March 2025 arXiv papers — page 48

Susan Athey, Guido Imbens

This paper studies identification of average treatment effects in a panel data setting. It introduces a novel nonparametric factor model and proves identification of average treatment effects. The identification proof is based on the introduction of a consistent estimator. Underlying the proof is a result that there is a consistent estimator for the expected

Guillaume Quispe, Pierre Jouvelot, Gerard Memmi

In this paper, we describe the motivation, design, security properties, and a prototype implementation of NickPay, a new privacy-preserving yet auditable payment system built on top of the Ethereum blockchain platform. NickPay offers a strong level of privacy to participants and prevents successive payment transfers from being linked to their actual owners.

Jinzheng Li, Pran Nath, Raza M. Syed

The $\mathsf{SO(10)}$ model with a heavy Higgs spectrum consisting of $\mathsf{560+\overline{560}}$ and a light Higgs spectrum consisting of $2\mathsf{\times 10+320}$ plet representations of $\mathsf{SO(10)}$ is unique among $\mathsf{SO(10)}$ models.,It has the remarkable property that VEVs of $\mathsf{560}$ and $\mathsf{\overline{560}}$ can simultaneously r

Bernardita Ried Guachalla, Emmanuel Schaan, Boryana Hadzhiyska, Simone Ferraro

The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel'dovich effect (kSZ). We precisely measure this effect ($S/N\approx 10$) via velocity stacking with more than 800,000 spectroscopically confirmed luminous red galaxies (LRG) fro

Raimundas Vidunas, Arnas Vaicekauskas

A stochastic modification of Conway's cellular automaton "Life" is introduced here. Any cell could be perturbed spontaneously to the opposite (dead or alive) state at any iteration with a very low probability. This probability is assumed to be so low that perturbations affect most sensibly large patterns only in single cells after they settle into stable, os

Sungyeon Kim, Xinliang Zhu, Xiaofan Lin, Muhammet Bastan

Generative retrieval is an emerging approach in information retrieval that generates identifiers (IDs) of target data based on a query, providing an efficient alternative to traditional embedding-based retrieval methods. However, existing models are task-specific and fall short of embedding-based retrieval in performance. This paper proposes GENIUS, a univer

Ming Lei, Christophe Baehr

This paper establishes a unified framework integrating geometric flows with deep learning through three fundamental innovations. First, we propose a thermodynamically coupled Ricci flow that dynamically adapts parameter space geometry to loss landscape topology, formally proved to preserve isometric knowledge embedding (Theorem~\ref{thm:isometric}). Second,

Maarten V. de Hoop, Joonas Ilmavirta, Vitaly Katsnelson

We study the inverse spectral problem of jointly recovering a radially symmetric Riemannian metric and an additional coefficient from the Dirichlet spectrum of a perturbed Laplace-Beltrami operator on a bounded domain. Specifically, we consider the elliptic operator \[ L_{a,b} := e^{a-b} \nabla \cdot e^b \nabla \] on the unit ball $ B \subset \mathbb{R}^3 $,

Thomas L. Howarth, Terence Lehmann, Michael Gauding, Heinz Pitsch

This work discusses the role of diffusive enthalpy transport in relation to the origin of thermodiffusive instability and the resulting enhanced reactivity. Thermodiffusive effects in premixed hydrogen flames are typically explained and modelled via local equivalence ratio fluctuations. However, it is reiterated here that the imbalance between species and th

Spyros Basilakos, Andronikos Paliathanasis, Emmanuel N. Saridakis

We show that $f(Q)$ cosmology with a non-trivial connection, namely the Connection II of the literature, is dynamically equivalent with a quintom-like model. In particular, we show that the scalar field arising from the non-linear $f(Q)$ form, and the scalar field associated to the non-trivial connection, are combined to provide one canonical and one phantom

Can Kutlu Yüksel, Tomáš Vyhlídal, Jaroslav Bušek, Martin Hromčík

A fully analytical controller design is proposed to tackle a periodic control problem for stable linear systems with an input delay. Applying the internal model control scheme, the controller design reduces to designing a filter, which is done through the placement of poles and zeros. The zeros are placed to compensate for the harmonics and to achieve the de

Jan-Hendrik Arling, Alexander Burgman, Christina Dimitriadi, Ulrich Einhaus

This document, written by early career researchers (ECRs) in particle physics, aims to represent the perspectives of the European ECR community and serves as input for the 2025--2026 update of the European Strategy for Particle Physics. With input from a community-wide survey, it highlights key challenges faced by ECRs -- career stability, funding access and

