March 2024 arXiv papers — page 64

He-Ran Wang, Dong Yuan

Quantum many-body scars are highly excited eigenstates of non-integrable Hamiltonians which violate the eigenstate thermalization hypothesis and are embedded in a sea of thermal eigenstates. We provide a general mechanism to construct partially integrable models with arbitrarily large local Hilbert space dimensions, which host exact many-body scars. We intro

Derek Churchill, Hae-Young Kee

For many years, CoNb$_2$O$_6$ has served as an exemplar of the one-dimensional Ising model. However, recent experimental and theoretical analyses challenge its applicability to this material. Prior to that, a tailored spin model for 3d$^7$ systems such as Co$^{2+}$, known as the $JK\Gamma$ model, has emerged, featuring Heisenberg $(J)$, Kitaev $(K)$, and Gam

Ethan N. Evans, Matthew Cook, Zachary P. Bradshaw, Margarite L. LaBorde

The recent exploding growth in size of state-of-the-art machine learning models highlights a well-known issue where exponential parameter growth, which has grown to trillions as in the case of the Generative Pre-trained Transformer (GPT), leads to training time and memory requirements which limit their advancement in the near term. The predominant models use

Anirudh Gundhi, Oliviero Angeli, Angelo Bassi

Lagrangians can differ by a total derivative without altering the equations of motion, thus encoding the same physics. This is true both classically and quantum mechanically. We show, however, that in the context of open quantum systems, two Lagrangians that differ by a total derivative can lead to inequivalent reduced dynamics. While these Lagrangians are c

Thomas Bohn, Hanae Inami, Aditya Togi, Lee Armus

We present James Webb Space Telescope (JWST) Integral Field Spectrograph observations of NGC 3256, a local infrared-luminous late-stage merging system with two nuclei roughly 1$\;\rm{kpc}$ apart, both of which have evidence of cold molecular outflows. Using JWST/NIRSpec and MIRI datasets, we investigate this morphologically complex system on spatial scales o

Guillermo Franco Abellán, Guadalupe Cañas Herrera, Matteo Martinelli, Oleg Savchenko

Forthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods.

Jinning Liang, Fangzhou Jiang, Houjun Mo, Andrew Benson

We study the connection between galaxy morphology and host dark matter (DM) halo structure using cosmological simulations. Introducing a new kinematic decomposition scheme, we robustly separate thin and thick discs and measure halo properties, including cosmic web locations, internal structures, and assembly histories. In the TNG50 simulation, we find that t

Daniel DeFelippis, Frédéric Bournaud, Nicolas F. Bouché, Edouard Tollet

The circumgalactic medium (CGM) contains information on the cumulative effect of galactic outflows over time, generally thought to be caused by feedback from star formation and active galactic nuclei. Observations of such outflows via absorption in CGM gas of quasar sightlines show a significant amount of cold ($\lesssim 10^4 \; \rm{K}$) gas which cosmologic

Ahmed Abouelkomsan, Nisarga Paul, Ady Stern, Liang Fu

We explore the possibility of quantum liquids that are compressible but have vanishing DC conductivity in the absence of disorder. We show that the composite Fermi liquid emerging from strong interaction in a generic Chern band has zero Drude weight, in stark contrast to normal Fermi liquids. Our work establishes the absence of Drude weight as the defining p

Ning Bao, Gun Suer

Recently, a polynomial time classical algorithm has been found for learning the shallow representation of a unitary $U$ acting on $n$-qubits, by learning local inversions and then sewing them back together with ancilla qubits and SWAP gates. In this work, we bootstrap local inversion learning (LIL) to optimize quantum circuit depth by learning shallow repres

Orsolya E. Kovacs, Akos Bogdan, Priyamvada Natarajan, Norbert Werner

While supermassive black holes (BHs) are widely observed in the nearby and distant universe, their origin remains debated with two viable formation scenarios with light and heavy seeds. In the light seeding model, the first BHs form from the collapse of massive stars with masses of $10-100 \ \rm{M_{\odot}}$, while the heavy seeding model posits the formation

Ethan Poore, Michael Carini, Ryne Dingler, Ann E. Wehrle

Blazars are characterized by largely aperiodic variability on timescales ranging from minutes to decades across the electromagnetic spectrum. The TESS (Transiting Exoplanet Survey Satellite) mission provides continuous sampling of blazar variability on timescales ranging from tens of minutes to 27 days for a single sector observation. Proper removal of the b

Ahmad Mahmood, Ashmal Vayani, Muzammal Naseer, Salman Khan

Recent studies have demonstrated the effectiveness of Large Language Models (LLMs) as reasoning modules that can deconstruct complex tasks into more manageable sub-tasks, particularly when applied to visual reasoning tasks for images. In contrast, this paper introduces a Video Understanding and Reasoning Framework (VURF) based on the reasoning power of LLMs.

Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner

Automating real-time anomaly detection is essential for identifying rare transients, with modern survey telescopes generating tens of thousands of alerts per night, and future telescopes, such as the Vera C. Rubin Observatory, projected to increase this number dramatically. Currently, most anomaly detection algorithms for astronomical transients rely either

Shun Iwase, Katherine Liu, Vitor Guizilini, Adrien Gaidon

We present a 3D scene completion method that recovers the complete geometry of multiple unseen objects in complex scenes from a single RGB-D image. Despite notable advancements in single-object 3D shape completion, high-quality reconstructions in highly cluttered real-world multi-object scenes remains a challenge. To address this issue, we propose OctMAE, an

Yuedong Chen, Haofei Xu, Chuanxia Zheng, Bohan Zhuang

We introduce MVSplat, an efficient model that, given sparse multi-view images as input, predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we build a cost volume representation via plane sweeping, where the cross-view feature similarities stored in the cost volume can provide valuable geometry cues to the estimation of dep

Tianye Ding, Hongyu Li, Huaizu Jiang

Obstacle detection and tracking represent a critical component in robot autonomous navigation. In this paper, we propose ODTFormer, a Transformer-based model to address both obstacle detection and tracking problems. For the detection task, our approach leverages deformable attention to construct a 3D cost volume, which is decoded progressively in the form of

Saksham Suri, Matthew Walmer, Kamal Gupta, Abhinav Shrivastava

We present a simple self-supervised method to enhance the performance of ViT features for dense downstream tasks. Our Lightweight Feature Transform (LiFT) is a straightforward and compact postprocessing network that can be applied to enhance the features of any pre-trained ViT backbone. LiFT is fast and easy to train with a self-supervised objective, and it

Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin

The remarkable progress of Multi-modal Large Language Models (MLLMs) has garnered unparalleled attention, due to their superior performance in visual contexts. However, their capabilities in visual math problem-solving remain insufficiently evaluated and understood. We investigate current benchmarks to incorporate excessive visual content within textual ques

Zhicong Tang, Tiankai Hang, Shuyang Gu, Dong Chen

This paper introduces a novel theoretical simplification of the Diffusion Schr\"odinger Bridge (DSB) that facilitates its unification with Score-based Generative Models (SGMs), addressing the limitations of DSB in complex data generation and enabling faster convergence and enhanced performance. By employing SGMs as an initial solution for DSB, our approach c

Kumara Kahatapitiya, Kanchana Ranasinghe, Jongwoo Park, Michael S. Ryoo

Language has become a prominent modality in computer vision with the rise of LLMs. Despite supporting long context-lengths, their effectiveness in handling long-term information gradually declines with input length. This becomes critical, especially in applications such as long-form video understanding. In this paper, we introduce a Language Repository (Lang

Yinghao Xu, Zifan Shi, Wang Yifan, Hansheng Chen

We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from sparse-view images in around 0.1s. GRM is a feed-forward transformer-based model that efficiently incorporates multi-view information to translate the input pixels into pixel-aligned Gaussians, which are unprojected to create a set of densely distributed 3D Gaussians represen

Sanjib Kumar Das, Bitan Roy

Altermagnets are crystallographic rotational symmetry breaking spin-ordered states, possessing a net zero magnetization despite manifesting Kramer's non-degenerate bands. Here, we show that momentum-independent local spin nematic orders in monolayer, Bernal bilayer, and rhombohedral trilayer graphene give rise to $p$-wave, $d$-wave, and $f$-wave altermagnets

Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham, Qianyi Wu

3D decomposition/segmentation still remains a challenge as large-scale 3D annotated data is not readily available. Contemporary approaches typically leverage 2D machine-generated segments, integrating them for 3D consistency. While the majority of these methods are based on NeRFs, they face a potential weakness that the instance/semantic embedding features d

