December 2024 arXiv papers — page 113

Tony Chang, Kiarie Ndegwa, Andreas Gros, Vincent A. Landau

This paper explores the application of a novel multi-task vision transformer (ViT) model for the estimation of canopy height models (CHMs) using 4-band National Agriculture Imagery Program (NAIP) imagery across the western United States. We compare the effectiveness of this model in terms of accuracy and precision aggregated across ecoregions and class heigh

Aykut İşleyen, Abhidnya Kadu, René van de Molengraft, Ömür Arslan

Safe, smooth, and optimal motion planning for nonholonomically constrained mobile robots and autonomous vehicles is essential for achieving reliable, seamless, and efficient autonomy in logistics, mobility, and service industries. In many such application settings, nonholonomic robots, like unicycles with restricted motion, require precise planning and contr

Lai Wei, Jiahua Ma, Yibo Hu, Ruimao Zhang

In dynamic environments, robots often encounter constrained movement trajectories when manipulating objects with specific properties, such as doors. Therefore, applying the appropriate force is crucial to prevent damage to both the robots and the objects. However, current vision-guided robot state generation methods often falter in this regard, as they lack

Yuan Sun, Zhao Zhang, Jorge Ortiz

In current multimodal tasks, models typically freeze the encoder and decoder while adapting intermediate layers to task-specific goals, such as region captioning. Region-level visual understanding presents significant challenges for large-scale vision-language models. While limited spatial awareness is a known issue, coarse-grained pretraining, in particular

Yuchen Ren, Wenwei Han, Qianyuan Zhang, Yining Tang

As key elements within the central dogma, DNA, RNA, and proteins play crucial roles in maintaining life by guaranteeing accurate genetic expression and implementation. Although research on these molecules has profoundly impacted fields like medicine, agriculture, and industry, the diversity of machine learning approaches-from traditional statistical methods

Jooseop Lee, Greta L. Chappell, Ryan E. Baumbach, Ayman H. Said

Using high-energy-resolution inelastic x-ray scattering, we observe anomalous softening and damping of the transverse acoustic phonon in UPt$_2$Si$_2$ as the system is cooled towards the charge density wave (CDW) transition temperature, T$_{\rm{CDW}}$. The phonon exhibits a marked Kohn-type anomaly around the CDW wave vector, Q$_{\rm{CDW}}$, and becomes over

Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao

Although large vision-language-action (VLA) models pretrained on extensive robot datasets offer promising generalist policies for robotic learning, they still struggle with spatial-temporal dynamics in interactive robotics, making them less effective in handling complex tasks, such as manipulation. In this work, we introduce visual trace prompting, a simple

Gabriel Cuomo, Fanny Eustachon, Eren Firat, Brian Henning

We provide a comprehensive picture for the formulation of the perfect fluid in the modern effective field theory formalism at both the classical and quantum level. Due to the necessity of decomposing the hydrodynamical variables $(\rho, p, u^\mu)$ into other internal degrees of freedom, the procedure is inherently not unique. We discuss and compare the diffe

Garima Rajguru, Ritaban Chatterjee

We study the variability of the thermal (accretion disc) and non-thermal (jet) emission of thirteen flat spectrum radio quasars in the optical and near infrared (OIR) regime using light curves spanning years with an average sampling of three observations per week. We fit a combination of a blackbody and a power-law function to the OIR data, in the blazar res

Zhiqi Ge, Juncheng Li, Xinglei Pang, Minghe Gao

Digital agents are increasingly employed to automate tasks in interactive digital environments such as web pages, software applications, and operating systems. While text-based agents built on Large Language Models (LLMs) often require frequent updates due to platform-specific APIs, visual agents leveraging Multimodal Large Language Models (MLLMs) offer enha

Julia Huuk, Abheek Dhingra, Eirini Ntoutsi, Berend Denkena

This paper presents an innovative method for predicting shape errors in 5-axis machining using graph neural networks. The graph structure is defined with nodes representing workpiece surface points and edges denoting the neighboring relationships. The dataset encompasses data from a material removal simulation, process data, and post-machining quality inform

Marina Delianidi, Konstantinos Diamantaras, Ioannis Moras, Antonis Sidiropoulos

This study introduces DK-PRACTICE (Dynamic Knowledge Prediction and Educational Content Recommendation System), an intelligent online platform that leverages machine learning to provide personalized learning recommendations based on student knowledge state. Students participate in a short, adaptive assessment using the question-and-answer method regarding ke

Wangkai Li, Rui Sun, Huayu Mai, Tianzhu Zhang

Semantic segmentation suffers from significant performance degradation when the trained network is applied to a different domain. To address this issue, unsupervised domain adaptation (UDA) has been extensively studied. Despite the effectiveness of selftraining techniques in UDA, they still overlook the explicit modeling of domain-shared feature extraction.