Ryotatsu Yanagimoto, Benjamin A. Ash, Mandar M. Sohoni, Martin M. Stein

Nonlinear photonics uses coherent interactions between optical waves to engineer functionality that is not possible with purely linear optics. Traditionally, the function of a nonlinear-optical device is determined during design and fixed during fabrication. In this paper, we present a photonic device with highly programmable nonlinear functionality: an opti

Junzhi Ning, Dominic Marshall, Yijian Gao, Xiaodan Xing Yang Nan

Chest X-ray radiographs (CXRs) play a pivotal role in diagnosing and monitoring cardiopulmonary diseases. However, lung opacities in CXRs frequently obscure anatomical structures, impeding clear identification of lung borders and complicating the localization of pathology. This challenge significantly hampers segmentation accuracy and precise lesion identifi

Hilda Hadan, Sabrina A. Sgandurra, Leah Zhang-Kennedy, Lennart E. Nacke

Deceptive game designs that manipulate players are increasingly common in the gaming industry, but the impact on players is not well studied. While studies have revealed player frustration, there is a gap in understanding how cultural attributes affect the impact of deceptive design in games. This paper proposes a new research direction on the connection bet

Romolo Marotta, Francesco Quaglia

The current trend of technology has brought parallel machines equipped with multiple processors and multiple memory sockets to be available off-the-shelf -- or via renting through Iaas Clouds -- at reasonable costs. This has opened the possibility of natively supporting HPC in diffused realities, like industry or academic labs. At the same time, the Parallel

Alexander Ryabchenko, Idan Attias, Daniel M. Roy

We study online learning with oblivious losses and delays under a novel ``capacity constraint'' that limits how many past rounds can be tracked simultaneously for delayed feedback. Under ``clairvoyance'' (i.e., delay durations are revealed upfront each round) and/or ``preemptibility'' (i.e., we can stop tracking previously chosen round feedback), we establis

Xiaoyu Tian, Sitong Zhao, Haotian Wang, Shuaiting Chen

Recent advances in large language models (LLMs), such as OpenAI-o1 and DeepSeek-R1, have demonstrated the effectiveness of test-time scaling, where extended reasoning processes substantially enhance model performance. Despite this, current models are constrained by limitations in handling long texts and reinforcement learning (RL) training efficiency. To add

Shadi Ali Ahmad, Ahmed Almheiri, Simon Lin

There is ample evidence that the bulk dual of a $T\overline{T}$ deformed holographic CFT is a gravitational system with a finite area cutoff boundary. For states dual to black holes, the finite cutoff surface cannot be moved beyond the event horizon. We overcome this by considering an extension of the $T\overline{T}$ deformation with a boundary cosmological

Léa Ricard, Guy Desaulniers, Andrea Lodi, Louis-Martin Rousseau

The global transition to battery electric buses (EBs) presents an opportunity to reduce air and noise pollution in urban areas. However, the adoption of EBs introduces challenges related to limited driving range, extended charging times, and battery degradation. This study addresses these challenges by proposing a novel chance-constrained model for the elect

Pier Domenico Lamberti, Luigi Provenzano

We prove that the Steklov eigenfunctions on convex domains of $\mathbb R^n$ are $H^2$ regular by adapting a classical argument combined with the Rellich-Pohozaev identity.

Xinpeng Li, Shijian Deng, Bolin Lai, Weiguo Pian

In this paper, we introduce a new problem, Online-MMSI, where the model must perform multimodal social interaction understanding (MMSI) using only historical information. Given a recorded video and a multi-party dialogue, the AI assistant is required to immediately identify the speaker's referent, which is critical for real-world human-AI interaction. Withou

Carlos Plou, Cesar Borja, Ruben Martinez-Cantin, Ana C. Murillo

Finding information in hour-long videos is a challenging task even for top-performing Vision Language Models (VLMs), as encoding visual content quickly exceeds available context windows. To tackle this challenge, we present FALCONEye, a novel video agent based on a training-free, model-agnostic meta-architecture composed of a VLM and a Large Language Model (

Anthony Sulak, Olga Turanova

We study a porous medium equation that models tissue growth in a heterogeneous environment. We show that, in the incompressible limit, solutions converge to those of a weak form of a Hele-Shaw type free boundary problem. To obtain enough compactness to take the limit, we establish an $L^4$ bound on the gradient of the pressure and an estimate of Aronson-B\'{

Alex Glynn

The tendency of generative artificial intelligence (AI) systems to "hallucinate" false information is well-known; AI-generated citations to non-existent sources have made their way into the reference lists of peer-reviewed publications. Here, I propose a solution to this problem, taking inspiration from the Transparency and Openness Promotion (TOP) data shar

