April 2026 arXiv papers — page 28

B. van Es

Background: Dutch medical corpora are scarce, limiting NLP development. Methods: We translated English datasets, identified medical text in generic corpora, and extracted open Dutch medical resources. Results: The resulting corpus comprises +- 36 billion tokens across the medical domain in about 105 million documents, freely available on Hugging Face. Conclu

Amir Ali Farzin, Philipp Braun, Iman Shames

While it is generally understood that zeroth-order (ZO) algorithms have an extra dependency on their number of iterations for any choice of parameters, compared to their first-order (FO) counterparts, in this work, we show that under several conditions, in expectation, ZO methods do not suffer from extra dimension dependencies in their convergence rates with

Kidus Zewde, Simiao Ren, Xingyu Shen, Jiaqi Wu

The release of GPT-image-2 by OpenAI marks a watershed moment in AI-generated imagery: the boundary between photographic reality and synthetic content has never been more difficult to discern. We introduce the GPT-Image-2 Twitter Dataset, the first published dataset of GPT-image-2 generated images, sourced from publicly available Twitter/X posts in the immed

Quentin Vacher, Nicolas Beuve, Mickaël Dardaillon, Karol Desnos

Over the past few decades, machine learning has been widely used to learn complex tasks. Reinforcement Learning (RL), inspired by human behavior, is a great example, as it involves developing specific behaviours for specific tasks. To further challenge algorithms, Multi-Task RL (MTRL) environments have been introduced, requiring a single model to learn multi

Johannes Brutsche, Sebastian Hahn, Angelika Rohde

Based on discrete observations $X_0,X_{\Delta},\dots, X_{n\Delta}$ for $\Delta=n^{-\gamma}$ with $\gamma\in [0,1)$ of the null-recurrent dynamic $dX_t = \sigma(X_t)dW_t$ with a Brownian motion $W$ and $\sigma(x)=\alpha\mathbb{1}\{x<\rho\} + \beta\mathbb{1}\{x\geq \rho\}$, we derive rate of convergence and limiting distribution of the profile MLE for $\rho$.

Jianyu Wen, Jun Xie, Feng Chen, Zhepeng Wang

In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our previous Self-Reference Deep Adaptive Curve Estimation (Self-DACE). To better address the trade-off between computational efficiency and restoration quality, Self-DACE++ introduces enhanced Adaptive Adjustment Cu

Mitsuyoshi Adachi

In the previous paper, the author showed that for a smooth family $X \to \mathbb{X} \to B$ of a homotopy $K3$ surface, the obstruction for the tangent bundle along the fibers $T_B \mathbb{X}$ to have a spin structure is canonically isomorphic to the obstruction for $\mathcal{H}^+(\mathbb{X})$, the vector bundle over $B$ consisting of self-dual harmonic 2-for

Juan Pardo-Montero

Objective: This study aims to investigate the influence of organ architecture (specifically the distinction between serial and parallel tissue) on the protective FLASH effect when organs are irradiated with inhomogeneous dose distributions. Approach: An in silico modeling framework was developed using two distinct methods to calculate the effective FLASH dos

A. Barletta, D. A. S. Rees

The threshold conditions to convective instability in a semi-infinite porous layer saturated by a fluid are determined. The classical setup for this problem in geothermal fluid dynamics was originally modelled by Wooding in 1960. Its formulation is here reconsidered to allow for an imperfect heat transfer across the boundary, parametrised through the Biot nu

Bingzi Zhang, Kaisi Guan, Ruihua Song

Video generation models have developed rapidly in recent years, where generating natural human motion plays a pivotal role. However, accurately evaluating the quality of generated human motion video remains a significant challenge. Existing evaluation metrics primarily focus on global scene statistics, often overlooking fine-grained human details and consequ

Haowei Yuan

The continuous linear $P(k; N, w)$ and circular scan statistics $P_c(k; N, w)$ are fundamental tools in probability and spatial statistics, frequently used to detect clustering in uniform data. Let $X_1, X_2, \dots, X_N$ be independently and uniformly distributed random variables on a unit interval or unit ring. The exact distribution of these scan statistic

Abhinav Kumar Singh, Harsha Vardhan Khurdula, Yoeven D Khemlani, Vineet Agarwal

Large Language Models are increasingly being deployed to extract structured data from unstructured and semi-structured sources: parsing invoices, medical records, and converting PDF documents to database entries. Yet existing benchmarks for structured output generation either focus on schema compliance alone, or evaluate value correctness within a single sou

