October 2025 arXiv papers — page 166

Yanyuan Chen, Dexuan Xu, Yu Huang, Songkun Zhan

Currently, medical vision language models are widely used in medical vision question answering tasks. However, existing models are confronted with two issues: for input, the model only relies on text instructions and lacks direct understanding of visual clues in the image; for output, the model only gives text answers and lacks connection with key areas in t

Matheus J. T. Vargas

We present SLEAN (Simple Lightweight Ensemble Analysis Network), a deterministic framework for coordinating multiple LLM providers through text-based prompt orchestration. Unlike complex multi-agent systems requiring specialized infrastructure, SLEAN operates as a simple prompt bridge between LLMs using .txt templates, requiring no deep technical knowledge f

Shu Zhao, Tan Yu, Anbang Xu

Reasoning-augmented search agents, such as Search-R1, are trained to reason, search, and generate the final answer iteratively. Nevertheless, due to their limited capabilities in reasoning and search, their performance on multi-hop QA benchmarks remains far from satisfactory. To handle complex or compound queries, we train an LLM-based search agent with the

Meng Xi, Sihan Lv, Yechen Jin, Guanjie Cheng

Retrieval-Augmented Generation (RAG) systems based on Large Language Models (LLMs) have become a core technology for tasks such as question-answering (QA) and content generation. RAG poisoning is an attack method to induce LLMs to generate the attacker's expected text by injecting poisoned documents into the database of RAG systems. Existing research can be

David P. Huenemoerder, Sean J. Gunderson, Richard Ignace, Joy S. Nichols

We present 197 ks HETG and 95 ks NuSTAR spectra of the $\gamma\,$Cas-type object V750 Ara. The high-resolution X-ray spectra show that the target is similar to other objects of this class. Data are interpreted under the assumption that the X-rays come from an accreting white dwarf, and our analysis implies an accretion rate of about $3\times10^{-11}M_\odot\m

Pei Yu, Yanni Zeng, Maoan Han

In solving real-world problems, determining the codimension of Bogdanov-Takens (BT) and Bautin (generalized Hopf) bifurcations can be very challenging, even for simple two-dimensional dynamical systems. This difficulty becomes particularly evident when the number of system parameters exceeds the codimension of the bifurcations. Such challenges are closely li

Ryan F. Johnson, Eric J. Ching, Ethan S. Genter, Joshua E. Lipman

This paper introduces ChemGen, a software package that uses code generation to integrate multispecies thermodynamics and chemical kinetics into C+-based computational physics codes. ChemGen aims to make chemical kinetics more accessible in existing simulation frameworks and help bridge the gap between combustion modeling and computational physics. The packag

Jiahui Hong, Siqing Li, Muqing Jian, Luming Yang

Existing EEG recognition models suffer from poor cross-paradigm generalization due to dataset-specific constraints and individual variability. To overcome these limitations, we propose BITE (Bidirectional Time-Freq Pyramid Network), an end-to-end unified architecture featuring robust multistream synergy, pyramid time-frequency attention (PTFA), and bidirecti

Jianjin Wang, Runsong Zhao, Xiaoqian Liu, Yuan Ge

Current direct speech-to-speech translation methods predominantly employ speech tokens as intermediate representations. However, a single speech token is not dense in semantics, so we generally need multiple tokens to express a complete semantic unit. To address this limitation, we introduce multi-token prediction (MTP) loss into speech-to-unit translation (

Yixiu Xiao, Hongze Li

An effective upper bound is established for the least non-trivial integer solution to the system of cubic forms \[ \begin{cases} F = c_{1}x_1^3 + c_{2}x_2^3 + \cdots + c_{n}x_n^3 = 0, \\ G = d_{1}x_1^3 + d_{2}x_2^3 + \cdots + d_{n}x_n^3 = 0, \end{cases} \] under the "$M$-good" condition for $n \ge 16$, where $c_{1}, \dots, c_{n}$ and $d_{1}, \dots, d_{n}$ ar

Bach C. Le, Tung V. Dao, Binh T. Nguyen, Hong T. M. Chu

Wasserstein distributionally robust optimization (WDRO) provides a framework for adversarial robustness, yet existing methods based on global Lipschitz continuity or strong duality often yield loose upper bounds or require prohibitive computation. We address these limitations with a primal approach and adopt a notion of exact Lipschitz certificates to tighte

Yiran Bai, Feng Xiong, Xueheng Kuang

Classical computation of electronic properties in large-scale materials remains challenging. Quantum computation has the potential to offer advantages in memory footprint and computational scaling. However, general and practical quantum algorithms for simulating large-scale materials are still lacking. We propose and implement random-state quantum algorithms