Anchal Saxena, P. Daniel Meerburg, Christoph Weniger, Eloy de Lera Acedo

The redshifted 21-cm signal from the Cosmic Dawn and Epoch of Reionization carries invaluable information about the cosmology and astrophysics of the early Universe. Analyzing data from a sky-averaged 21-cm signal experiment requires navigating through an intricate parameter space addressing various factors such as foregrounds, beam uncertainties, ionospheri

Xiang Fan, Anand Bhattad, Ranjay Krishna

We introduce Videoshop, a training-free video editing algorithm for localized semantic edits. Videoshop allows users to use any editing software, including Photoshop and generative inpainting, to modify the first frame; it automatically propagates those changes, with semantic, spatial, and temporally consistent motion, to the remaining frames. Unlike existin

Hasindri Watawana, Kanchana Ranasinghe, Tariq Mahmood, Muzammal Naseer

Self-supervised representation learning has been highly promising for histopathology image analysis with numerous approaches leveraging their patient-slide-patch hierarchy to learn better representations. In this paper, we explore how the combination of domain specific natural language information with such hierarchical visual representations can benefit ric

Manish Chauhan, Manash Samal, Anandmayee Tej, Dirk Froebrich

Jets and outflows are the early signposts of stellar birth. Using the UKIRT Wide Field Infrared Survey for H2 (UWISH2) at 2.12 micron, 127 outflows are identified in molecular cloud complexes Vulpecula OB1 and IRDC G53.2 covering 12 square degrees of the Galactic plane. Using multi-wavelength datasets, from 1.2 to 70 micron, 79 young stellar objects (YSOs) a

Yuning Cui, Syed Waqas Zamir, Salman Khan, Alois Knoll

In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent limitations of cameras or unfavorable ambient conditions. To recover clean images from degraded versions, numerous specialized restoration methods have been developed, each targeting

Junliang Ye, Fangfu Liu, Qixiu Li, Zhengyi Wang

3D content creation from text prompts has shown remarkable success recently. However, current text-to-3D methods often generate 3D results that do not align well with human preferences. In this paper, we present a comprehensive framework, coined DreamReward, to learn and improve text-to-3D models from human preference feedback. To begin with, we collect 25k

David Sweeney, Peter Tuthill, Alberto Krone-Martins, Antoine Mérand

Isolated black holes (BHs) and neutron stars (NSs) are largely undetectable across the electromagnetic spectrum. For this reason, our only real prospect of observing these isolated compact remnants is via microlensing; a feat recently performed for the first time. However, characterisation of the microlensing events caused by BHs and NSs is still in its infa

Haiwen Feng, Zheng Ding, Zhihao Xia, Simon Niklaus

We introduce bounded generation as a generalized task to control video generation to synthesize arbitrary camera and subject motion based only on a given start and end frame. Our objective is to fully leverage the inherent generalization capability of an image-to-video model without additional training or fine-tuning of the original model. This is achieved t

Qing Jiang, Feng Li, Zhaoyang Zeng, Tianhe Ren

We present T-Rex2, a highly practical model for open-set object detection. Previous open-set object detection methods relying on text prompts effectively encapsulate the abstract concept of common objects, but struggle with rare or complex object representation due to data scarcity and descriptive limitations. Conversely, visual prompts excel in depicting no

Owen Deen, Colton River Waller, John Paul Ward

We consider the problem of estimating log-determinants of large, sparse, positive definite matrices. A key focus of our algorithm is to reduce computational cost, and it is based on sparse approximate inverses. The algorithm can be implemented to be adaptive, and it uses graph spline approximation to improve accuracy. We illustrate our approach on classes of

Zeyu Han, Chao Gao, Jinyang Liu, Jeff Zhang

Large models represent a groundbreaking advancement in multiple application fields, enabling remarkable achievements across various tasks. However, their unprecedented scale comes with significant computational costs. These models, often consisting of billions of parameters, require vast amounts of computational resources for execution. Especially, the expan

Joel Rajakumar, James D. Watson, Yi-Kai Liu

Sampling from the output distributions of quantum computations comprising only commuting gates, known as instantaneous quantum polynomial (IQP) computations, is believed to be intractable for classical computers, and hence this task has become a leading candidate for testing the capabilities of quantum devices. Here we demonstrate that for an arbitrary IQP c

Naman Aggarwal, Jonathan P. How

The paper presents Maximal Covariance Backward Reachable Trees (MAXCOVAR BRT), which is a multi-query algorithm for planning of dynamic systems under stochastic motion uncertainty and constraints on the control input with explicit coverage guarantees. In contrast to existing roadmap-based probabilistic planning methods that sample belief nodes randomly and d

Minoru Hirose

We give an explicit formula for the well-known parity result for multiple zeta values as an application of the multitangent functions.