Aaron Serianni, Tyler Zhu, Olga Russakovsky, Vikram V. Ramaswamy

Computer vision models have been shown to exhibit and amplify biases across a wide array of datasets and tasks. Existing methods for quantifying bias in classification models primarily focus on dataset distribution and model performance on subgroups, overlooking the internal workings of a model. We introduce the Attention-IoU (Attention Intersection over Uni

Xianzhe Li, Li Wu

Let $ (\Theta,T,\mu) $ be an ergodic topological dynamical system. The fibered rotation number for cocycles in $ \Theta\times \mathrm{SL}(2,\mathbb{R}) $, acting on $ \Theta\times \mathbb{R}\mathbb{P}^1 $ is well-defined and has wide applications in the study of the spectral theory of Schr\"odinger operators. In this paper, we will provide its natural genera

Zhao Fang, Liang-Chun Wu, Xuening Kong, Spencer Dean Stewart

This paper compares large language models (LLMs) and traditional natural language processing (NLP) tools for performing word segmentation, part-of-speech (POS) tagging, and named entity recognition (NER) on Chinese texts from 1900 to 1950. Historical Chinese documents pose challenges for text analysis due to their logographic script, the absence of natural w

Denis A. Leahy, Jakob Hansen, Andrew M. Hopkins

New far ultraviolet imaging of the galaxy NGC 205 is presented, which shows the emission is significantly offset ($\sim5^{\prime\prime}$ NW) from the optical and infrared centers of the galaxy. Spectral energy distribution (SED) modelling is applied to investigate the spatial dependence of the star formation history (SFH) of NGC 205, using data from far ultr

Alfred M. Grundland, Javier de Lucas, Bartosz M. Zawora

The aim of this paper is to perform a nonlinear stability analysis of the $(1+1)$-dimensional Nambu-Goto action gas models. The energy-Casimir method is employed to discuss in detail the Lyapunov stability of the Chaplygin and Born-Infeld models. Particular solutions are considered and their stability is studied in order to illustrate the application of our

Felix Egle, Christoph Englert, Margarete Mühlleitner, Michael Spannowsky

Interference effects in effective field theory (EFT) analyses can significantly distort sensitivity expectations, leaving subtle yet distinct signatures in the reconstruction of final states crucial for limit setting around Standard Model predictions. Using the specific example of four-fermion operators in top-quark pair production at the LHC, we provide a d

Kuldeep Ray, Jérémie Vigier, Perrine Usé, Sylvain Martin

The writing process of SOT-MRAMs is considered deterministic when additional symmetry-breaking factors, such as the application of an external magnetic field aligned with the current, are present. Notably, the write probability exhibits a unique behavior as a function of the current: it drops to zero at high currents or even oscillates with the current. This

Jun Zhou, Jiahao Li, Zunnan Xu, Hanhui Li

Currently, instruction-based image editing methods have made significant progress by leveraging the powerful cross-modal understanding capabilities of vision language models (VLMs). However, they still face challenges in three key areas: 1) complex scenarios; 2) semantic consistency; and 3) fine-grained editing. To address these issues, we propose FireEdit,

Sarah E. McCarthy, Ali Anwar, Daniel K. L. Oi, Loyd J. McKnight

The realization of quantum networks requires the development of robust low size, weight and power (SWaP) systems suitable for operation under harsh environments in remote and mobile nodes such as satellites. We present a source of polarization-entangled photon-pairs in a folded linear displacement interferometer based on spontaneous parametric down conversio

Vitaly Magerya, Levente Fekésházy

We present the analytic calculation of all master integrals for 3-, 4-, and 5-particle semi-inclusive cuts of four-loop massless propagators by means of differential equations. We fix the integration constants by reducing the semi-inclusive integrals to their fully inclusive counterparts with the Integration-By-Parts (IBP) method. We validate our results by

The ATLAS Collaboration

The production cross-section of high-mass $\tau$-lepton pairs is measured as a function of the dilepton visible invariant mass, using 140 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data recorded with the ATLAS detector at the Large Hadron Collider. The measurement agrees with the predictions of the Standard Model. A fit to the invariant mass dist

Adam Kłosiński, Roman Drachynskyi, Krzysztof Wohlfeld, Wojciech Brzezicki

We study magnetism in the electron-doped infinite-layer nickelate NdNiO$_2$. We perform an unrestricted Hartree-Fock calculation for a tight-binding model which contains both nickel and neodymium orbitals. We reproduce the self-doping effect, which is the escape of charge onto the neodymium bands. By fixing all free parameters to realistic values we find tha