Luca Parolari, Nicla Faccioli, Lamberto Ballan

Evaluating layout-guided text-to-image generative models requires assessing both semantic alignment with textual prompts and spatial fidelity to prescribed layouts. Assessing layout alignment requires collecting fine-grained annotations, which is costly and labor-intensive. Consequently, current benchmarks rarely provide comprehensive layout evaluation and o

Cindy Pistorius, J. Theresia van Essen

Uncertainty in surgery durations continues to be difficult to account for in operating room scheduling. In particular, it remains complex to accurately incorporate uncertainty in surgical overtime constraints within mixed-integer linear programming (MILP) models. Therefore, we propose a method that integrates feedforward neural networks (FNNs) into MILP mode

Laura Hellwege, Johann Christopher Engster, Moritz Schaar, Thorsten M. Buzug

Dual-energy computed tomography (DECT) enables material-specific imaging through acquisitions at two different X-ray energy spectra. Material decomposition from DECT data is an ill-posed inverse problem that is highly sensitive to noise amplification. Conventional methods face challenges regarding accuracy and computational efficiency. We present a novel phy

Yaqi Chen, Hao Chen, Cunsheng Ding, Huimin Lao

Goppa codes form an important class of alternant codes with wide applications in algebraic coding theory and code-based cryptography. Determining the true minimum distance of a Goppa code is a difficult problem. In this paper, we provide a necessary and sufficient criterion for a Goppa code to attain its designed distance $\delta=t+1$, where $t$ is the degre

Guiquan Wang, Willem Van Roy, Chengxun Liu, Tim Stakenborg

This study investigates the lift force acting on a finite-size, neutrally buoyant spherical particle suspended in a liquid while flowing through a shallow channel at low Reynolds numbers. Using an immersed boundary method, we calculate the lift force for particle radius-to-channel height ratios spanning \(0.03 \leq a/H \leq 0.35\) in 2D planar Poiseuille flo

Xingjian Hu, Zuoyu Yan, Jianhua Zhu, Liangcai Gao

Current research on distributed multi-modal learning typically assumes that clients can access complete information across all modalities, which may not hold in practice. In this paper, we explore patchwork learning, in which the modalities available to different clients vary, and the objective is to impute the missing modalities for each client in an unsupe

Julián Urbano

In benchmarking of Information Retrieval systems, the Wilcoxon signed-rank test is often treated as a safer alternative to the t-test. This belief is fueled by textbooks and recommendations that portray Wilcoxon as the proper non-parametric alternative because metric scores are not normally distributed. We argue that this narrative is misleading and harmful.

Ali Asghar Molavi Choobini, Mehran Shahmansouri

This study presents theoretical and numerical investigation of the coupled longitudinal and radial wakefields excited by ultrarelativistic electron beams propagating through a cold plasma channel subjected to an external axial magnetic field. A fully causal three dimensional Green function formalism is developed directly from the linearized Maxwell fluid equ

S. S. Ghaffari-Oskooei, A. A. Molavi Choobini

A fluid-based theoretical framework is developed to describe the nonlinear cascade linking primary BRS-driven plasma wave amplification, oscillating two-stream instability (OTSI), nonlinear current generation within a self-formed ponderomotive channel, and radiation of the secondary electromagnetic mode. Systematic parameter studies reveal a strong sensitivi

Geraldo Xexéo

Artificial intelligence systems are increasingly integrated into writing processes, challenging traditional notions of authorship, responsibility, and intellectual contribution. Current disclosure practices usually indicate whether AI was used, but rarely explain how it was used, where it intervened, or how its output was reviewed. This paper proposes a face

Lewis Stanton, Fedor Vylegzhanin

We show that the loop homology algebras of polyhedral products of the form $(\underline{X},\underline{*})^{\mathcal{K}}$ can be written as a colimit over the flagification of $\mathcal{K}$, and obtain a similar result for the Poincar\'e series. This effectively reduces the study of the algebras $H_*(\Omega(\underline{X},\underline{*})^{\mathcal{K}})$ to the

Changming Ke, Shi Liu

Wurtzite ferroelectrics such as scandium-doped aluminum nitride (AlScN) are promising for next-generation memory because of their compatibility with semiconductor processes and strong spontaneous polarization. Ferroelectric switching in these materials is typically attributed to doping-induced softening of the bulk switching barrier. However, recent reports

Riccardo Pajno, Felicetta Carillo, Paolo Maranzano, Timo Schmid

The agricultural sector is undergoing rapid change due to climate pressures, demographic shifts, and uneven economic development, increasing the demand for reliable environmental indicators at fine spatial scales. However, limited data availability often constrains subregional analyses. This study develops a model-based framework for producing reliable small