Alexei Vazquez

The utilization of glycolysis in aerobic conditions have been a subject of debate for more than a century. A hypothesis supported by previous data is that glycolysis has a higher rate of ATP production per protein mass and per occupied volume than oxidative phosphorylation (OxPhos). However, a recent work by Shen et al14 challenges previous estimates, report

A. K. Srivastava, Anshika Singh, Balveer Singh, K. Murawski

We present the formation of quasi-periodic cool spicule-like jets in the solar atmosphere using 2.5-D numerical simulation in two-fluid regime (ions+neutrals) under the presence of thermal conduction and ion-neutral collision. The non-linear, impulsive Alfv\'enic perturbations at the top of the photosphere trigger field aligned magnetoacoustic perturbations

Daniel Garibi, Or Patashnik, Andrey Voynov, Hadar Averbuch-Elor

Recent advancements in text-guided diffusion models have unlocked powerful image manipulation capabilities. However, applying these methods to real images necessitates the inversion of the images into the domain of the pretrained diffusion model. Achieving faithful inversion remains a challenge, particularly for more recent models trained to generate images

Rukmani Bai, Soumik Bandyopadhyay

Interaction plays key role in the mixing properties of a multi-component system. The miscibility-immiscibility transition (MIT) in a weakly interacting mixture of Bose gases is predominantly determined by the strengths of the intra and inter-component two-body contact interactions. On the other hand, in the strongly interacting regime interaction induced pro

Dmitry Galakhov, Alexei Morozov, Nikita Tselousov

BPS states in supersymmetric theories can admit additional algebro-geometric structures in their spectra, described as quiver Yangian algebras. Equivariant fixed points on the quiver variety are interpreted as vectors populating a representation module, and matrix elements for the generators are then defined as Duistermaat-Heckman integrals in the vicinity o

Yuval Alaluf, Elad Richardson, Sergey Tulyakov, Kfir Aberman

Recent large-scale vision-language models (VLMs) have demonstrated remarkable capabilities in understanding and generating textual descriptions for visual content. However, these models lack an understanding of user-specific concepts. In this work, we take a first step toward the personalization of VLMs, enabling them to learn and reason over user-provided c

Zheng Zhang, Yeyao Ma, Enming Zhang, Xiang Bai

PSALM is a powerful extension of the Large Multi-modal Model (LMM) to address the segmentation task challenges. To overcome the limitation of the LMM being limited to textual output, PSALM incorporates a mask decoder and a well-designed input schema to handle a variety of segmentation tasks. This schema includes images, task instructions, conditional prompts

Yehor Karpichev, Todd Charter, Jayden Hong, Amir M. Soufi Enayati

The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-robot collaboration attempts to tackle these challenges by combining the strength and precision of machines with

Xiaotian Bi, Dike Su, Qianyun Zhou

Empirical studies have demonstrated that humans possess the remarkable capacity to distinguish whether a glass of water is hot or cold solely by the sound of pouring it. However, the underlying physical mechanisms governing the disparities in the acoustic signatures of hot versus cold water remain to be deciphered. In this paper, we conducted a series of exp

Pedro G. S. Fernandes, Clare Burrage, Astrid Eichhorn, Thomas P. Sotiriou

In this work, we explore the properties and shadows of spin-induced scalarized black holes, as well as investigate how a Ricci coupling influences them. Our findings reveal significant deviations from the Kerr metric in terms of the location and geodesic frequencies of the innermost stable circular orbit and light ring, with the former exhibiting more pronou

Joseph Grant, Davide Morigi

We introduce a signed variant of (valued) quivers and a mutation rule that generalizes the classical Fomin-Zelevinsky mutation of quivers. To any signed valued quiver we associate a matrix that is a signed analogue of the Cartan counterpart appearing in the theory of cluster algebras. From this matrix, we construct a Lie algebra via a "Serre-like" presentati