Hanzhou Liu, Chengkai Liu, Jiacong Xu, Peng Jiang

Deep state-space models (SSMs), like recent Mamba architectures, are emerging as a promising alternative to CNN and Transformer networks. Existing Mamba-based restoration methods process visual data by leveraging a flatten-and-scan strategy that converts image patches into a 1D sequence before scanning. However, this scanning paradigm ignores local pixel dep

Divya Shanmugam, Monica Agrawal, Rajiv Movva, Irene Y. Chen

The increased capabilities of generative AI have dramatically expanded its possible use cases in medicine. We provide a comprehensive overview of generative AI use cases for clinicians, patients, clinical trial organizers, researchers, and trainees. We then discuss the many challenges -- including maintaining privacy and security, improving transparency and

Eran Alouf, Antongiulio Fornasiero, Itay Kaplan

Suppose $N$ is elementarily equivalent to an archimedean ordered abelian group $(G,+,<)$ with small quotients (for all $1 \leq n < \omega$, $[G: nG]$ is finite). Then every stable reduct of $N$ which expands $(G,+)$ (equivalently every reduct that does not add new unary definable sets) is interdefinable with $(G,+)$. This extends previous results on stable r

Joseph Brennan, Susan Morey

When $I$ is the edge ideal of a graph $G$, we use combinatorial properities, particularly Property $P$ on connectivity of neighbors of an edge, to classify when a binomial sum of vertices is a regular element on $R/I(G)$. Under a mild separability assumption, we identify when such elements can be combined to form a regular sequence. Using these regular seque

A. S. Rusetskii, M. A. Negodaev, A. V. Oginov, V. A. Ryabov K. V. Shpakov

The energy spectrum of alpha particles from the nuclear reaction p + $^{11}$B $\rightarrow 3\alpha$ was studied using the beam of the injector of the proton synchrotron of the Prometheus proton therapy complex. The reaction products (alpha particles) were recorded using a CR-39 track detector. The detectors were calibrated using a $^{241}$Am radioactive sour

C. Senthil Kumar, R. Radha

In this paper, we analyse the (3+1) dimensional Bogoyavlensky - Konopelchenko equation. Using Painlev\'e Truncation approach, we have constructed solutions in terms of lower dimensional arbitrary functions of space and time. By suitably harnessing the arbitrary functions present in the solution, we have generated physically interesting solutions like periodi

Taj Sobral, John Kokkalis, Kay Romann, Jovan Nedić

This paper introduces a novel piston-driven apparatus to study the onset of cavitation in an impulsively accelerated liquid column as it compresses a closed gas volume. The experiment is monitored using high-speed videography and piezoelectric pressure transducers. Cavitation onset is observed in the liquid column as it undergoes an abrupt deceleration and i

Ha Luu, Mert Sisman, Ilhami Kovanlikaya, Tam Vu

Paramagnetic rim lesions (PRLs) are an emerging biomarker in multiple sclerosis (MS). Manual identification and rim segmentation of PRLs on quantitative susceptibility mapping (QSM) images are time-consuming. Deep learning-based QSM-RimNet can provide automated PRL detection, but this method does not provide rim segmentation for microglial density quantifica

Jie Min, Xinyi Song, Simin Zheng, Caleb B. King

The advent of artificial intelligence (AI) technologies has significantly changed many domains, including applied statistics. This review and vision paper explores the evolving role of applied statistics in the AI era, drawing from our experiences in engineering statistics. We begin by outlining the fundamental concepts and historical developments in applied

Randhir Singh, S. C. Patekar

Let $R$ be a ring (not necessarily a commutative ring) with identity. The clean graph $Cl(R)$ of a ring $R$ is a graph with vertices in the form of an ordered pair $(e,u)$, where $e$ is an idempotent and $u$ is a unit of ring $R$, respectively. Two distinct vertices $(e,u)$ and $(f,v)$ are adjacent in $Cl(R)$ if and only if $ef=fe=0$ or $uv=vu=1$. In this st

Leonor Ferrer, Francisco Martín, Miguel Sánchez

Obstructions to the existence of spacelike solitons depending on the growth of the mean curvature $H$ are proved for Lorentzian products $(M\times \mathbb{R}, \bar g=g_M-dt^2)$ with lowerly bounded curvature. The role of these bounds for both the completeness of the soliton $\Sigma$ and the applicability of the Omori-Yau principle for the drift Laplacian, is