Sanchayan Banerjee, Soumya Ranjan Padhi, Tapan Mishra

Mobility edges (MEs) constitute the energies separating the localized states from the extended ones in disordered systems. Going beyond this conventional definition, recent proposal suggests for an ME which separates the localized and multifractal states in certain quasiperiodic systems - dubbed as the anomalous mobility edges (AMEs). In this study, we propo

Franziskus Wiesnet

This article presents the concept of material interpretation as a method to transform classical proofs into constructive ones. Using the case study of maximal ideals in $\mathbb{Z}[X]$, it demonstrates how a classical implication $A \to B$ can be rephrased as a constructive disjunction $\neg A \vee B$, with $\neg A$ representing a strong form of negation. Th

Sara Cardona, Mathias Peirlinck, Behrooz Fereidoonnezhad

The fields of mechanobiology and biomechanics are expanding our understanding of the complex behavior of soft biological tissues across multiple scales. Given the intricate connection between tissue microstructure and its macroscale mechanical behavior, unraveling this mechanistic relationship remains an ongoing challenge. Reconstituted fiber networks serve

Henry Beuster, Lars-Michel Bretthauer, Gerd Scholl

This paper presents the integration of OPC UA as a communication protocol in a wireless sensor network and the associated companion specifications as a semantic template for an information model. The Cyber Physical Finite Element Sensor Network (CPFEN ) for Shape Measurements, a distributed wireless system, uses IO-Link Wireless for data transmission at the

Francesco Benedetti, Antonio Pellicani, Gianvito Pio, Michelangelo Ceci

Technological progress in the last few decades has granted an increasing number of people access to social media platforms such as Facebook, X (formerly Twitter), and Instagram. Consequently, the potential risks associated with these services have also risen due to users exploiting these services for malicious purposes. The platforms have tools capable of de

Thomas Willwacher

We discuss the cohomology of the bridgeless graph complex, that is, the subcomplex of the Kontsevich graph complex spanned by bridgeless graphs.

Wen Sun, Chuyi Tuo, Hong Yao

The ground-state properties of the single-band triangular lattice Hubbard model with hopping anisotropy and strong interactions remain elusive so far. Here we show that twisted diamond homobilayers with band extrema at $Y$ valley can realize weakly-coupled chains with quasi-1D band structure; applying displacement field generates interchain hopping, transfor

Athiya Deviyani, Fernando Diaz

Meta-evaluation of automatic evaluation metrics -- assessing evaluation metrics themselves -- is crucial for accurately benchmarking natural language processing systems and has implications for scientific inquiry, production model development, and policy enforcement. While existing approaches to metric meta-evaluation focus on general statements about the ab

Gabriel Malmer, Arvid Rolander, Emil Hillberg, Olof Samuelsson

The urgent need to address climate change prompts societies worldwide to adopt carbon neutral energy and electrification. To facilitate this, a range of technologies and policies will be needed. Alternatives to traditional power grid reinforcement, such as grid-enhancing technologies and system automation, are particularly attractive due to their potentially

Saleha Kiran, Farhan Hussain, Mian Ilyas Ahmad

Energy distribution networks are crucial for human societies and since they often cover large geographical areas, their physical analysis is challenging. Modeling and simulation can be used to analyze such complex energy networks. In this paper, we performed discretization on the underlying partial differential equations of a pipeline and identified the comp

Jiong-Jiong Liu, Zhan-Wei Liu, Xiu-Lei Ren, Yu Zhuge

The magnetic moments, magnetic form factors, and transition magnetic form factors of doubly charmed baryons are studied within heavy baryon chiral perturbation theory. We regulate the loop integrals using the finite-range regularization. The contributions of vector mesons are taken into account to investigate the dependence of form factors on the transferred

Gunjan Varshney, Anirudh Pradhan, Nasr Ahmed, Vansh Mittal

We study the anisotropic and homogeneous Bianchi type-V Universe with holographic dark energy (HDE) and interacting dark matter (DM). The solution for the field equations have been obtained for a certain form of the deceleration parameter. As for $\Lambda$CDM, we show that the coincidence problem disappears for a specific choice of the dark matter-holographi

Jiazhi Guan, Kaisiyuan Wang, Zhiliang Xu, Quanwei Yang

Despite the recent progress of audio-driven video generation, existing methods mostly focus on driving facial movements, leading to non-coherent head and body dynamics. Moving forward, it is desirable yet challenging to generate holistic human videos with both accurate lip-sync and delicate co-speech gestures w.r.t. given audio. In this work, we propose AudC