Yun-Jin Li, Mariia Gladkova, Yan Xia, Rui Wang

Cross-modal place recognition methods are flexible GPS-alternatives under varying environment conditions and sensor setups. However, this task is non-trivial since extracting consistent and robust global descriptors from different modalities is challenging. To tackle this issue, we propose Voxel-Cross-Pixel (VXP), a novel camera-to-LiDAR place recognition fr

Yangchun Zhang, Qiang Liu, Weiming Li, Yirui Zhou

Adversarial inverse reinforcement learning (AIRL) stands as a cornerstone approach in imitation learning, yet it faces criticisms from prior studies. In this paper, we rethink AIRL and respond to these criticisms. Criticism 1 lies in Inadequate Policy Imitation. We show that substituting the built-in algorithm with soft actor-critic (SAC) during policy updat

Khanh Nghiem, Anh Minh Nguyen, Nghi D. Q. Bui

As a research-product hybrid group in AI for Software Engineering (AI4SE), we present four key takeaways from our experience developing in-IDE AI coding assistants. AI coding assistants should set clear expectations for usage, integrate with advanced IDE capabilities and existing extensions, use extendable backend designs, and collect app data responsibly fo

Peter Humphries, Jesse Thorner

We establish two new variants of arithmetic quantum ergodicity. The first is for self-dual $\mathrm{GL}_2$ Hecke-Maass newforms over $\mathbb{Q}$ as the level and Laplace eigenvalue vary jointly. The second is a nonsplit analogue wherein almost all restrictions of Hilbert (respectively Bianchi) Hecke-Maass cusp forms to the modular surface dissipate as their

Attila Szolnoki, Xiaojie Chen

Competitors in an intransitive loop of dominance can form a defensive alliance against an external species. The vitality of this super-structure, however, is jeopardized if we modify the original rock-scissors-paper-like rule and allow that the vicinity of a predator blocks stochastically the invasion success of its neighboring prey towards a third actor. To

Zonghan Yang, Peng Li, Ming Yan, Ji Zhang

Language agents have demonstrated autonomous decision-making abilities by reasoning with foundation models. Recently, efforts have been made to train language agents for performance improvement, with multi-step reasoning and action trajectories as the training data. However, collecting such trajectories still requires considerable human effort, by either art

Sibasish Banerjee, Mauricio Romo, Raphael Senghaas, Johannes Walcher

Previous work has given proof and evidence that BPS states in local Calabi-Yau 3-folds can be described and counted by exponential networks on the punctured plane, with the help of a suitable non-abelianization map to the mirror curve. This provides an appealing elementary depiction of moduli of special Lagrangian submanifolds, but so far only a handful of e

Valay Agarawal, Daniel King, Matthew R. Hermes, Laura Gagliardi

The localized active space self consistent field (LASSCF) method factorizes a complete active space (CAS) wave function into an antisymmetrized product of localized active space wave function fragments. Correlation between fragments is then reintroduced through LAS state interaction (LASSI), in which the Hamiltonian is diagonalized in a model space of LAS st

William Toner, Luke Darlow

Despite their simplicity, linear models perform well at time series forecasting, even when pitted against deeper and more expensive models. A number of variations to the linear model have been proposed, often including some form of feature normalisation that improves model generalisation. In this paper we analyse the sets of functions expressible using these

R. Inanc Baykur

We note that infinitely many irreducible, closed, simply connected 4-manifolds, with prescribed signature and spin type, admit perfect Morse functions, i.e. they can be given handle decompositions without 1- and 3-handles. In particular, there are many such 4-manifolds homeomorphic but not diffeomorphic to the standard 4-manifolds # m (S^2 x S^2) and # n (CP

Valery V. Ryzhikov

Let $\psi(n)\to +0$ and a square-integrable function $f$ be non-zero, then for the typical mixing automorphism $T$ the set $\{n:\, |(T^nf,f) |>\psi( n)\}$ is infinite. The mildly mixing automorphisms $T$ do not have convergences of non-zero averages $\frac 1 {k_n} \sum_{i=1}^{k_n}T^if (x)$ with the rate of $o\left(\frac 1 {k_n}\right)$.