Stijn Cambie, Jionghua Chang

We estimate the maximum ratio between the $\sigma_t$- and $\sigma$-irregularity for graphs and trees of order $n$, which are respectively bounded by $\Theta(n^{5/2})$ and $n-2$. This answers a question and a conjecture by Filipovski et al. in an elegant way. For trees, we obtain that the (Albertson) irregularity measure $\irr$ is an upper bound for the graph

Wei Hu, Feiyue Huang, Yanbo Li, Xiangyu Qi

Duality relations between Lie algebras are a significant phenomenon in Lie algebra representation theory, with level-rank duality as a famous example. Level-rank dualities for affine Lie algebras of type $A^{(1)}$ were first discovered by Frenkel in 1982, and later extended to all classical non-twisted affine types by Hasegawa in 1989 through elaborate chara

Ignacio Diaz Alastuey, Yann Le Gorrec, Yongxin Wu

This paper generalises an early lumped observer-based state-feedback (OBSF) control design methodology, originally developed for one-dimensional (1-D) boundary-controlled port-Hamiltonian systems, to a two-dimensional (2-D) boundary-controlled Mindlin plate. To this end, the 2-D port-Hamiltonian Mindlin plate model is first introduced and then discretized us

Jangho Baik, Sunghyun Kim, Gisan Ji, Wonbo Shim

Recommendation system has gained a large popularity for a variety of personalized suggestion tasks, but the ever-increasing number of user data makes real-time processing of recommendation systems difficult. NAND flash memory-based in-storage computing scheme can be one of favorable candidates among the various acceleration approaches because the flash memor

Agustin Feregrino, Nelson Cisneros, Alexis Lefèvre, Yongxin Wu

This paper presents the mechatronic design, dynamic modeling, and experimental validation of a three-degree-of-freedom (3-DOF) micro parallel robot featuring a prismatic-spherical (3PS) topology actuated by three Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuators. Each soft actuator provides the prismatic motion of an individual limb, while

Silin Huang

The $A_\alpha$-matrix of a digraph $D$ is defined as a linear convex combination $\alpha\operatorname{Deg}(D)+(1-\alpha)A(D)$ of the adjacency matrix $A(D)$ and the diagonal out-degree matrix $\operatorname{Deg}(D)$, where $\alpha\in[0,1]$. The low energy of $A_\alpha(D)$ is defined as the sum of the absolute values of the real parts of the eigenvalues of $A

Hongfei Wu, Ruijian Han, Yancheng Yuan

Imbalanced classification remains a pervasive challenge in machine learning, particularly when minority samples are too scarce to provide a robust discriminative boundary. In such extreme scenarios, conventional models often suffer from unstable decision boundaries and a lack of reliable error control. To bridge the gap between generative modeling and discri

Yanqiao Wang, Jin-Peng Liu

We develop a systematic sign-embedding framework of operator-output quantum algorithms for matrix equations and matrix functions. Differing from the contour-integral treatment, we start with the matrix-sign embedding route: an augmented matrix $M$ whose half-plane matrix sign compresses the target operator either as a block of $\text{sign}(M)$ or, in project

Valentin Cuzin-Rambaud, Laetitia Matignon, Maxime Morge

In multi-agent reinforcement learning (MARL), the integration of a communication mechanism, allowing agents to better learn to coordinate their actions and converge on their objectives by sharing information. Based on an interaction graph, a subclass of methods employs graph neural networks (GNNs) to learn the communication, enabling agents to improve their

Rayane Bakari, Olivier Le Blouch, Nicolas Gengembre, Nicholas Evans

Automatic accent identification (AID) remains a challenging task due to the complex variability of accents, the entanglement of accent cues with speaker traits, and the scarcity of reliable accentlabelled data. To address these challenges, we propose a speaker augmentation strategy using voice conversion (VC), with which we generate additional training data

Dingxi Yang, Wenqi Guo, Yue Liu, Jungong Han

Real-time immersive video communications, particularly high-fidelity 3D telepresence, necessitates a synergistic balance between instantaneous dynamic scene reconstruction and high-efficiency data transmission. While recent advancements in feed-forward 3D Gaussian Splatting (3DGS) have enabled real-time rendering, performing multi-view video coding and 3D re

Chuyao Fu, Shengzhe Gan, Zhuoli Ouyang, Yuhan Rui

End-to-end autonomous driving planners typically generate trajectories from current observations alone. However, real-world driving is highly dynamic, and such reactive planning cannot anticipate future scene evolution, often leading to myopic decisions and safety-critical failures. We propose ProDrive, a world-model-based proactive planning framework that e