Lutz Honvehlmann

Weighted reciprocity between two agents can be defined as the minimum of sending and receiving value in their bilateral relationship. In financial networks, such reciprocity characterizes the importance of individual banks as both liquidity absorber and provider, a feature typically attributed to large, intermediating dealer banks. In this paper we develop a

Emanuel Gallo, Thomas Mädler

Chaotic systems near black holes satisfy a universal bound, $\lambda \leq \kappa_H$ linking the Lyapunov coefficient $\lambda$ associated with unstable orbits to surface gravity $\kappa_H$ of the event horizon. A natural question is whether this bound is satisfied by unstable circular null geodesics in the vicinity of black holes. However, there are known ca

Enrique Otarola, Abner J. Salgado

We study the finite element approximation of problems involving the weighted $\Phi$-Laplacian, where $\Phi$ is an $N$-function and the weight belongs to the class $A_\Phi$. In particular, we consider a boundary value problem and an obstacle problem and derive error estimates in both cases. The analysis is based on the language of weighted Orlicz and weighted

Jagdeep Singh

For a matroid of rank $r$ and a non-negative integer $k$, an element is called $k$-loose if every circuit containing it has size greater than $r-k$. Zaslavsky and the author characterized all binary matroids with a $1$-loose element. In this paper, we establish a sharp linear bound on the size of a binary matroid, in terms of its rank, that contains a $k$-lo

Christian Guzman Ruiz, Matthew Dawson, Mario C. Acosta, Oriol Jorba

Atmospheric models demand a lot of computational power and solving the chemical processes is one of its most computationally intensive components. This work shows how to improve the computational performance of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH), a chemical weather prediction system developed by the Barcelona Supercompu

Ewoud Vaneeckhaute, Charlotte Bocquelet, Nathan Rougier, Shebha Anandhi Jegadeesan

A sensitivity increase of two orders of magnitude in proton (1H) and carbon (13C) spins via dynamic nuclear polarization (DNP) has been accomplished recently using a compact benchtop DNP polarizer operating at 1 T and 77 K. However the DNP mechanisms at play at such low magnetic field and high operating temperature are still not elucidated. A deeper understa

Gabriel I. Róis, José Tarciso S. S. Junior, Francisco S. N. Lobo, Manuel E. Rodrigues

This paper presents a systematic exploration of exact solutions for electrically charged wormholes, black holes, and black bounces within the hybrid metric-Palatini gravity (HMPG) framework. HMPG combines features of the metric and Palatini formulations of modified gravity, offering a powerful approach to address challenges in General Relativity, particularl

Yen-Hua Chen, Samuel Siegel, Daniel Baker, Ue-Li Pen

For many pulsars, the scattering structures responsible for scintillation are typically dominated by a single, thin screen along the line of sight, which persists for years or decades. In recent years, an increasing number of doubly-lensed events have been observed, where a secondary lens crosses the line of sight. This causes additional or distorted scintil

Anna Hasenfratz, Oliver Witzel

Lattice simulations have observed a novel strong coupling symmetric mass generation (SMG) phase for the SU(3) gauge system with $N_f=8$ fundamental fermions (represented by two sets of staggered fields) at very large renormalized coupling ($g^2_{GF} \gtrsim 25$). The results of Phys.Rev.D 106 (2022) 014513 suggest that the SMG phase is separated from the wea

Sicheng Zhu, Brandon Amos, Yuandong Tian, Chuan Guo

Many jailbreak attacks on large language models (LLMs) rely on a common objective: making the model respond with the prefix ``Sure, here is (harmful request)''. While straightforward, this objective has two limitations: limited control over model behaviors, yielding incomplete or unrealistic jailbroken responses, and a rigid format that hinders optimization.

Marat Agranovskiy, Konstantin Yakovlev

We study a path planning problem where the possible move actions are represented as a finite set of motion primitives aligned with the grid representation of the environment. That is, each primitive corresponds to a short kinodynamically-feasible motion of an agent and is represented as a sequence of the swept cells of a grid. Typically, heuristic search, i.