Ethan Young, Mason A. Porter

The leading eigenvalue $\lambda$ of the adjacency matrix of a graph exerts much influence on the behavior of dynamical processes on that graph. It is thus relevant to relate notions of the importance (specifically, centrality measures) of network structures to $\lambda$ and its associated eigenvector. We study a previously derived measure of edge importance

Zhan Gao, Guang Yang, Amanda Prorok

This work views the multi-agent system and its surrounding environment as a co-evolving system, where the behavior of one affects the other. The goal is to take both agent actions and environment configurations as decision variables, and optimize these two components in a coordinated manner to improve some measure of interest. Towards this end, we consider t

Zeev Yampolsky, Yair Stolero, Nitzan Pri-Hadash, Dan Solodar

An inertial navigation system (INS) utilizes three orthogonal accelerometers and gyroscopes to determine platform position, velocity, and orientation. There are countless applications for INS, including robotics, autonomous platforms, and the internet of things. Recent research explores the integration of data-driven methods with INS, highlighting significan

Víctor Ponce-López

The aim of this paper is to evaluate whether large language models trained on multi-choice question data can be used to discriminate between medical subjects. This is an important and challenging task for automatic question answering. To achieve this goal, we train deep neural networks for multi-class classification of questions into the inferred medical sub

Sadiq Jaffer, Michael Dales, Patrick Ferris, Thomas Swinfield

Carbon credits purchased in the voluntary carbon market allow unavoidable emissions, such as from international flights for essential travel, to be offset by an equivalent climate benefit, such as avoiding emissions from tropical deforestation. However, many concerns regarding the credibility of these offsetting claims have been raised. Moreover, the credit

Pedro da Silveira Ferreira, Valerio Marra

The cosmological principle posits that the universe is statistically homogeneous and isotropic on large scales, implying all matter shares the same rest frame. This principle suggests that velocity estimates of our motion from various sources should agree with the cosmic microwave background (CMB) dipole's inferred velocity of 370 km/s. Yet, for over two dec

Christian Scharrer, Alexander West

Motivated by a model for lipid bilayer cell membranes, we study the minimization of the Willmore functional in the class of oriented closed surfaces with prescribed total mean curvature, prescribed area, and prescribed genus. Adapting methods previously developed by Keller-Mondino-Rivi\`ere, Bauer-Kuwert, and Ndiaye-Sch\"atzle, we prove existence of smooth m

William James Bolton, Rafael Poyiadzi, Edward R. Morrell, Gabriela van Bergen Gonzalez Bueno

Large Language Models (LLMs) increasingly support applications in a wide range of domains, some with potential high societal impact such as biomedicine, yet their reliability in realistic use cases is under-researched. In this work we introduce the Reliability AssesMent for Biomedical LLM Assistants (RAmBLA) framework and evaluate whether four state-of-the-a

I. Bearden, V. Buchakchiev, A. Buhl, L. Dufke

Highly integrated multichannel readout electronics is crucial in contemporary particle physics experiments. A novel silicon photomultiplier readout system based on the VMM3a ASIC was developed, for the first time exploiting this chip for calorimetric purposes. To extend the dynamic range the signal from each SiPM channel was processed by two electronics chan

Dragan Hajdukovic

More recently, the ALPHA-g experiment has shown that antiatoms fall in the Earth's gravitational field like ordinary atoms, with the non-negligible possibility that antiatoms fall with a slightly lower acceleration. A possible lower acceleration of antiatoms (which could be revealed with two orders of magnitude higher precision measurements) would be an epoc

Aleix Galan, Ignacio Fernandez-Hernandez, Wim De Wilde, Sofie Pollin

Galileo is the first global navigation satellite system to authenticate their civilian signals through the Open Service Galileo Message Authentication (OSNMA) protocol. However, OSNMA delays the time to obtain a first position and time fix, the Time To First Authentication Fix (TTFAF). Reducing the TTFAF as much as possible is crucial to integrate the techno

Bram Mesland, Adam Rennie

Using the Levi-Civita connection on the noncommutative differential one-forms of a spectral triple $(\B,\H,\D)$, we define the full Riemann curvature tensor, the Ricci curvature tensor and scalar curvature. We give a definition of Dirac spectral triples and derive a general Weitzenbock formula for them. We apply these tools to $\theta$-deformations of compac