Beining Ma, Jianyuan Qi, Xinghai Shen

Graphdiyne (GDY) is recognized as a compelling candidate for the fabrication of next-generation high-speed low-energy electronic devices due to its inherent p-type semiconductor characteristics. However, the development of GDY for applications in field-effect transistors (FETs), complementary metal-oxide-semiconductor (CMOS), and logic devices remains constr

Zhigang Cheng, Mingchao Sun, Yu Liu, Zengye Ge

Level of Detail (LoD) is a fundamental technique in real-time computer graphics for managing the rendering costs of complex scenes while preserving visual fidelity. Traditionally, LoD is implemented using discrete levels (DLoD), where multiple, distinct versions of a model are swapped out at different distances. This long-standing paradigm, however, suffers

Lishen Qu, Zhihao Liu, Shihao Zhou, Yaqi Luo

Flicker artifacts in short-exposure images are caused by the interplay between the row-wise exposure mechanism of rolling shutter cameras and the temporal intensity variations of alternating current (AC)-powered lighting. These artifacts typically appear as uneven brightness distribution across the image, forming noticeable dark bands. Beyond compromising im

Lishen Qu, Zhihao Liu, Jinshan Pan, Shihao Zhou

Lens flare occurs when shooting towards strong light sources, significantly degrading the visual quality of images. Due to the difficulty in capturing flare-corrupted and flare-free image pairs in the real world, existing datasets are typically synthesized in 2D by overlaying artificial flare templates onto background images. However, the lack of flare diver

Yimin Xiao, Yongle Zhang, Dayeon Ki, Calvin Bao

As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and adequacy errors impact bilingual and non-bilingual users' re

Uloma E. Nelson, Onyedikachi J. Okeke

This study examines recent enrollment trends and their socioeconomic drivers within New Mexico's public school districts, with a specific focus on those serving low-income communities. Utilizing a mixed-methods geospatial framework, the research integrates longitudinal enrollment data, district poverty metrics from the Small Area Income and Poverty Estimates

Mario Bukal, Igor Kukavica, Linfeng Li, Boris Muha

We address the fluid-structure interaction between a viscous incompressible fluid and an elastic plate forming its moving upper boundary in three dimensions. The fluid is described by the incompressible Navier-Stokes equations with a free upper boundary that evolves according to the motion of the structure, coupled via the velocity- and stress-matching condi

Virgile Troude, Didier Sornette

Heavy-tailed fluctuations and power law distributions pervade physics, biology, and the social sciences, with numerous mechanisms proposed for their emergence. Kesten processes, which are multiplicative stochastic recursions with additive noise or reinjection, provide a canonical explanation, where power law tails arise from transient supercritical excursion

Bitan Sarkar, Yuchao Jiang, Tian Ge, Yang Ni

Mendelian randomization (MR) is a pivotal tool in genetics, genomics, and epidemiology, leveraging genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. Traditional MR methods, while powerful, often rely on stringent assumptions such as the absence of feedback loops, which are frequently violated in complex

Moonzarin Reza, Lifan Wang

Precision cosmology requires robust, data-driven methods that can handle complex survey systematics without closed-form likelihoods. Simulation-Based Inference (SBI) meets this need through forward simulations that encode complex survey characteristics. Previous SBI analyses in supernova cosmology used SALT2 light-curve parameters as summary statistics; howe

Xuyang Sun, Hussein A. Ammar, Israfil Bahceci, Raviraj Adve

With the rapid deployment of 5G systems, remote interference (RI) caused by atmospheric ducting has emerged as an occasional, but critical challenge. This phenomenon occurs when the downlink (DL) signals from distant base stations (BSs) propagate over long distances through tropospheric ducting, severely disrupting uplink (UL) reception at local BSs. To addr

Jiaqi Wei, Xiang Zhang, Yuejin Yang, Wenxuan Huang

Deliberative tree search is a cornerstone of modern Large Language Model (LLM) research, driving the pivot from brute-force scaling toward algorithmic efficiency. This single paradigm unifies two critical frontiers: \textbf{Test-Time Scaling (TTS)}, which deploys on-demand computation to solve hard problems, and \textbf{Self-Improvement}, which uses search-g

Zongyu Guo, Zhaoyang Jia, Jiahao Li, Xiaoyi Zhang

Perceptual optimization is widely recognized as essential for neural compression, yet balancing the rate-distortion-perception tradeoff remains challenging. This difficulty is especially pronounced in video compression, where frame-wise quality fluctuations often cause perceptually optimized neural video codecs to suffer from flickering artifacts. In this pa