Yucheng Li, Huiqiang Jiang, Qianhui Wu, Xufang Luo

Long-context LLMs have enabled numerous downstream applications but also introduced significant challenges related to computational and memory efficiency. To address these challenges, optimizations for long-context inference have been developed, centered around the KV cache. However, existing benchmarks often evaluate in single-request, neglecting the full l

Rohan Mehta, Gideon Lee, Liang Jiang

Quantum random access memory (QRAM) is required for numerous quantum algorithms and network architectures. Previous work has shown that the ubiquitous bucket-brigade QRAM is highly resilient to arbitrary local incoherent noise channels occurring during the operation of the QRAM [PRX Quantum 2, 020311 (2021)], with query infidelities growing only polylogarith

Temitayo N. Adeyeye, Sidra Gibeault, Daniel P. Lathrop, Matthew W. Daniels

In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exponential. We sample this distribution using a temporal encoding scheme, in which information is encoded in the time at which the device switches between its resistance states. We t

Yaowei Li, Yuxuan Bian, Xuan Ju, Zhaoyang Zhang

Image editing has advanced significantly with the development of diffusion models using both inversion-based and instruction-based methods. However, current inversion-based approaches struggle with big modifications (e.g., adding or removing objects) due to the structured nature of inversion noise, which hinders substantial changes. Meanwhile, instruction-ba

Jyotismita Adhikary, Kevin J. Kelly, Felix Kling, Sebastian Trojanowski

With no concrete evidence for non-gravitational interactions of dark matter to date, it is natural to wonder whether dark matter couples predominantly to the Standard Model (SM)'s neutrinos. Neutrino interactions (and the possible existence of additional neutrinophilic mediators) are substantially less understood than those of other SM particles, yet this pi

Dilshod Azizov, Muhammad Arslan Manzoor, Velibor Bojkovic, Yingxu Wang

Deep learning has fundamentally reshaped the landscape of artificial intelligence over the past decade, enabling remarkable achievements across diverse domains. At the heart of these developments lie multi-layered neural network architectures that excel at automatic feature extraction, leading to significant improvements in machine learning tasks. To demysti

Maurice de Gosson

We present a probabilistic argument supporting the application of polar duality, as discussed in our previous work, to express the indeterminacy principle of quantum mechanics. Our approach combines the properties of the Mahler volume of a convex body with the Donoho--Stark uncertainty principle from harmonic analysis, which characterizes the concentration o

Yash Malviya, Karan Dhingra, Maneesh Singh

Regulatory documents are rich in nuanced terminology and specialized semantics. FRAG systems: Frozen retrieval-augmented generators utilizing pre-trained (or, frozen) components face consequent challenges with both retriever and answering performance. We present a system that adapts the retriever performance to the target domain using a multi-stage tuning (M

Federico Ruggeri, Gaetano Signorelli

A popular end-to-end architecture for selective rationalization is the select-then-predict pipeline, comprising a generator to extract highlights fed to a predictor. Such a cooperative system suffers from suboptimal equilibrium minima due to the dominance of one of the two modules, a phenomenon known as interlocking. While several contributions aimed at addr

Quentin Decant, Androniki Dimitriou, Laura Lopez Honorez, Bryan Zaldivar

The redshifted 21cm signal from Cosmic Dawn promises to open a new window into the early history of our universe and enable the probing of an unprecedented comoving survey volume. In this work, we revisit the imprint of Warm Dark Matter (WDM) on the 21cm signal power spectrum using an updated implementation of the WDM effect in the public code $\texttt{21cmF

Víctor Miralles, Yvonne Peters, Eleni Vryonidou, Joshua K. Winter

The observed baryon asymmetry of the Universe requires new sources of charge-parity ($\mathcal{CP}$) violation beyond those in the Standard Model. In this work, we investigate $\mathcal{CP}$-violating effects in the top-Higgs sector using the Standard Model Effective Field Theory (SMEFT) framework. Focusing on top-pair production in association with a Higgs

Yan Xia, Yunxiang Lu, Rui Song, Oussema Dhaouadi

We tackle the problem of localizing traffic cameras within a 3D reference map and propose a novel image-to-point cloud registration (I2P) method, TrafficLoc, in a coarse-tofine matching fashion. To overcome the lack of large-scale real-world intersection datasets, we first introduce Carla Intersection, a new simulated dataset with 75 urban and rural intersec

David M. Cerna

Error: Peer-review process exposed an error in Theorem 1 that, unfourtunately, is not repairable. Idempotent semigroups are always finite. See Green and Rees [1952], Siekmann and Szab\'o [1981] for details Anti-unification is a fundamental operation used for inductive inference. It is abstractly defined as a process deriving from a set of symbolic expression

Jay Bhambure, Rajeev Singh, Derek Teaney

We propose an algorithm for simulating stochastic relativistic fluid dynamics based on Metropolis updates. Each step of the algorithm begins with an update based on ideal hydrodynamics. This is followed by proposing random (spatial) momentum transfers between fluid cells, keeping the total energy fixed. These proposals are then accepted or rejected using the