Munkhtulga Battogtokh, Yiwen Xing, Cosmin Davidescu, Alfie Abdul-Rahman

In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes that are more difficult to differentiate from one another. As a consequence, the semantic structures of datasets have become more complex, and model decisions more difficult to explain. Existing tools, suit

Daniel Marchant, Imad Faruque, Jorge Barreto

Here we show photon pair generation from ring resonator and waveguide structures in a hybrid silicon-BTO on insulator platform with a pulsed pump. Our analysis of single photon and coincidence generation rates show that Spontaneous Four-Wave Mixing is comparable to that expected from SOI devices of similar characteristics and find a $\gamma_{eff}$ of (14.7 $

M. S. Zidi, J. Ph. Guillet, I. Schienbein, H. Zaraket

We present a novel subtraction method to remove the soft and collinear divergences at next-to-leading order for processes involving an arbitrary number of fragmentation functions, where this method acts directly in the hadronic centre-of-mass frame. We provide the analytical formulae of the subtraction terms in the general case where all the final state part

Larry Han, Yi Zhang, Meena Nathan, John E. Mayer,

Congenital heart defects (CHD) are the most prevalent birth defects in the United States and surgical outcomes vary considerably across the country. The outcomes of treatment for CHD differ for specific patient subgroups, with non-Hispanic Black and Hispanic populations experiencing higher rates of mortality and morbidity. A valid comparison of outcomes with

Yarden Frenkel, Yael Vinker, Ariel Shamir, Daniel Cohen-Or

Image stylization involves manipulating the visual appearance and texture (style) of an image while preserving its underlying objects, structures, and concepts (content). The separation of style and content is essential for manipulating the image's style independently from its content, ensuring a harmonious and visually pleasing result. Achieving this separa

Bernhard Böhmler, Caroline Lassueur

Let $p$ be a prime number. We compute the trivial source character tables of finite Frobenius groups $G$ with an abelian Frobenius complement $H$ and an elementary abelian Frobenius kernel of order $p^2$. More precisely, we deal with all infinite families of such groups which occur in the two extremal cases for the fusion of $p$-subgroups: the case in which

Luis Jorge Sánchez Saldaña, Mario Velásquez

We provide an explicit computation of the cohomology groups (with untwisted coefficients) of semidirect products of the form $\mathbb{Z}^n\rtimes \mathbb{Z}/m$ with $m$ free of squares, by means of formulas that only depend on $n$, $m$ and the action of $\mathbb{Z}/m$ on $\mathbb{Z}^n$. We want to highlight the fact that we are not impossing any conditions o

Sathiskumar Mariappan, Dilip Bhoi, Boby Joseph, R. P. Singh

We report a pressure-induced enhancement of the superconducting transition temperature (Tc) in a non-centrosymmetric (NCS) compound, LaPtGe. With pressure, till 3 GPa, we observed a modest enhancement of the Tc with a rate of 0.071 K/GPa. However, above this pressure, the rate showed a ~2.5 times increase, 0.183 K/GPa. We observed a Tc of 3.94 K at 6 GPa, th

Katie Marsden

The half-wave maps equation is a nonlocal geometric equation arising in the continuum dynamics of Haldane-Shashtry and Calogero-Moser spin systems. In high dimensions $n\geq4$, global wellposedness for data which is small in the critical Besov space $\dot{B}^{n/2}_{2,1}$ is known since the works of Krieger, Sire and Kiesenhofer [13,9]. There is a major obstr

Avani Gupta, P J Narayanan

The focus of recent research has shifted from merely improving the metrics based performance of Deep Neural Networks (DNNs) to DNNs which are more interpretable to humans. The field of eXplainable Artificial Intelligence (XAI) has observed various techniques, including saliency-based and concept-based approaches. These approaches explain the model's decision

Clayton Cohn, Nicole Hutchins, Tuan Le, Gautam Biswas

This paper explores the use of large language models (LLMs) to score and explain short-answer assessments in K-12 science. While existing methods can score more structured math and computer science assessments, they often do not provide explanations for the scores. Our study focuses on employing GPT-4 for automated assessment in middle school Earth Science,

Ivan D. Chipchakov

This paper considers K\"{o}the's question of whether every associative locally finite-dimensional (abbr., LFD) central division algebra $R$ over a field $K$ is a normally locally finite (abbr., NLF) algebra over $K$, that is, whether every nonempty finite subset $Y$ of $R$ is contained in a finite-dimensional central $K$-subalgebra $\mathcal{R} _{Y}$ of $R$.