Zi-Yi Zhou, Long Ji, Ling-Da Kong, Sergey S. Tsygankov

We report the detection of mHz quasi-periodic oscillations (QPOs) in four NuSTAR observations of 4U 1626-67 during its recent spin-down episode. By using a novel method based on the Hilbert-Huang Transform (HHT), we present the first QPO-phase-resolved timing and spectral analysis of accreting X-ray pulsars in low mass X-ray binaries. Broadband QPO waveforms

Nges Brian Njungle, Eric Jahns, Luigi Mastromauro, Edwin P. Kayang

Machine learning has become a crucial part of our lives, with applications spanning nearly every aspect of our daily activities. However, using personal information in machine learning applications has sparked significant security and privacy concerns about user data. To address these challenges, different privacy-preserving machine learning (PPML) framework

Kartikeya Aneja, Nagender Aneja, Murat Kantarcioglu

Software systems can be represented as graphs, capturing dependencies among functions and processes. An interesting aspect of software systems is that they can be represented as different types of graphs, depending on the extraction goals and priorities. For example, function calls within the software can be captured to create function call graphs, which hig

Ethan Thompson, Ali Sadeghi Jahromi, AbdelRahman Abdou

The use of Content Delivery Networks (CDNs) has significantly increased over the past decade, with approximately 55 million websites currently relying on CDN services. Emerging solutions, such as Delegated Credentials (RFC 9345), lack fine-grained definitions of many critical aspects of delegation, such as the length of delegation chains, revocation mechanis

Cesar Mello, Fernando Medina da Cunha

Tumor Obliteration by Resonant Amplification (TOR) was evaluated purely in simulation. Forward models in COMSOL, ANSYS, and ABAQUS used the same small-strain rheology, nonthermal/noncavitational limits, and an emulated closed loop (phase-locked actuation plus contrast/safety gating). Over >= 200 Monte Carlo runs per setup, TOR produced per-focus extinction i

Fan Zuo, Donglin Zhou, Jingqin Gao, Kaan Ozbay

Accurate, scalable traffic monitoring is critical for real-time and long-term transportation management, particularly during disruptions such as natural disasters, large construction projects, or major policy changes like New York City's first-in-the-nation congestion pricing program. However, widespread sensor deployment remains limited due to high installa

Jingyuan Sun, Hongyu Ji, Zihan Qu, Chaoran Wang

Hybrid locomotion of wheeled-legged robots has recently attracted increasing attention due to their advantages of combining the agility of legged locomotion and the efficiency of wheeled motion. But along with expanded performance, the whole-body control of wheeled-legged robots remains challenging for hybrid locomotion. In this paper, we present ATRos, a re

Yao Gao, Lei Sun, Shaohua Gao, Qi Jiang

The highly non-convex optimization landscape of modern lens design necessitates extensive human expertise, resulting in inefficiency and constrained design diversity. While automated methods are desirable, existing approaches remain limited to simple tasks or produce complex lenses with suboptimal image quality. Drawing inspiration from the synaptic pruning

Shi-Min Liang, Jian-Fu Zhang, Na-Na Gao, Nian-Yu Yi

Magnetic reconnection, often accompanied by turbulence interaction, is a ubiquitous phenomenon in astrophysical environments. However, the current understanding of the nature of turbulent magnetic reconnection remains insufficient. We investigate the statistical properties of reconnection turbulence in the framework of the self-driven reconnection. Using the

Frida Cantu, Salomon Ibarra, Arturo Gonzales, Jesus Barreda

Online sensing plays an important role in advancing modern manufacturing. The real-time sensor signals, which can be stored as high-resolution time series data, contain rich information about the operation status. One of its popular usages is online process monitoring, which can be achieved by effective anomaly detection from the sensor signals. However, mos

Chang Huang

We aim to prove a twisted version of the Osborne conjecture obtained by Hecht and Schmid in their 1983 Acta Mathematica paper. Bergeron and Clozel (2013) have considered a special case, and we generalize their method to our setting.