Yanhui Chen, Chaomi Duan, Yi Yu

LAMOST J052016.79+345651.7 was identified as an EW-type eclipsing binary by Chen et al. when studying the periodic variable stars based on the ZTF telescope. An orbital period of 0.3507818 days has been reported. Using the ZTF g, r, i band light curves, we reproduced the orbital period and obtained a phase folded diagram. The multi-band apparent magnitudes f

Ma Zirui, Fan Zhihua, Li Wenxing, Wu Haibin

Speculative decoding enhances the inference efficiency of large language models (LLMs) by generating drafts using a small draft language model (DLM) and verifying them in batches with a large target language model (TLM). However, adaptive drafting inference on a mobile single-NPU-PIM system faces idle overhead in traditional operator-level synchronous execut

Hojae Han, Yeonseok Jeong, Seung-won Hwang, Zhewei Yao

Modern Text-to-SQL systems generate multiple candidate SQL queries and rank them to judge a final prediction. However, existing methods face two limitations. First, they often score functionally equivalent SQL queries inconsistently despite identical execution results. Second, ranking cannot recover when the correct SQL is absent from the candidate pool. We

Carl Jonas Linnemann, Kim-Khuong Huynh, Davide Ceresoli, Martin Bremholm

Marcasite compounds formed between $3d$ transition metals and antimony (TMSb$_2$) have been heavily studied due to their intriguing physical properties. For instance they can possess flat bands in their electronic structure, however due to their semiconducting nature, these intriguing electronic states often reside far from the Fermi level, and observations

Jinhao Jiang, Shengyu Fang, Sibo Zuo, Yujie Tang

Recent advances in open-vocabulary mobile manipulation have brought robots into real domestic environments. In such settings, reliable long-horizon execution under open-set object references and frequent disturbances becomes essential. However, many failures persist. These are not caused by semantic misunderstanding but by inconsistencies between symbolic pl

Benedikt Peterseim, Milan Lopuhaä-Zwakenberg

Discrete probabilistic programs (DPPs) provide a highly expressive formalism for compactly defining arbitrary finite probabilistic models. This expressivity comes at a price: DPP inference is PSPACE-hard. In this work, we show that DPP inference only takes polynomial time for programs that are 'structurally simple'. More precisely, inference can be performed

Yinuo Xue, Qian Chen, Jing-Song Huang

We present a criterion that serves as the basis for a polynomial-time algorithm to decide whether a finite set of qudit gates exponentiated by some Hamiltonians is universal. Our approach formulates universality in Lie algebraic terms and applies Borel--de Siebenthal theory with a diagonal generator having incommensurate spectrum. In this framework, nonunive

Daniela Kraus, Annika Moucha, Oliver Roth

Forward iteration of holomorphic self-maps generalizes the iteration of a single function in a natural way. This framework arises in complex dynamics, for instance in the study of wandering domains and in seeking suitable extensions of the Denjoy-Wolff theorem. Here, we consider forward iteration of Blaschke products. We prove that the classes of indestructi

Yun Li, Xianju Li

The exponential surge in high-resolution remote sensing data faces a severe bottleneck in satellite-to-ground transmission. Limited downlink bandwidth forces the use of extreme high-ratio compression, which irreversibly destroys high-frequency structural details essential for downstream machine perception tasks like object detection. While current super-reso

Lanshan He, Haozhou Pang, Qi Gan, Xin Shen

Cutscenes are carefully choreographed cinematic sequences embedded in video games and interactive media, serving as the primary vehicle for narrative delivery, character development, and emotional engagement. Producing cutscenes is inherently complex: it demands seamless coordination across screenwriting, cinematography, character animation, voice acting, an

Zihao Xuan, Jia Chen, Yewen Li, Wei Xuan

In this paper, we propose FusionCIM, an operator-fusion-driven compute-in-memory (CIM) accelerator architecture for efficient and scalable LLM inference, with three key innovations: (1) a hybrid CIM pipeline architecture that maps QKT computation on inner-product-based CIM (IP-CIM) and PV aggregation on outer-product-based CIM (OP-CIM) for efficient matrix m

Fabian Dionys Schrag, Mehmet Ozgur Turkoglu, Konrad Schindler, Ralph Lukas Stoop

Domain adaptation (DA) addresses the challenge of transferring a machine learning model trained on a source domain to a target domain with a different data distribution. In this work, we study DA for the task of Rumex obtusifolius (Rumex) image classification. We train models on a published, ground vehicle-based dataset (source) and evaluate their performanc

Ali Karkehabadi, Jamshid Hassanpour, Houman Homayoun, Avesta Sasan

Gradient-based saliency methods are widely used to interpret deep neural networks, yet they often produce noisy and unstable explanations that poorly align with semantically meaningful input features. We argue that a fundamental cause of this behavior lies in the geometry of learned representations: correlated feature dimensions diffuse attribution gradients