Stéphane Bonhomme, Koen Jochmans, Martin Weidner

A popular approach to perform inference on a target parameter in the presence of nuisance parameters is to construct estimating equations that are orthogonal to the nuisance parameters, in the sense that their expected first derivative is zero. Such first-order orthogonalization allows the estimator of the nuisance parameters to converge at a slower-than-par

Jay Bhambure, Aleksas Mazeliauskas, Jean-Francois Paquet, Rajeev Singh

We conduct a numerical study of relativistic viscous fluid dynamics in the Density Frame for one-dimensional fluid flows. The Density Frame is a formulation of relativistic viscous hydrodynamics that is first-order in time, requires no auxiliary fields, and has no non-hydrodynamic modes. We compare our results to QCD kinetic theory simulations and find excel

Zhiyu Wu, Xiaokang Chen, Zizheng Pan, Xingchao Liu

We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL, through two key major upgrades. For the vision component, we incorporate a dynamic tiling vision encoding strategy designed for processing high-resolution images with different aspect ratios. For

Aleksandra Borówka

We discuss complex quaternionic manifolds, i.e., those that have holonomy $GL(n,\mathbb{H})U(1)$, which naturally arise via quaternionic Feix--Kaledin construction. We show that for a fixed c-projective class, any real analytic connection with type $(1,1)$ curvature induces, via quaternionic Feix--Kaledin construction, an $S^1$-invariant connection with holo

Talha Sultan, Eric Brandt, Khadijeh Masumnia-Bisheh, Simone Riccardo

Active imaging systems sample the Transient Light Transport Matrix (TLTM) for a scene by sequentially illuminating various positions in this scene using a controllable light source, and then measuring the resulting spatiotemporal light transport with time of flight (ToF) sensors. Time-resolved Non-line-of-sight (NLOS) imaging employs an active imaging system

Amodio Carleo, Delphine Perrodin, Andrea Possenti

The pulsar timing technique, which compares the observed arrival times of electromagnetic radiation from a pulsar with the predicted arrival times derived from a theoretical model of the pulsar system, is used in pulsar astronomy to infer a multitude of physical information and to constrain possible corrections to General Relativity (GR). The propagation del

Anakin Trotter

Accurately predicting sports viewership is crucial for optimizing ad sales and revenue forecasting. Social media platforms, such as Reddit, provide a wealth of user-generated content that reflects audience engagement and interest. In this study, we propose a regression-based approach to predict sports viewership using social media metrics, including post cou

Oscar Scholin, Theresa W. Lynn

Entanglement of qudit pairs, with single particle Hilbert space dimension $d$, has important potential for quantum information processing, with applications in cryptography, algorithms, and error correction. For a pair of qudits of arbitrary even dimension $d$, we introduce a generalized Bell basis with definite symmetry under exchange of internal states bet

Simon Benhaïem

Statistical schools-such as Bayesianism and Frequentism-are often presented as competing frameworks, each claiming technical rigour and superiority. Frequentism emphasizes objective inferences through repeated sampling, while Bayesianism incorporates prior beliefs and updates them with new evidence. Despite their strengths, neither school proves universally

José A. Carrillo, Jakub Skrzeczkowski, Jethro Warnett

The Stein Variational Gradient Descent method is a variational inference method in statistics that has recently received a lot of attention. The method provides a deterministic approximation of the target distribution, by introducing a nonlocal interaction with a kernel. Despite the significant interest, the exponential rate of convergence for the continuous

P. L. Krapivsky

We investigate the hiring problem where a sequence of applicants is sequentially interviewed, and a decision on whether to hire an applicant is immediately made based on the applicant's score. For the maximal and average improvement strategies, the decision depends on the applicant's score and the scores of all employees, i.e., previous successful applicants

Manuel Dahnert, Angela Dai, Norman Müller, Matthias Nießner

We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simultaneously denoise the 3D poses and geometries of all objects within the scene. Motivated by the ill-posed nature of the task and to obtain consistent scene reconstruction results,

Gemma Crowe

In this paper we solve the conjugacy problem for several classes of virtual right-angled Artin groups, using algebraic and geometric techniques. We show that virtual RAAGs of the form $A_{\phi} = A_{\Gamma} \rtimes_{\phi} \mathbb{Z}/m\mathbb{Z}$ are $\mathrm{CAT}(0)$ when $\phi \in \mathrm{Aut}(A_{\Gamma})$ is length-preserving, and so have solvable conjugac