Fei Liu, Yang Ai, Ye-Xin Lu, Rui-Chen Zheng

In real-world scenarios, speech signals are inevitably corrupted by various types of interference, making speech enhancement (SE) a critical task for robust speech processing. However, most existing SE methods only handle a limited range of distortions, such as additive noise, reverberation, or band limitation, while the study of SE under multiple simultaneo

Rongyang Zhang, Yuqing Huang, Chengqiang Lu, Qimeng Wang

In real-world scenarios, providing user queries with visually enhanced responses can considerably benefit understanding and memory, underscoring the great value of interleaved image-text generation. Despite recent progress, like the visual autoregressive model that unifies text and image processing in a single transformer architecture, generating high-qualit

Ming Xi, Yuchong Zhang, Wenju Zhou, Famin Chen

Interplay between topology and magnetism induces various exotic quantum phenomena, with magnetic topological insulators (MTIs) serving as a prominent example due to their ability to host the quantum anomalous Hall effect (QAHE). However, the realization of QAHE at higher temperature approaching magnetic-transition-temperature remains a significant challenge,

Charlotte Smith-Perez, Aidan Hembruff, Els Peeters, Alexander G. G. M. Tielens

Polycyclic Aromatic Hydrocarbons (PAHs) constitute a significant fraction of the Universe's carbon budget, playing a key role in the cosmic carbon cycle and dominating the mid-infrared spectra of astrophysical environments in which they reside. Although PAHs are known to form in the circumstellar envelopes of post-AGB stars, their formation and evolution are

David Marasco, Paolo Marasco

Liquid nitrogen (LN2) is a long-time favorite for physics demonstrations, with a large repertoire of crowd-pleasing experiments that are cornerstones in outreach efforts. While R1 universities usually have a ready LN2 supply for their Physics, Chemistry, and Biology departments, K-12 and two-year college teachers often have to go to specialty suppliers to ob

Olivia Peiyu Wang, Tashvi Bansal, Ryan Bai, Emily M. Chui

Large Language Models (LLMs) suffer from critical reasoning gaps, including a tendency to hallucinate and poor accuracy in classifying logical fallacies. This limitation stems from their default System 1 processing, which is fast and intuitive, whereas reliable reasoning requires the deliberate, effortful System 2 approach (Kahneman, 2011; Li et al., 2025).

Mohammed Rafiq Namiq

In this paper, we study a class $\mathcal{C}$ of squarefree monomial ideals $I\subseteq R=\mathbb{K}[x_1,\dots,x_n]$ over a field $\mathbb{K}$, defined by the condition that $\dim R/I$ equals the maximum degree of the minimal generators of $I$ minus one. We show that the Stanley-Reisner ideal of every $i$-skeleton of a simplicial complex $\Delta$ belongs to

Stefan Pasch

Organizational efforts to utilize and operationalize artificial intelligence (AI) are often accompanied by substantial challenges, including scalability, maintenance, and coordination across teams. In response, the concept of Machine Learning Operations (MLOps) has emerged as a set of best practices that integrate software engineering principles with the uni

Kai E. Yang, Xudong Sun, Lucas A. Tarr, Jiayi Liu

Inferring the three-dimensional (3D) solar atmospheric structures from observations is a critical task for advancing our understanding of the magnetic fields and electric currents that drive solar activity. In this work, we introduce a novel, Physics-Informed Machine Learning method to reconstruct the 3D structure of the lower solar atmosphere based on the o

Easton R. Potokar, Taylor Pool, Daniel McGann, Michael Kaess

Light Detection and Ranging (LiDAR) sensors have become a de-facto sensor for many robot state estimation tasks, spurring development of many LiDAR Odometry (LO) methods in recent years. While some smoothing-based LO methods have been proposed, most require matching against multiple scans, resulting in sub-real-time performance. Due to this, most prior works

Shuo Zhao, Yongqiang Li, Yu Feng, Zhongsheng Hou

State aggregation aims to reduce the computational complexity of solving Markov Decision Processes (MDPs) while preserving the performance of the original system. A fundamental challenge lies in optimizing policies within the aggregated, or abstract, space such that the performance remains optimal in the ground MDP-a property referred to as {"}optimal policy

Chaoran Wang, Jingyuan Sun, Yanhui Zhang, Mingyu Zhang

We introduce a novel framework for automatic behavior tree (BT) construction in heterogeneous multi-robot systems, designed to address the challenges of adaptability and robustness in dynamic environments. Traditional robots are limited by fixed functional attributes and cannot efficiently reconfigure their strategies in response to task failures or environm

Qionghua Chu

I identify a new signaling channel in ESG research by empirically examining whether environmental, social, and governance (ESG) investing remains valuable as large institutional investors increasingly shift toward artificial intelligence (AI). Using winsorized ESG scores of S&P 500 firms from Yahoo Finance and controlling for market value of equity, I conduc

Yicheng He, Jingwen Yu, Guangcheng Chen, Hong Zhang

Maintaining an up-to-date map that accurately reflects recent changes in the environment is crucial, especially for robots that repeatedly traverse the same space. Failing to promptly update the changed regions can degrade map quality, resulting in poor localization, inefficient operations, and even lost robots. 3D Gaussian Splatting (3DGS) has recently seen