Hao Li

Compositional text-to-image (T2I) generation requires a model to honour multiple sub-prompts that describe distinct image regions. Recent work shows that the \emph{starting noise} of a diffusion model carries significant semantic information: ``golden'' noise predicted from text can substantially raise prompt fidelity. We observe that this noise prediction i

Luc Ramsès Talla Waffo

We consider the two families of even polynomials $\Xi_n$ and $\Lambda_n$ studied in~\cite{TallaWaffo2026arxiv2602.16761}, together with the rescaled polynomials $\widetilde{\Xi}_n(x):=\Xi_n(\sqrt{x})$ and $\widetilde{\Lambda}_n(x):=\Lambda_n(\sqrt{x})$, $n\ge2$. Their zeros are real, simple, and contained in $(0,1)$. Writing them as $0<x^{(\Xi)}_{1,n}<\cdots

Li Ju, Junzhe Wang, Qi Zhang

Retrieval-Augmented Generation (RAG) models frequently produce answers grounded in parametric memory rather than the retrieved context, undermining the core promise of retrieval augmentation. A fundamental obstacle to fixing this unfaithfulness is the lack of training data that explicitly requires models to prefer context over internal knowledge. We introduc

Andy Crabtree

This is the authors response to commentaries on the original article H is for Human and How (Not) to Evaluate Qualitative Research in HCI, https://doi.org/10.1080/07370024.2025.2475743 Commentaries were provided by: Jeffrey Bardzell, https://doi.org/10.1080/07370024.2025.2612474 Alan Blackwell, https://doi.org/10.1080/07370024.2025.2591878 Paul Dourish, http

Roson Nongthombam, Amarendra K. Sarma

We investigate the role of continuous measurement and postselection in the dynamics and entanglement of a transmon-cavity-transmon coupled system. In the dispersive regime, characterized by a large detuning between the transmons and the cavity, the two transmons interact via virtual excitation of the cavity, giving rise to an effective transmon-transmon coup

Yuqing Cao, Shuo Zhu, Rongzhou Chen, Jingyan Chen

This work addresses the critical problem of tracking fast-moving objects through strongly scattering media in a low-light environment. Different from existing approaches that use frame-based cameras with fixed exposure times, which trade off signal-to-noise ratio for temporal resolution, we introduce computational neuromorphic tracking (CNT), a physics-infor

Deepshikha Gogoi, Parismita Gogoi, Yang Saring

Under-resourced languages remain underrepresented in quantitative rhythm research,particularly in systematic intra-branch analysis of acoustic differentiation within closely related linguistic groups.This study investigates acoustic differentiation within the Tani language subgroup by examining speech rhythm in Nyishi and Adi,two under-resourced Tani languag

Pinaki Roy, Tomasz Bulik

Einstein Telescope (ET) is a third-generation gravitational wave (GW) detector with tenfold better sensitivity compared to the advanced LIGO detectors. It will be capable of observing copious stellar mass binary black hole mergers up to a redshift of 10 which will make it especially useful for cosmography. We generate a mock gravitational wave event catalog

Sehyeon Oh, Yongin Kwon, Jemin Lee

FlashAttention improves efficiency through tiling, but its online softmax still relies on floating-point arithmetic for numerical stability, making full quantization difficult. We identify three main obstacles to integer-only FlashAttention: (1) scale explosion during tile-wise accumulation, (2) inefficient shift-based exponential operations on GPUs, and (3)

Mikhail I. Gomoyunov

We consider a path-dependent Hamilton--Jacobi equation with coinvariant derivatives over the space of continuous functions. We prove two uniqueness results for viscosity (generalized) solutions defined in terms of coinvariantly smooth test functionals and a dense family of compact subsets of the space of continuous functions. It is assumed that the Hamiltoni

Josue Obregon

Tree ensembles provide strong classification performance but usually behave as black-box models. Post-hoc interpretability techniques such as RuleCOSI+ extract a small ruleset that approximates the ensemble, but this simplification can leave the probabilities attached to the extracted rules unreliable. In particular, RuleCOSI+ assigns empirical class probabi

Ruizi Hu, Zongyuan Li, Zhancheng Yao, Yufei Wu

Scaling superconducting quantum processors is increasingly constrained by the wiring, heat load, and calibration overhead associated with delivering high-resolution analog signals from room temperature to qubits at millikelvin temperature. Here we demonstrate a superconducting digital-to-analog converter (DAC) integrated with high-coherence fluxonium qubits