Yan Zhuang, Minheng Chen, Chao Cao, Tong Chen

Understanding the structural and functional organization of the human brain requires a detailed examination of cortical folding patterns, among which the three-hinge gyrus (3HG) has been identified as a key structural landmark. GyralNet, a network representation of cortical folding, models 3HGs as nodes and gyral crests as edges, highlighting their role as c

Love Pettersson, Anders S. Sørensen

To realize long-distance quantum communication, it is crucial to design quantum repeater architectures that can deal with transmission losses and operational errors. Code concatenation of photonic graph codes is a promising way to achieve this; however, existing concatenated codes that can correct both transmission losses and operational errors are extremely

Matthew Greenig, Haowen Zhao, Vladimir Radenkovic, Aubin Ramon

Designing antibody sequences to better resemble those observed in natural human repertoires is a key challenge in biologics development. We introduce IgCraft: a multi-purpose model for paired human antibody sequence generation, built on Bayesian Flow Networks. IgCraft presents one of the first unified generative modeling frameworks capable of addressing mult

Amir Nassibi, Christos Papavassiliou, Ildar Rakhmatulin, Danilo Mandic

Depression disorder is a serious health condition that has affected the lives of millions of people around the world. Diagnosis of depression is a challenging practice that relies heavily on subjective studies and, in most cases, suffers from late findings. Electroencephalography (EEG) biomarkers have been suggested and investigated in recent years as a pote

Pratibha Kumari, Afshin Bozorgpour, Daniel Reisenbüchler, Edgar Jost

White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant challenges due to domain shifts caused by variations in sample sources (e.g., blood or bone marrow) and differing imaging conditions across hospitals. Traditional deep learning models often suffer from catastrophic f

Yichao Yu, Sagnik Saha, Mikhail Shalaev, George Toh

The remote entanglement of two atomic quantum memories through photonic interactions is accompanied by atomic momentum recoil. When the interactions occur at different times, such as from the random emission over the lifetime of the atomic excited state, the difference in recoil timing can expose ``which-path'' information and ultimately lead to decoherence.

Jordan Madden, Lhamo Dorje, Xiaohua Li

Neural image compression (NIC) has emerged as a promising alternative to classical compression techniques, offering improved compression ratios. Despite its progress towards standardization and practical deployment, there has been minimal exploration into it's robustness and security. This study reveals an unexpected vulnerability in NIC - bitstream collisio

Yudong Yang, Jimin Zhuang, Guangzhi Sun, Changli Tang

Audio often serves as an auxiliary modality in video understanding tasks of audio-visual large language models (LLMs), merely assisting in the comprehension of visual information. However, a thorough understanding of videos significantly depends on auditory information, as audio offers critical context, emotional cues, and semantic meaning that visual data a

Xiaowen Dong

We construct more non-trivial examples for Toda brackets in unstable motivic homotopy theory via the first and second motivic Hopf maps.

Thomas Miconi, Kevin McKee, Yicong Zheng, Jed McCaleb

Intelligent organisms can solve truly novel problems which they have never encountered before, either in their lifetime or their evolution. An important component of this capacity is the ability to ``think'', that is, to mentally manipulate objects, concepts and behaviors in order to plan and evaluate possible solutions to novel problems, even without enviro

Lukas Hörmann, Wojciech G. Stark, Reinhard J. Maurer

Nanoscale design of surfaces and interfaces is essential for modern technologies like organic LEDs, batteries, fuel cells, superlubricating surfaces, and heterogeneous catalysis. However, these systems often exhibit complex surface reconstructions and polymorphism, with properties influenced by kinetic processes and dynamic behavior. A lack of accurate and s

Zhenyu Wu, Jiaoyan Chen, Norman W. Paton

Taxonomy inference for tabular data is a critical task of schema inference, aiming at discovering entity types (i.e., concepts) of the tables and building their hierarchy. It can play an important role in data management, data exploration, ontology learning, and many data-centric applications. Existing schema inference systems focus more on XML, JSON or RDF

Cristian Morasso, Giorgio Dolci, Ilaria Boscolo Galazzo, Sergey M. Plis

Given the broad adoption of artificial intelligence, it is essential to provide evidence that AI models are reliable, trustable, and fair. To this end, the emerging field of eXplainable AI develops techniques to probe such requirements, counterbalancing the hype pushing the pervasiveness of this technology. Among the many facets of this issue, this paper foc