Nathan London, Mohammad R. Momeni

Feynman path integrals (PIs) have found many uses in approximate quantum dynamics methods that are able to efficiently calculate real-time quantum correlation functions. The PIs typically take the form of discrete imaginary time slices over a closed path, where the slices form the ``beads'' of a ring polymer (RP) necklace. Some methods, such as centroid mole

Bolong Hong, Lei Gao, Bingkai Zhang, Pengfei Nan

Amorphous solid-state electrolytes (SSEs) hold great promise for advancing the application of all-solid-state batteries (ASSBs), owing to their favorable ionic conductivity, structural tunability, and promising electrochemical performance. However, the absence of universal design principles for amorphous SSEs limits their development. By fundamentally re-eva

Jun Yin, Runcheng Cai, Shiliang Sun

Incomplete multi-view spectral clustering generalizes spectral clustering to multi-view data and simultaneously realizes the partition of multi-view data with missing views. For this category of method, K-means algorithm needs to be performed to generate the clustering result after the procedure of feature extraction. More importantly, the connectivity of sa

David Schmitz, Sadman Rahman, Anthony Kindness

In a previous study, the first author defines an inverse ambiguous function on a group $G$ to be a bijective function $f : G \to G$ satisfying the functional equation $f^{-1}(x) = f(x^{-1})$ for all $x \in G$. In this paper, we investigate the existence of continuous inverse ambiguous functions on classical Lie groups. In particular, we look at tori, ellipti

Sobin Alosious, Fiach Antaw, Matt Trau, Shern R. Tee

This study investigates the molecular-level mechanism of Alternating Current Electrohydrodynamic (AC-EHD) flow in nanopores under high-frequency conditions, using molecular dynamics simulations. A gold-NaCl system with symmetric and asymmetric electrode configurations is used to analyze the flow patterns under high-frequency AC potentials. Our findings revea

Israel Quiros

We show that if the masses of timelike fields are point-dependent quantities transforming under conformal transformations as $m\rightarrow\Omega^{-1}m$, so the energy density of perfect fluids transforms as $\rho\rightarrow\Omega^{-4}\rho$, form-invariance under Weyl transformations could be an actual symmetry of the gravitational interactions of matter. Tha

Elena Cáceres, Hare Krishna

Holographic Renormalization Group (RG) flows, described by Einstein gravity coupled to matter fields, have been thoroughly explored in the context of vacuum states. In this work, we shift the focus to thermal states. Using the Hamilton-Jacobi formalism for the coupled system, we derive the Ward identity associated with broken dilatation symmetry in thermal c

Zhizhong Huang, Nicolas de Saxcé

Given a flag variety $X$ defined over $\mathbb{Q}$ and a point $x$ in $X(\mathbb{R})$, we study approximations to $x$ by points $v$ in $X(\mathbb{Q})$, and show that, with an appropriate rescaling, those approximations equidistribute when $x$ is chosen randomly according to a Lebesgue measure on $X(\mathbb{R})$, or when $x$ is defined over $\mathbb{Q}$ and s

Cem Topcuoglu, Kaan Onarlioglu, Steven Sprecher, Engin Kirda

Contemporary web application architectures involve many layers of proxy services that process traffic. Due to the complexity of HTTP and vendor design decisions, these proxies sometimes process a given request in different ways. Attackers can exploit these processing discrepancies to launch damaging attacks including web cache poisoning and request smuggling

Xiao-Xiong Lin, Yuk-Hoi Yiu, Christian Leibold

Sequential firing of hippocampal place cells is often attributed to sequential sensory drive along a trajectory, and has also been attributed to planning and other cognitive functions. Here, we propose a mechanistic and parsimonious interpretation to complement these ideas: hippocampal sequences arise from intrinsic recurrent circuitry that propagates transi

Andrei A. Bulatov, Amirhossein Kazeminia

In the Constraint Satisfaction Problem (CSP for short) the goal is to decide the existence of a homomorphism from a given relational structure $G$ to a given relational structure $H$. If the structure $H$ is fixed and $G$ is the only input, the problem is denoted $CSP(H)$. In its counting version, $\#CSP(H)$, the task is to find the number of such homomorphi

Pan Wang, Yihao Hu, Xiaodong Bai, Jingchu Yang

Shatian pomelo detection in orchards is essential for yield estimation and lean production, but models tuned to ideal datasets often degrade in practice due to device-dependent tone shifts, illumination changes, large scale variation, and frequent occlusion. We introduce STP-AgriData, a multi-scenario dataset combining real-orchard imagery with curated web i