Lakshmipriya K, Harssh Karn, Sutapa Roy

We investigate phase separation dynamics in a binary mixture subjected to a moving cooling source from which cold temperature fronts propagate radially outward into the mixture. The motion of the source introduces two distinct velocity scales: $v_s$ associated with the translation of the source, and $v$ related to the propagation of the cooling thermal front

Xiong Zhouzhi, Zimo Zeng, Yi Chen, Shuqi Xu

Deploying tiny object perception on edge platforms is challenging because practical systems must satisfy both strict compute budgets and end-to-end latency constraints. A common strategy is to first select a small number of candidate patches from a high-resolution image and then apply downstream processing only to the selected regions. However, existing dete

Wenxi Zhu, Wensheng Gan, Zhenlian Qi

Viruses represent the most abundant biological entities on Earth and play a pivotal role in microbial ecosystems, yet, as prominent human pathogens, they are closely linked to human morbidity and mortality. Accurate identification of viral sequences from viral genome sequences is therefore essential, but existing genome-based classification models that large

Yuwei Sun, Yuxuan Yao, Hui Li, Siyu Zhu

Diffusion models have achieved success in high-fidelity data synthesis, yet their capacity for more complex, structured reasoning like text following tasks remains constrained. While advances in language models have leveraged strategies such as latent reasoning and recursion to enhance text understanding capabilities, extending these to multimodal text-to-im

Youngjoon Jang, Chanhee Park, Hyeonseok Moon, Young-kyoung Ham

In recent years, the rapid proliferation of open-source large language models (LLMs) has spurred efforts to turn general-purpose models into domain specialists. However, many domain-specialized LLMs are developed using datasets and training protocols that are not aligned with the nuanced requirements of real-world applications. In the legal domain, where pre

Jianghang Lin, Haihua Yang, Deli Yu, Kai Wu

Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional data curation strategies that rely on coarse-grained partitioning by modality or department. Such fragmented approaches fail to capture the hierarchical and interconnected nature of clinical medical knowledge

Rui Wu, Hong Xie

Continuous causal discovery typically couples representation learning with structural optimization via non-convex acyclicity penalties, which subjects solvers to local optima and restricts scalability in high-dimensional regimes. We propose a decoupled paradigm that shifts the causal discovery bottleneck from non-convex optimization to statistical score esti

Yuling Li, Yubo Sun, Gennian Ge

In this paper, we investigate the problem of designing $(n, N; \mathcal{B})$-reconstruction codes for $N\in \{14,11,9,5\}$, where $\mathcal{B}$ is the single-deletion single-substitution ball function that maps a sequence to the set of all sequences obtainable via one deletion and one substitution. Such a code is defined by the requirement that the intersect

Pradeep J, Siddhardha Kedarisetty, Ashwini Ratnoo

This paper addresses the problem of traffic congestion management in fixed-wing unmanned aerial vehicle (UAV) corridors by further developing a recently introduced loiter-lane framework. A semi-cooperative guidance strategy is developed for inserting fixed-wing UAVs into a loiter lane with minimal disruption to the UAVs already operating within it, while ena

Pengyue Jia, Xiaobei Wang, Yingyi Zhang, Shuchang Liu

In modern recommender systems, list-wise reranking serves as a critical phase within the multi-stage pipeline, finalizing the exposed item sequence and directly impacting user satisfaction by modeling complex intra-list item dependencies. Existing methods typically formulate this task as selecting indices from the local input list. However, this approach suf

Liuzhuozheng Li, Zhiyuan Zhan, Shuhong Liu, Dengyang Jiang

Practically, training diffusion models typically requires explicit time conditioning to guide the network through the denoising sampling process. Especially in deterministic methods like DDIM, the absence of time conditioning leads to significant performance degradation. However, other deterministic sampling approaches, such as flow matching, can generate hi

Jonathan Holland

We give a metaplectic proof of Hilbert reciprocity, and hence of quadratic reciprocity, in which the local phase is the Kashiwara--Maslov phase of a triple of Lagrangians. In rank two the phase of the ordered triple $(L_\infty,L_a,L_0)$ is the one-dimensional Weil index $\gamma_v(a)$. The local Hilbert symbol appears as the defect of strict multiplicativity

Shantal Adajian, Fanghao Zhang, Zeyu Xiang, Tanay Tak

Crystalline defects are generally regarded as static phonon scatterers that irreversibly suppress thermal transport. Here we show that elastic strain can dynamically and reversibly reorganize dislocation ensembles and strongly modify heat conduction. Using in situ strain-dependent time-domain thermoreflectance measurements, we observe a reversible enhancemen

