VEVs) of exotic multi-Higgs fields by employing non-invertible symmetries. Specifically, we introduce an $SU(2)_L$ quartet $H_4$ and a quintet $H_5$ within the framework of the minimal Fibonacci fusion rule (FFR). This non-invertible symmetry strictly forbids the generatio