Mir Tafseer Nayeem, Sawsan Alqahtani, Md Tahmid Rahman Laskar, Tasnim Mohiuddin

Tokenization is a crucial but under-evaluated step in large language models (LLMs). The standard metric, fertility (the average number of tokens per word), captures compression efficiency but obscures how vocabularies are allocated across languages and domains. We analyze six widely used tokenizers across seven languages and two domains, finding stable ferti

Bing-Long Chen

In this paper, we derive a general regularity estimate for any 4-d spacetime, in terms of a priori bounds of the Ricci curvature and Lie derivative of the Lorentzian metric with respect to an arbitrary timelike vector field.

Pouya Shaeri, Ryan T. Woo, Yasaman Mohammadpour, Ariane Middel

Segmentation models achieve high accuracy on benchmarks but often fail in real-world domains by relying on spurious correlations instead of true object boundaries. We propose a human-in-the-loop interactive framework that enables interventional learning through targeted human corrections of segmentation outputs. Our approach treats human corrections as inter

Jaeyoon Choi, Mohammad Amin Samadi, Spencer JaQuay, Seehee Park

Research on Collaborative Problem Solving (CPS) has traditionally examined how humans rely on one another cognitively and socially to accomplish tasks together. With the rapid advancement of AI and large language models, however, a new question emerge: what happens to team dynamics when one of the "teammates" is not human? In this study, we investigate how t

Yutian Pang, Andrew Kendall, John-Paul Clarke

We investigate the potential impact of communication and human performance uncertainties on runway operations. Specifically, we consider these impacts within the context of an arrival scenario with two converging flows: a straight-in approach stream and a downwind stream merging into it. Both arrival stream are modeled using a modified Possion distribution t

Payel Bhattacharjee, Fengwei Tian, Meiyu Zhong, Guangyi Zhang

Edge-cloud speculative decoding (SD) accelerates inference by having a cloud-based large language model (LLM) that verifies draft tokens generated by a resource-constrained small language model (SLM) at the edge. A central bottleneck is the limited bandwidth of the edge-cloud link, which necessitates efficient compression of draft token distributions. We fir

Dinithi Jayasuriya, Divake Kumar, Sureshkumar Senthilkumar, Devashri Naik

Multi-objective optimization of analog circuits is hindered by high-dimensional parameter spaces, strong feedback couplings, and expensive transistor-level simulations. Evolutionary algorithms such as Non-dominated Sorting Genetic Algorithm II (NSGA-II) are widely used but treat all parameters equally, thereby wasting effort on variables with little impact o

Haytham Albousayri, Bechir Hamdaoui, Weng-Keen Wong, Nora Basha

Deep learning-based radio frequency fingerprinting (RFFP) has become an enabling physical-layer security technology, allowing device identification and authentication through received RF signals. This technology, however, faces significant challenges when it comes to adapting to domain variations, such as time, location, environment, receiver and channel. Fo

Adil Kabylda, Sergio Suárez-Dou, Nils Davoine, Florian N. Brünig

Recent advances in machine learning force fields (MLFFs) are revolutionizing molecular simulations by bridging the gap between quantum-mechanical (QM) accuracy and the computational efficiency of mechanistic potentials. However, the development of reliable MLFFs for biomolecular systems remains constrained by the scarcity of high-quality, chemically diverse

Youshuai Tan, Zishuo Ding, Jinfu Chen, Weiyi Shang

Errors in floating-point programs can lead to severe consequences, particularly in critical domains such as military, aerospace, and financial systems, making their repair a crucial research problem. In practice, some errors can be fixed using original-precision arithmetic, while others require high-precision computation. Developers often avoid addressing th

Shahbaz P Qadri Syed, He Bai

The empirical success of multi-agent reinforcement learning (MARL) has motivated the search for more efficient and scalable algorithms for large scale multi-agent systems. However, existing state-of-the-art algorithms do not fully exploit inter-agent coupling information to develop MARL algorithms. In this paper, we propose a systematic approach to leverage

Agampreet Aulakh, Nils D. Forkert, Matthias Wilms

The human brain undergoes dynamic, potentially pathology-driven, structural changes throughout a lifespan. Longitudinal Magnetic Resonance Imaging (MRI) and other neuroimaging data are valuable for characterizing trajectories of change associated with typical and atypical aging. However, the analysis of such data is highly challenging given their discrete na