Yu-Jhe Li, Xinyang Zhang, Kun Wan, Lantao Yu

We tackle the challenge of open-vocabulary segmentation, where we need to identify objects from a wide range of categories in different environments, using text prompts as our input. To overcome this challenge, existing methods often use multi-modal models like CLIP, which combine image and text features in a shared embedding space to bridge the gap between

Murray Shanahan

My paper "Talking About Large Language Models" has more than once been interpreted as advocating a reductionist stance towards large language models. But the paper was not intended that way, and I do not endorse such positions. This short note situates the paper in the context of a larger philosophical project that is concerned with the (mis)use of words rat

Jerome Wiesemann, Fadri Grünenfelder, Ana Blázquez, Nino Walenta

While ideal quantum key distribution (QKD) systems are well-understood, practical implementations face various vulnerabilities, such as side-channel attacks resulting from device imperfections. Current security proofs for decoy-state BB84 protocols either assume uniform phase randomization of Alice's signals, which is compromised by practical limitations and

Max Bannach, Jai Grover, Markus Hecher

Hardware accelerators like quantum annealers or neuromorphic chips are capable of finding the ground state of a Hamiltonian. A promising route in utilizing these devices is via methods from automated reasoning: The problem at hand is first encoded into MaxSAT; then MaxSAT is reduced to Max2SAT; and finally, Max2SAT is translated into a Hamiltonian. It was ob

Ben Van Calster, Gary S. Collins, Andrew J. Vickers, Laure Wynants

A myriad of measures to illustrate performance of predictive artificial intelligence (AI) models have been proposed in the literature. Selecting appropriate performance measures is essential for predictive AI models that are developed to be used in medical practice, because poorly performing models may harm patients and lead to increased costs. We aim to ass

Georgiy Belyanin, Semyon Grigoriev, Rodion Suvorov

Two-way regular path queries (2-RPQs) allow one to use regular languages over edges and inverted edges in edge-labelled graph to constrain paths of interest. 2-RPQs are (partially) adopted in different real-world graph analysis systems and have become a part of the GQL ISO standard. However the performance of 2-RPQs on real-world graphs remains a bottleneck

Pyeongjae Park, Brenden R. Ortiz, Milo Sprague, Anup Pradhan Sakhya

Kagome metals with van Hove singularities near the Fermi level can host intriguing quantum phenomena such as chiral loop currents, electronic nematicity, and unconventional superconductivity. However, to our best knowledge, unconventional magnetic states driven by van Hove singularities--like spin-density waves--have not been observed experimentally in kagom

Jae-Weon Lee, Chueng-Ryong Ji

We derive the characteristic scales for physical quantities of dwarf galaxies, such as mass, size, acceleration, and angular momentum, within the self-interacting ultralight dark matter (ULDM) model. Due to the small mass of ULDM, even minor self-interactions can drastically alter these scales in the Thomas-Fermi limit. We suggest that these characteristic s

Julia Bernatska

An effective method of computing division polynomials in terms of Mumford coordinates is presented. As an example, division polynomials for $3$- and $4$-torsion divisors on a genus two curve are obtained explicitly in terms of Mumford coordinates, and $x$-, $y$-coordinates of the support of torsion divisors. As a result, $n$-torsion divisors on a given curve

Luke Hogg, Renée DiResta, Francis Fukuyama, Richard Reisman

Middleware, third-party software intermediaries between users and platforms, has been broached as a means to decentralize the power of social media platforms and enhance user agency. Middleware may enable a more user-centric and democratic approach to shaping digital experiences, offering a flexible architecture as an alternative to both centrally controlled

Mahmoud Reshadati, Manoochehr Shirzaei

Vertical land motion (VLM) observations obtained from Interferometric Synthetic Aperture Radar (InSAR) have transformed our understanding of crustal deformation processes over the past 3 decades. However, these observations are often related to a local reference frame, posing challenges for studies that require large-scale observations within a global refere

Sofie Goethals, Lauren Rhue

As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who the LLMs view as the most prominent figures across various fields, using prompts in ten different languages to explore the influence of linguistic diversity. Our findings reveal

Han-Xie Wang, Shuai A. Chen, Peng Ye

Fractonic superfluids are featured by the interplay of spontaneously broken charge symmetry and mobility constraints on single-particle kinematics due to the conservation of higher moments, such as dipoles, angular charge moments, and quadrupoles. Building on prior studies by Yuan \textit{et al.} [\href{https://doi.org/10.1103/PhysRevResearch.2.023267}{Phys.