Matteo Tuveri, Viviana Fanti

Introducing gravitational physics at high school provides educational means for bridging the gap between the image of science held by students and science itself. Natural language is fundamental in this learning. It engages students in constructing an understanding of a concept or a notion, establishing new relations between previous and new elements of know

Adriano Di Pietro, Alessandro Magni, Giovanni Carlotti, Gianfranco Durin

We study the effect of magnetic domain wall curvature on its dynamics in the creep regime in systems displaying Dzyaloshinskii-Moriya interaction (DMI). We first derive an extended creep model able to account for the finite curvature effect in magnetic bubble domain expansion. We then discuss the relative importance of this effect and discuss its dependence

Gen Li, Chen-Hao Hao, Xin Su, Yong-Qiang Wang

In this paper, we study Proca stars in asymptotically anti-de Sitter (AdS) Ellis wormholes. This study distinguishes itself from the analysis of the Proca stars in asymptotically flat spacetimes. In the AdS Ellis wormhole background, the mass of the wormhole solutions vanishes. Consequently, we employ numerical techniques to investigate in detail the impact

David Radke, Kyle Tilbury

Advanced analytics have transformed how sports teams operate, particularly in episodic sports like baseball. Their impact on continuous invasion sports, such as soccer and ice hockey, has been limited due to increased game complexity and restricted access to high-resolution game tracking data. In this demo, we present a method to collect and utilize simulate

Le Phuong Hoang, David Pesquera, Gerard N. Hinsley, Robert Carley

A fundamental understanding of the interplay between lattice structure, polarization and electrons is pivotal to the optical control of ferroelectrics. The interaction between light and matter enables the remote and wireless control of the ferroelectric polarization on the picosecond timescale, while inducing strain, i.e., lattice deformation. At equilibrium

Luis Irastorza-Valera, Luis Saucedo-Mora

Topology optimization (TO) is a well-established methodology for structural design under user-defined constraints, e.g. minimum volume and maximum stiffness. However, such methods have traditionally been applied to static, deterministic loading, in which modulus, position and direction are known and invariant. This is against the probabilistic load combinati

Jesús Guillera

We prove two fast formulas for the Hurwitz values $\zeta(2,a)$ and $\zeta(3,a)$ respectively with the help of the WZ method. In them $(a)_n$ denotes the rising factorial or Pochhammer's symbol defined by $(a)_0=1$ and $(a)_n=a(a+1)\cdots(a+n-1)$ for positive integers $n$. The Huwitz $\zeta$ function is defined by $\zeta(s,a)=\zeta(0,s,a)=\sum_{k=0}^{\infty}

Peyton Mullarkey, Sarah Marzen

Time delays increase the effective dimensionality of reservoirs, thus suggesting that time delays in reservoirs can enhance their performance, particularly their memory and prediction abilities. We find new closed-form expressions for memory and prediction functions of linear time-delayed reservoirs in terms of the power spectrum of the input and the reservo

Hongyu Gao, Minghe Zhu, Jia Ma, Marc Honecker

Accurately measuring liquid dynamic viscosity across a wide range of shear rates, from the linear-response to shear-thinning regimes, presents significant experimental challenges due to limitations in resolving high shear rates and controlling thermal effects. In this study, we integrated machine learning (ML) with non-equilibrium molecular dynamics (NEMD) s

Manjushree Aithal, Rosaura G. VidalMata, Manikandtan Kartha, Gong Chen

Low-light image enhancement is crucial for a myriad of applications, from night vision and surveillance, to autonomous driving. However, due to the inherent limitations that come in hand with capturing images in low-illumination environments, the task of enhancing such scenes still presents a formidable challenge. To advance research in this field, we introd

Thales F. Bittencourt, Rodrigo F. Sobreiro

We consider pure three-dimensional Maxwell-Chern-Simons electrodynamics in the static limit. We show that this theory can be mapped onto a two-dimensional gravitational model in the first-order formalism of Riemannian manifolds with Euclidean signature, coupled to a real scalar field naturally interpreted as a dilaton. In this framework, the Newtonian and co

Laura Kurek, Kevin Zheng, Eric Gilbert, Ceren Budak

Tenet Media, a U.S.-based, right-wing media company, hired six established podcasters to create content related to U.S. politics and culture during the 2024 U.S. presidential election cycle. After publishing content on YouTube and Rumble for nearly a year, Tenet Media was declared by the U.S. government to be funded entirely by Russia -- making it effectivel