Nilesh Jain, Elie Alhajjar

Underwater images play a crucial role in ocean research and marine environmental monitoring since they provide quality information about the ecosystem. However, the complex and remote nature of the environment results in poor image quality with issues such as low visibility, blurry textures, color distortion, and noise. In recent years, research in image enh

Saeed Pezeshki, Francois Barthelat

Entangled materials offer attractive structural features including tensile strength and large deformations, combined with infinite assembly and disassembly capabilities. How the geometry of individual particles governs entanglement, and in turn translates into macroscopic structural properties, provides a rich landscape in terms of mechanics and offers intri

Devansh Jain, Akash Pardeshi, Marco Frigo, Kaustubh Khulbe

Machine learning (ML) compilers play a key role in enabling high-performance implementations of ML workloads. These compilers use existing CPU and GPU backends to generate device-specific code. In recent years, many tensor accelerators (or AI accelerators) have been designed to further accelerate these workloads, with commercial products like AWS Trainium pu

Jake Van Clief, Constantine Kyritsopoulos

As Large Language Models increasingly mediate human communication and decision-making, understanding their value expression becomes critical for research across disciplines. This work presents the Ethics Engine, a modular Python pipeline that transforms psychometric assessment of LLMs from a technically complex endeavor into an accessible research tool. The

Weibin Cai, Reza Zafarani

Hate speech detection has been extensively studied, yet existing methods often overlook a real-world complexity: training labels are biased, and interpretations of what is considered hate vary across individuals with different cultural backgrounds. We first analyze these challenges, including data sparsity, cultural entanglement, and ambiguous labeling. To a

Chaitanya Karamchedu, Matthew Fox, Daniel Gottesman

Say a collection of $n$-qu$d$it gates $\Gamma$ is eventually universal if and only if there exists $N_0 \geq n$ such that for all $N \geq N_0$, one can approximate any $N$-qu$d$it unitary to arbitrary precision by a circuit over $\Gamma$. In this work, we improve the best known upper bound on the smallest $N_0$ with the above property. Our new bound is rough

Ching Chang, Ming-Chih Lo, Chiao-Tung Chan, Wen-Chih Peng

Real-world systems, ranging from industrial manufacturing to wearable healthcare, generate multivariate time series with hierarchical states ranging from coarse regimes to fine-grained events. Unlike zero- or few-shot segmentation, our setting uses dense state labels for model training. Sparse expert prompts provide inference-time corrections that resolve se

Dylan Hirsch, Jaime Fernández Fisac, Sylvia Herbert

Control barrier functions (CBFs) and Hamilton-Jacobi reachability (HJR) are central frameworks in safe control. Traditionally, these frameworks have been viewed as distinct, with the former focusing on optimally safe controller design and the latter providing sufficient conditions for safety. A previous work introduced the notion of a control barrier value f

Rajendra P. Gupta

The formation and evolution of galaxies and other astrophysical objects have become of great interest, especially since the launch of the James Webb Space Telescope in 2021. The mass, size, and density of objects in the early universe appear to be drastically different from those predicted by the standard cosmology - the $Λ$CDM model. This work shows that th

Dris Boubaa, Shaaban Khalil

The persistent deviations observed in semileptonic $B$ decays, in particular the lepton flavor universality ratios $\mathcal{R}(D^{(*)})$ and $\mathcal{R}(Λ_c)$, provide intriguing hints of physics beyond the Standard Model (SM). While current measurements remain limited by experimental uncertainties, their lower central values compared to SM expectations mo

Ze-Hua Zhang, Xiang Liu

In this work, we employ the quark-meson coupling model to investigate the mass shifts of $1P$-wave charmonia $χ_{cJ}(1P)$ ($J=0,1,2$) in cold symmetric nuclear matter by incorporating in-medium loop contributions to the $χ_{cJ}(1P)$ self-energy within the unquenched picture. At normal nuclear matter density, we obtain significant mass reductions of about 60

Pascal Isenring, Zaher Salman

The use of a Si pixel-based particle tracking scheme in muSR will, among others, allow measurements using a ten-fold increased stopped muons rate and samples ten times smaller than currently possible. Here we present simulation results to assess the effects of magnetic fields on two spectrometer configurations using a two-layered tracking scheme for the inco

Yingfeng Liu, Shijie Sun, Kaifeng Yu, Furen Deng

For an interferometric array, an image of the sky can be synthesized from interferometric visibilities, which are the cross-correlations of the received electric voltages of pairs of array elements. However, to search for transient targets such as the fast radio burst (FRB), it is more convenient to use the beam-forming technique, where the real-time voltage