Rozhin Yousefjani, Shaikha Al-Naimi, Saif Al-Kuwari, Abolfazl Bayat

Discrete time crystals are non-equilibrium phases of matter in periodically driven systems, characterized by robust subharmonic oscillations and broken discrete time-translation symmetry. Their long-lived coherent dynamics and resilience to imperfections make them promising resources for quantum sensing. A disorder-free discrete-time crystal probe can provid

Xinwei Yue, Xinglun Tao, Jingjing Zhao, Xianfu Lei

Pinching antenna systems (PASS) have the advantages in the perspective of flexible antenna reconfiguration, line-of-sight (LoS) creation, and scalability features. To highlight the ascendancy of PASS, we survey the integration of PASS into non-orthogonal multiple access (NOMA) networks. The locations of nodes are randomly distributed within a circular covera

Kai Huang, Houdong Liang, Chongchong Yao, Xi Zhao

Visual Graph Query Interfaces (VQIs) empower non-programmers to query graph data by constructing visual queries intuitively. Devising efficient technologies in Graph Query Engines (GQEs) for interactive search and exploration has also been studied for years. However, these two vibrant scientific fields are traditionally independent of each other, causing a v

Ryohei Oishi, Kazunori Umeo, Takuya Aoyama, Takahiro Onimaru

We have investigated the piezomagnetic (PZM) effect of the rare-earth-based g-wave altermagnet TbPt6Al3 by magnetization measurements of single-crystalline samples under uniaxial stress sigma. The magnetization in magnetic field along the trigonal a axis increases linearly with sigma for T < TN, indicating the emergence of PZM effect, while the theoretically

A. Devaraj, S. Narendranath, Sreeja. S. Kartha, Netra S. Pillai

Sodium (Na) is a moderately volatile element in the lunar exosphere, released from the surface through thermal and non-thermal processes. We present a combined analysis of Chandrayaan-2 CLASS surface Na abundance, LADEE-UVS exospheric measurements, and DIVINER surface temperature data to investigate the coupling between surface and exospheric Na. Surface Na

Ashwin Ram, Aaditya Ramdas

This paper characterizes the best possible rate of growth of wealth in a Kelly betting game when repeatedly betting against a general i.i.d. null hypothesis $\mathscr{P}$, but the data are drawn i.i.d from an arbitrary alternative $Q$. We prove that it equals $\lim_{n \to \infty}n^{-1}\inf_{P \in (\mathscr P)^n)^{\circ\circ}} \mathrm{KL}(Q^n,P)$, where ${\ma

Jiahong Cai, Wensheng Gan, Philip S. Yu

Privacy-preserving utility mining (PPUM) aims to hide sensitive high-utility patterns while preserving the utility of the sanitized database. In practice, however, many datasets are associated with taxonomic information, which makes the identification and processing of generalized items more challenging. To address this, we investigate the cross-level privac

Rami Katz, Francesca Calà Campana, Giulia Giordano

We extend the Sakawa-Shindo algorithm to solve optimal control problems where the system dynamics involve an arbitrary number of discrete state delays. We prove that the algorithm guarantees termination in a finite number of steps, asymptotic first-order optimality of the generated control sequence and convergence of a subsequence to a control satisfying fir

Ankita Ghosh, Bhaswati Bhattacharyya, David L. Kaplan, David A. Smith

We present timing and orbital phase-resolved polarimetry of the millisecond pulsar (MSP) J2101$-$4802, having a spin period of 9.48~ms and dispersion measure (DM) $25.05\ \mathrm{pc\ cm^{-3}}$ discovered with the Giant Meter Radio Telescope (GMRT). From the phase-connected timing of this MSP spanning 3.7 years, we identify that PSR J2101-4802 is in a $\sim$1

Susanne Pfalzner, Furkan Dincer, Nienke van der Marel, Frank W. Wagner

The lifetime of protoplanetary discs is a critical factor for planet formation. Although the mean disc lifetime provides an estimate of the typical period available for planet formation, it does not capture the substantial variability in individual disc lifetimes or their dependence on host star mass. This study addresses these limitations by deriving the di

Minghang Zheng, Zihao Yin, Yi Yang, Yuxin Peng

Video Temporal Grounding (VTG), the task of localizing video segments from text queries, struggles in open-world settings due to limited dataset scale and semantic diversity, causing performance gaps between common and rare concepts. To overcome these limitations, we introduce OmniVTG, a new large-scale dataset for open-world VTG, coupled with a Self-Correct