J. R. Bermejo-Climent, R. Demina, A. Krolewski, E. Chaussidon

We use the angular cross-correlation between a luminous red galaxy (LRG) sample from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey data release DR9 and the $Planck$ cosmic microwave background (CMB) lensing maps to constrain the local primordial non-Gaussianity parameter, $f_{\rm NL}$, using the scale-dependent galaxy bias effect. The galaxy

Shantenu Jha, Yolanda Gil

This is a report of an NSF workshop titled "Envisioning National Resources for Artificial Intelligence Research" held in Alexandria, Virginia, in May 2024. The workshop aimed to identify initial challenges and opportunities for national resources for AI research (e.g., compute, data, models, etc.) and to facilitate planning for the envisioned National AI Res

A. Wilzewski, L. I. Huber, M. Door, J. Richter

Nonlinearities in King plots (KP) of isotope shifts (IS) can reveal the existence of beyond-Standard-Model (BSM) interactions that couple electrons and neutrons. However, it is crucial to distinguish higher-order Standard Model (SM) effects from BSM physics. We measure the IS of the transitions ${{}^{3}P_{0}~\rightarrow~{}^{3}P_{1}}$ in $\mathrm{Ca}^{14+}$ a

Sergey G. Bobkov, Friedrich Götze

An upper bound for the Kantorovich transport distance between probability measures on multidimensional Euclidean spaces is given in terms of transport distances between one dimensional projections. This quantifies the Cram\'er-Wold continuity theorem for the weak convergence of probability measures.

Xingrui Wang, Xin Li, Yaosi Hu, Hanxin Zhu

Text-driven Image to Video Generation (TI2V) aims to generate controllable video given the first frame and corresponding textual description. The primary challenges of this task lie in two parts: (i) how to identify the target objects and ensure the consistency between the movement trajectory and the textual description. (ii) how to improve the subjective qu

Federico Fabrizi, Piotr J. Cegielski, Saeed Goudarzi, Naho Kurahashi

Silicon photonic integrated circuits (PICs) require cost-effective laser sources that can be monolithically integrated. The low cost and low-temperature solution processability of metal halide perovskites (MHPs) make them attractive alternatives to established III-V compound semiconductors for on-chip laser sources in PICs. Cesium lead bromide (CsPbBr$_3$) p

Juan Mauricio Torres, Christian Ventura-Velázquez, Ivan Arellano-Melendez

We show that perfect revivals of Rabi oscillations are possible, under certain conditions, in the population inversion of a trapped ion. Based on this property, we find that Schr\"odinger cat states of the atomic motion are naturally generated by the unitary dynamics. Using a pair of symmetric and antisymmetric Schr\"odinger cat states of the motion, togethe

Rishabh Kabra, Drew A. Hudson, Sjoerd van Steenkiste, Joao Carreira

Image-to-3D models increasingly rely on hierarchical generation to disentangle geometry and texture. However, the design choices underlying these two-stage models--particularly the optimal choice of intermediate geometric representations--remain largely understudied. To investigate this, we introduce unPIC (undo-a-Picture), a modular framework for empirical

Guillaume Povéda, Ryma Boumazouza, Andreas Strahl, Mark Hall

In industrial contexts, effective workforce allocation is crucial for operational efficiency. This paper presents an ongoing project focused on developing a decision-making tool designed for workforce allocation, emphasising the explainability to enhance its trustworthiness. Our objective is to create a system that not only optimises the allocation of teams

Yanzhu Guo, Guokan Shang, Chloé Clavel

The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in some areas. However, this focus often neglects whether machine-generated language matches the human level of diversity, in terms of vocabulary choice, syntactic construction, and expr

Aron Vallinder, Edward Hughes

Large language models (LLMs) provide a compelling foundation for building generally-capable AI agents. These agents may soon be deployed at scale in the real world, representing the interests of individual humans (e.g., AI assistants) or groups of humans (e.g., AI-accelerated corporations). At present, relatively little is known about the dynamics of multipl

Marko Perestjuk, Rémi Armand, Miguel Gerardo Sandoval Campos, Lamine Ferhat

We report ring resonators on a silicon germanium on silicon platform operating in the mid-infrared wavelength range around 3.5 - 4.6 {\mu}m with quality factors reaching up to one million. Advances in fabrication technology enable us to demonstrate such high Q-factors, which put silicon germanium at the forefront of mid-infrared integrated photonic platforms