Zhiyang Liu, Dong Yang, Minghao Zhang, Hanyu Sun

Despite that deep learning (DL) methods have presented tremendous potential in many medical image analysis tasks, the practical applications of medical DL models are limited due to the lack of enough data samples with manual annotations. By noting that the clinical radiology examinations are associated with radiology reports that describe the images, we prop

Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren

In this challenge, we explored text-based food hazard prediction with long tail distributed classes. The task was divided into two subtasks: (1) predicting whether a web text implies one of ten food-hazard categories and identifying the associated food category, and (2) providing a more fine-grained classification by assigning a specific label to both the ha

Mathieu Calvat, Chris Bean, Dhruv Anjaria, Haoren Wang

Encoding metal plasticity captured from high-resolution digital image correlation (DIC) can be leveraged to predict a wide range of monotonic and cyclic macroscopic properties of metallic materials. To capture the spatial heterogeneity of plasticity that develops in metals, latent space features describing plasticity of a small region are spatially mapped ac

Ruixi You, Hecheng Jia, Feng Xu

Synthetic Aperture Radar (SAR) imagery provides all-weather, all-day, and high-resolution imaging capabilities but its unique imaging mechanism makes interpretation heavily reliant on expert knowledge, limiting interpretability, especially in complex target tasks. Translating SAR images into optical images is a promising solution to enhance interpretation an

Johan Comparat, Andrea Merloni, Gabriele Ponti, Soumya Shreeram

This article presents the construction and validation of complete stellar mass-selected, volume-limited galaxy samples using the Legacy Survey (data release 10) galaxy catalogs, covering $\sim16,800$ deg$^2$ of extra-galactic sky, and extending to redshift $z<0.35$. We measure the correlation function of these galaxies with tiny statistical uncertainties at

Edwin Y. N. Tang, Stef Baas, Daniel Kaddaj, Lukas Pin

Response-adaptive randomization (RAR) can increase participant benefit in clinical trials, but also complicates statistical analysis. The burn-in period (a non-adaptive initial stage) is commonly used to mitigate this disadvantage, yet guidance on its optimal duration is scarce. To address this critical gap, this paper introduces an exact evaluation approach

Zhuoming Liu, Yiquan Li, Khoi Duc Nguyen, Yiwu Zhong

Pre-trained video large language models (Video LLMs) exhibit remarkable reasoning capabilities, yet adapting these models to new tasks involving additional modalities or data types (e.g., audio or 3D information) remains challenging. In this paper, we present PAVE, a flexible framework for adapting pre-trained Video LLMs to downstream tasks with side-channel

Vitaly Gnatyuk, Valeriia Koriukina, Ilya Levoshevich, Pavel Nurminskiy

With video games steadily increasing in complexity, automated generation of game content has found widespread interest. However, the task of 3D gaming map art creation remains underexplored to date due to its unique complexity and domain-specific challenges. While recent works have addressed related topics such as retro-style level generation and procedural

Stefan Steinerberger

Suppose $\left\{x_1, \dots, x_n\right\} \subset \mathbb{R}^2$ is a set of $n$ points in the plane with diameter $\leq 1$, meaning $\|x_i - x_j\| \leq 1$ for all $1 \leq i,j \leq n$. We show that if there are many `antipodes', these are pairs of points of with distance $\geq 1-\varepsilon$, then there are many neighbors, these are pairs of points that are dis

Jingdan Kang, Haoxin Yang, Yan Cai, Huaidong Zhang

Image generation technology has brought significant advancements across various fields but has also raised concerns about data misuse and potential rights infringements, particularly with respect to creating visual artworks. Current methods aimed at safeguarding artworks often employ adversarial attacks. However, these methods face challenges such as poor tr

Theerapat Tansuwannont, Yugo Takada, Keisuke Fujii

Quantum error-correcting codes with high encoding rate are good candidates for large-scale quantum computers as they use physical qubits more efficiently than codes of the same distance that encode only a few logical qubits. Some logical gate of a high-rate code can be fault-tolerantly implemented using transversal physical gates, but its logical operation m

Oleksandr Mokliachuk

At present, in the theory of stochastic process modeling a problem of assessment of reliability and accuracy of stochastic process model in $C(T)$ space wasn't studied for the case of implicit decomposition of process in the form of a series with independent terms. The goal is to study reliability and accuracy in $C(T)$ of models of processes from $Sub_\varp

Kechen Li, Jiaming Liu, Zhenyu Wu, Tianbo Ji

The predictive analysis of match outcomes and player momentum in professional tennis has long been a subject of scholarly debate. In this paper, we introduce a novel approach to game prediction by combining a multi-level fuzzy evaluation model with a CV-GRNN model. We first identify critical statistical indicators via Principal Component Analysis and then de