Guifeng Li, Chaoyang Gong

Single-molecule detection enables direct observation of individual biomolecular events, providing mechanistic insights into biological processes and offering a powerful tool for disease diagnostics. However, the fundamental scale mismatch between optical wavelengths and molecules restricts the application of label-free techniques, leading to poor signal-to-n

Akilan Rajamani, Martin Beseda, Benjamin Lasorne, Bruno Senjean

Calculating excited states in chemistry is crucial to provide insight into photoinduced molecular behavior beyond the ground state, enabling innovations in spectroscopy, material sciences, and drug design. While several approaches have been developed to compute excited-state properties, finding the best ratio between computational cost and accuracy remains c

Martin Minchev, Maroussia Slavtchova-Bojkova

Following the pivotal work of Sevastyanov, who considered branching processes with homogeneous Poisson immigration, much has been done to understand the behaviour of such processes under different types of branching and immigration mechanisms. Recently, the case where the times of immigration are generated by a non-homogeneous Poisson process was considered

Lilit Martirosyan, Hans Wenzl

We determine the structure of the cyclotomic Hecke algebra corresponding to the complex reflection group $G_{25}$ also when it is not semisimple, as long as the generators are diagonalizable. In particular, we classify all simple representations of the braid group $B_4$ for which the generators are diagonalizable and satisfy a cubic polynomial. This will be

Kiran Kate, Yara Rizk, Poulami Ghosh, Ashu Gulati

Most realistic task automation problems require large language models (LLMs) to call tools, which often return complex JSON responses. These responses must be further processed to derive the information necessary for task completion. The ability of LLMs to do so is under-studied. In this paper, we study the tool response processing task and LLMs' abilities t

Cesareo A. Dominguez, Michael Koning, Luis A. Hernández

We investigate the impact of an external magnetic field on the vector charmonium system within the framework of Hilbert moment QCD sum rules. By incorporating magnetic corrections to the perturbative contributions of the QCD sector, we analyze the behavior of the hadronic parameters of the $J/\psi$ resonance -- namely, its continuum threshold $s_0$, decay co

Naman Agrawal

This study explores the design and application of Complex-Valued Convolutional Neural Networks (CVCNNs) in audio signal processing, with a focus on preserving and utilizing phase information often neglected in real-valued networks. We begin by presenting the foundational theoretical concepts of CVCNNs, including complex convolutions, pooling layers, Wirtinge

James Usevitch, Juan Augusto Paredes Salazar, Ankit Goel

Control barrier functions (CBFs) have seen widespread success in providing forward invariance and safety guarantees for dynamical control systems. A crucial limitation of discrete-time formulations is that CBFs that are nonconcave in their argument require the solution of nonconvex optimization problems to compute safety-preserving control inputs, which inhi

Renjie Li, Zihao Zhu, Xiaoyu Wang, Zhengzhong Tu

Portrait pictures, which typically feature both human subjects and natural backgrounds, are one of the most prevalent forms of photography on social media. Existing image super-resolution (ISR) techniques generally focus either on generic real-world images or strictly aligned facial images (i.e., face super-resolution). In practice, separate models are blend

Nikola Surjanovic, Alexandre Bouchard-Côté, Trevor Campbell

The performance of gradient-based optimization methods, such as standard gradient descent (GD), greatly depends on the choice of learning rate. However, it can require a non-trivial amount of user tuning effort to select an appropriate learning rate schedule. When such methods appear as inner loops of other algorithms, expecting the user to tune the learning

Lilit Martirosyan, Hans Wenzl

We prove that any non-symmetric ribbon tensor category $\mathcal{C}$ with the fusion rules of the compact group of type $G_2$ needs to be equivalent to the representation category of the corresponding Drinfeld-Jimbo quantum group for $q$ not a root of unity. We also prove an analogous result for the corresponding finite fusion tensor categories.

Soma Nagahama, Yuki Sato, Minoru Kawamura, Ilya Belopolski

The superconducting diode effect (SDE) is characterized by the nonreciprocity of Cooper-pair motion with respect to current direction. In three-dimensional (3D) materials, SDE results in a critical current that varies with direction, making the effect distinctly observable: the material exhibits superconductivity in one direction while behaving as a resistiv

Adalyn Gibson, Meredith A. MacGregor, Ward S. Howard, Ann Marie Cody

We present the TESS discovery of only the second system of transiting exocomets with a sufficient number of events to measure the size distribution in the RZ Psc system, enabling comparisons with the $\beta$ Pictoris and Solar System size distributions. Twenty-four transits with absorption depths (AD) of 1--20\% were observed across three TESS sectors of the