Kien X. Nguyen, Ilya Safro

We study parameter transferability for the Quantum Approximate Optimization Algorithm (QAOA) across multiple combinatorial optimization problem classes from a parameter generation perspective. Specifically, a meta-optimizer is trained on one problem class and deployed on another during test time. Prior work employs a Long Short-Term Memory network to emulate

Guosheng Zhang, Linkai Liu, Keyao Wang, Haixiao Yue

Despite significant progress in Unified Multimodal Retrieval (UMR) powered by Large Multimodal Models (LMMs), existing embedding methods primarily focus on sample-level objectives via contrastive learning while overlooking the crucial subject-level semantics. This limitation hinders the model's ability to group semantically coherent subjects in complex multi

Tomáš Kocák, Rémi Munos, Branislav Kveton, Shipra Agrawal

Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs of arms are smooth on a graph. This framework is suitable for solving online learning problems that involve graphs, such as content-based recommendation. In this problem, each item we can recommend is a node of

Tomáš Kocák, Gergely Neu, Michal Valko

We consider adversarial multi-armed bandit problems where the learner is allowed to observe losses of a number of arms beside the arm that it actually chose. We study the case where all non-chosen arms reveal their loss with a fixed but unknown probability $r$, independently of each other and the action of the learner. We propose two algorithms that work for

Felix Forner, Cesare Carlo Mella, Christoph Nega, Lorenzo Tancredi

In this paper, we elaborate on the connection between leading singularities and canonical bases of Feynman integrals beyond polylogarithms. We start by discussing a notion of leading singularities in dimensional regularization, which can be generalized from the Riemann sphere to more complex geometries, and use it to demonstrate how selecting Feynman integra

Gergely Neu, Michal Valko

Most work on sequential learning assumes a fixed set of actions that are available all the time. However, in practice, actions can consist of picking subsets of readings from sensors that may break from time to time, road segments that can be blocked or goods that are out of stock. In this paper we study learning algorithms that are able to deal with stochas

Ninh Nguyen, Srinivas Akella

This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more unmanned aerial vehicles (UAVs) operating on an uncertain road network with potentially impassable edges. DUCPP is particularly relevant for scenarios such as disaster response, emergency supply transport, and

Jaan Janno

Inverse problem to determine simultaneously a general space- and time-dependent source and an initial state in a fractional diffusion equation from an {\it a posteriori} measurement of the normal derivative of the state on a portion of a boundary of the space domain is considered. Uniqueness for this problem is proved under the assumption that an order of a

Ryo Ishizuka, Shou Yoshikawa

We introduce (lim-)perfectoid splitting, which is a global variant of (lim-)perfectoid purity. Our main result establishes a correspondence between the lim-perfectoid splitting of projective schemes and the lim-perfectoid purity of their Gorenstein section rings. As an application, we construct a new supply of examples of lim-perfectoid pure rings that go be

Xueying Zeng, Youquan Xian, Sihao Liu, Xudong Mou

With the rapid evolution of Android applications, traditional machine learning-based detection models suffer from concept drift. Additionally, they are constrained by shallow features, lacking deep semantic understanding and interpretability of decisions. Although Large Language Models (LLMs) demonstrate remarkable semantic reasoning capabilities, directly p

Sota Arakawa, Takayuki Ushikubo, Ryosuke T. Tominaga

Chondrules are thought to have formed during transient flash-heating events in dust-enriched regions of the solar protoplanetary disk. Although laboratory studies have characterized the oxygen isotopic compositions of chondritic materials, quantitative interpretations based on simulations of disk formation and evolution remain limited. Here, we perform one-d

Connor W. Edwards, Jack D. Evans

Universal machine-learned interatomic potentials (uMLIPs) offer a promising approach to performing atomistic simulations at near-DFT accuracy with greatly reduced computational cost. Here, we present a new high-temperature benchmarking dataset of 40~ps ab~initio molecular dynamics (AIMD) trajectories simulated at 300, 1000, and 2000 K for nine zinc- and zirc

D. Gómez, B. López-Rodríguez, P. Salgado, P. Venegas

This paper analyzes a transient thermo-electromagnetic problem arising in the modeling of induction heating processes. Unlike previous studies that focused on steady-state scenarios, we consider a time-dependent thermal problem coupled with a nonlinear time-harmonic electromagnetic problem through temperature-dependent electrical conductivity and Joule effec

Manyi Guo, Jackson Morris, Alex Waugh, Albert Jinghui Yang

We compute the Atiyah Real $K$-theory of $C_2$-equivariant projective spaces and construct immersions of such spaces into multiples of the regular representation. These computations are made tractable by the recent geometric filtration of equivariant projective spaces due to Bhattacharya-Waugh-Zeng-Zou, together with a variant of the localized slice spectral