Jérémy Faupin, Marius Lemm, Israel Michael Sigal, Jingxuan Zhang

We consider a broad class of strongly interacting quantum lattice gases, including the Fermi-Hubbard and Bose-Hubbard models. We focus on macroscopic particle clusters of size $\theta N$, with $\theta\in(0,1)$ and $N$ the total particle number, and we study the quantum probability that such a cluster is transported across a distance $r$ within time $t$. Conv

Christian Liedtke, Matthew Satriano

We compute the equations of all rational double point singularities and we determine their types over perfect ground fields $k$ that arise as quotient singularities by finite linearly reductive subgroup schemes of $\textrm{SL}_{2,k}$.

Gemma Team, Aishwarya Kamath, Johan Ferret, Shreya Pathak

We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision understanding abilities, a wider coverage of languages and longer context - at least 128K tokens. We also change the architecture of the model to reduce the KV-cache memory that tends to

S. Zhou, A. Iovino, M. Longhetti, M. Scodeggio

We present a study of the evolution of star-forming galaxies within the so-called Wall structure at z$\sim$0.73 in the field of the COSMOS survey. We use a sample of star-forming galaxies from a comprehensive range of environments and across a wide stellar mass range and discuss the correlation between the environment and the galaxy's internal properties, in

Annalisa Buffa, Denise Grappein, Rafael Vázquez

An adaptive refinement strategy, based on an equilibrated flux a posteriori error estimator, is proposed in the context of defeaturing problems. Defeaturing consists of removing features from complex domains to simplify mesh generation and reduce the computational cost of simulations. It is a common procedure, for example, in computer aided design for simula

Kartik Thakral, Tamar Glaser, Tal Hassner, Mayank Vatsa

Existing unlearning algorithms in text-to-image generative models often fail to preserve the knowledge of semantically related concepts when removing specific target concepts: a challenge known as adjacency. To address this, we propose FADE (Fine grained Attenuation for Diffusion Erasure), introducing adjacency aware unlearning in diffusion models. FADE comp

Sanjeev Kumar, D. Thomas Seidl, Brian N. Granzow, Jin Yang

Accurate identification of material parameters is crucial for predictive modeling in computational mechanics. The two primary approaches in the experimental mechanics' community for calibration from full-field digital image correlation data are known as finite element model updating (FEMU) and the virtual fields method (VFM). In VFM, the objective function i

Martin Bauer, Stephen C. Preston, Justin Valletta

We consider the EPDiff equation on $\mathbb{R}^n$ with the integer-order homogeneous Sobolev inertia operator $A=(-\Delta)^k$. We prove that for arbitrary radial initial data and a sign condition on the initial momentum, the corresponding radial velocity solution has $C^1$ norm that blows up in finite time whenever $0\le k<n/2+1.$ Our approach is to use Lagr

Abhishek Ghosh, Ajay Nayak, Ashish Panwar, Arkaprava Basu

Machine learning (ML) workloads launch hundreds to thousands of short-running GPU kernels per iteration. With GPU compute throughput growing rapidly, CPU-side launch latency of kernels is emerging as a bottleneck. CUDA Graphs promise to address this by replaying a set of kernels with a single dispatch of the graph, removing per-kernel launch costs. However,

Vladan Stojnić, Yannis Kalantidis, Jiří Matas, Giorgos Tolias

We propose a training-free method for open-vocabulary semantic segmentation using Vision-and-Language Models (VLMs). Our approach enhances the initial per-patch predictions of VLMs through label propagation, which jointly optimizes predictions by incorporating patch-to-patch relationships. Since VLMs are primarily optimized for cross-modal alignment and not

Konyul Park, Yecheol Kim, Daehun Kim, Jun Won Choi

Modern autonomous driving perception systems utilize complementary multi-modal sensors, such as LiDAR and cameras. Although sensor fusion architectures enhance performance in challenging environments, they still suffer significant performance drops under severe sensor failures, such as LiDAR beam reduction, LiDAR drop, limited field of view, camera drop, and

FASER Collaboration, Roshan Mammen Abraham, Xiaocong Ai, Saul Alonso-Monsalve

The FASER experiment at CERN has opened a new window in collider neutrino physics by detecting TeV-energy neutrinos produced in the forward direction at the LHC. Building on this success, this document outlines the scientific case and design considerations for an upgraded FASER neutrino detector to operate during LHC Run 4 and beyond. The proposed detector w