Isabel Martin-Lyons

We investigate two sub-classes of skew bracoids, the first consists of those we term almost a brace, meaning the multiplicative group decomposes as a certain semi-direct product, and then those that are almost classical, which additionally specifies the relationship between the multiplicative group and the additive. Skew bracoids with these properties have a

Danielle R. Thomas, Conrad Borchers, Sanjit Kakarla, Jionghao Lin

The role of multiple-choice questions (MCQs) as effective learning tools has been debated in past research. While MCQs are widely used due to their ease in grading, open response questions are increasingly used for instruction, given advances in large language models (LLMs) for automated grading. This study evaluates MCQs effectiveness relative to open-respo

Jiaqing Yuan, Ruijie Xi, Munindar P. Singh

Stance detection is crucial for fostering a human-centric Web by analyzing user-generated content to identify biases and harmful narratives that undermine trust. With the development of Large Language Models (LLMs), existing approaches treat stance detection as a classification problem, providing robust methodologies for modeling complex group interactions a

Alireza Furutanpey, Pantelis A. Frangoudis, Patrik Szabo, Schahram Dustdar

This paper investigates the adversarial robustness of Deep Neural Networks (DNNs) using Information Bottleneck (IB) objectives for task-oriented communication systems. We empirically demonstrate that while IB-based approaches provide baseline resilience against attacks targeting downstream tasks, the reliance on generative models for task-oriented communicat

Theodore Kareta, Oscar Fuentes-Muñoz, Nicholas Moskovitz, Davide Farnocchia

The Near-Earth Asteroid (NEA) 2024 PT5 is on an Earth-like orbit which remained in Earth's immediate vicinity for several months at the end of 2024. PT5's orbit is challenging to populate with asteroids originating from the Main Belt and is more commonly associated with rocket bodies mistakenly identified as natural objects or with debris ejected from impact

Manuel González, Javier Pello

We introduce the notion of subprojective and superprojective operators and we use them to prove a variation of the three-space property for subprojective and superprojective spaces. As an application, we show that some spaces considered by Johnson and Lindenstrauss are both subprojective and superprojective.

Cindy Zhang, Frederick P. Roth

Computational variant effect predictors (VEPs) are providing increasingly strong evidence to classify the pathogenicity of missense variants. Precision vs. recall analysis is useful in evaluating VEP performance, especially when adjusted for imbalanced test sets. Here, we describe VEPerform, a web-based tool for evaluating the performance of VEPs at the gene

Shuaiting Li, Chengxuan Wang, Juncan Deng, Zeyu Wang

Vector quantization(VQ) is a hardware-friendly DNN compression method that can reduce the storage cost and weight-loading datawidth of hardware accelerators. However, conventional VQ techniques lead to significant accuracy loss because the important weights are not well preserved. To tackle this problem, a novel approach called MVQ is proposed, which aims at

J. Kyle Brubaker, Kyle E. C. Booth, Akihiko Arakawa, Fabian Furrer

The peptide-protein docking problem is an important problem in structural biology that facilitates rational and efficient drug design. In this work, we explore modeling and solving this problem with the quantum-amenable quadratic unconstrained binary optimization (QUBO) formalism. Our work extends recent efforts by incorporating the objectives and constraint

B. Kootte, M. P. Reiter, C. Andreoiu, S. Beck

Direct observation of proton emission for very small Q-values is often unfeasible due to the long partial half-lives of the proton emission channel associated with tunneling through the Coulomb barrier. Therefore, proton emitters with very small decay energies may require the masses of both parent and daughter nuclei in order to establish them as proton unbo

Hao-Chiang Shao, Yuan-Rong Liao, Tse-Yu Tseng, Yen-Liang Chuo

With increasing revelations of academic fraud, detecting forged experimental images in the biomedical field has become a public concern. The challenge lies in the fact that copy-move targets can include background tissue, small foreground objects, or both, which may be out of the training domain and subject to unseen attacks, rendering standard object-detect

Kaifan Zhang, Lihuo He, Xin Jiang, Wen Lu

Electroencephalogram (EEG) signals have attracted significant attention from researchers due to their non-invasive nature and high temporal sensitivity in decoding visual stimuli. However, most recent studies have focused solely on the relationship between EEG and image data pairs, neglecting the valuable ``beyond-image-modality" information embedded in EEG

Harry J. Davies, Giorgos Iacovides, Danilo P. Mandic

The sheer scale of data required to train modern large language models (LLMs) poses significant risks, as models are likely to gain knowledge of sensitive topics such as bio-security, as well the ability to replicate copyrighted works. Methods designed to remove such knowledge must do so from all prompt directions, in a multi-lingual capacity and without deg