Yuxi Tian, Nicole Pratt, Laura L Hester, George Hripcsak

In pharmacoepidemiology research, instrumental variables (IVs) are variables that strongly predict treatment but have no causal effect on the outcome of interest except through the treatment. There remain concerns about the inclusion of IVs in propensity score (PS) models amplifying estimation bias and reducing precision. Some PS modeling approaches attempt

Maxime Peyrard, Martin Josifoski, Robert West

Recent work demonstrated great promise in the idea of orchestrating collaborations between LLMs, human input, and various tools to address the inherent limitations of LLMs. We propose a novel perspective called semantic decoding, which frames these collaborative processes as optimization procedures in semantic space. Specifically, we conceptualize LLMs as se

Vitaliy Popov, Xinyue Chen, Jingying Wang, Michael Kemp

Shared gaze visualizations have been found to enhance collaboration and communication outcomes in diverse HCI scenarios including computer supported collaborative work and learning contexts. Given the importance of gaze in surgery operations, especially when a surgeon trainer and trainee need to coordinate their actions, research on the use of gaze to facili

Pantelis Bampoulis, Carolien Castenmiller, Dennis J. Klaassen, Jelle v. Mil

Twisting bilayers of two-dimensional topological insulators has the potential to create unique quantum states of matter. Here, we successfully synthesized a twisted bilayer of germanene on Ge2Pt(101) with a 21.8$^o$ degrees twist angle, corresponding to a commensurate ($\sqrt{7} \times \sqrt{7}$) structure. Using scanning tunneling microscopy and spectroscop

Ruyi Lian, Yuewei Lin, Longin Jan Latecki, Haibin Ling

Localizing predefined 3D keypoints in a 2D image is an effective way to establish 3D-2D correspondences for instance-level 6DoF object pose estimation. However, unreliable localization results of invisible keypoints degrade the quality of correspondences. In this paper, we address this issue by localizing the important keypoints in terms of visibility. Since

Matteo Braglia, Lucas Pinol

The in-in formalism provides a way to systematically organize the calculation of primordial correlation functions. Although its theoretical foundations are now firmly settled, the treatment of total time derivative interactions, incorrectly trivialized as ``boundary terms'', has been the subject of intense discussions and conceptual mistakes. In this work, w

Takahiro Tsumura, Seiji Yamada

As anthropomorphic agents (AI and robots) are increasingly used in society, empathy and trust between people and agents are becoming increasingly important. A better understanding of agents by people will help to improve the problems caused by the future use of agents in society. In the past, there has been a focus on the importance of self-disclosure and th

Tom Mucke, Alexander Renneke, Finn Seesemann, Felix Engelhardt

This paper aims to improve the average response time for naval accidents in the North and Baltic Sea. To do this we optimize the strategic distribution of the vessel fleet used by the Deutsche Gesellschaft zur Rettung Schiffbr\"uchiger (German Maritime Search and Rescue Service) (DGzRS) across several home stations. Based on these locations, in case of an in

Gabriel O. Ferreira, André F. Zanella, Stefanos Bakirtzis, Chiara Ravazzi

Heterogeneous networks have emerged as a popular solution for accommodating the growing number of connected devices and increasing traffic demands in cellular networks. While offering broader coverage, higher capacity, and lower latency, the escalating energy consumption poses sustainability challenges. In this paper a novel optimization approach for OFDMA h

Antoine Guédon, Vincent Lepetit

We propose Gaussian Frosting, a novel mesh-based representation for high-quality rendering and editing of complex 3D effects in real-time. Our approach builds on the recent 3D Gaussian Splatting framework, which optimizes a set of 3D Gaussians to approximate a radiance field from images. We propose first extracting a base mesh from Gaussians during optimizat

Matteo Beccaria

We consider Schur line defect correlators in four dimensional $\mathcal N=4$ $U(N)$ SYM and their giant graviton expansion encoding finite $N$ corrections to the large $N$ limit. We compute in closed form the single giant graviton contribution to correlators with general insertions of $\frac{1}{2}$-BPS charged Wilson lines. For the 2-point function with fund

Junyi Wu, Bin Duan, Weitai Kang, Hao Tang

While Transformers have rapidly gained popularity in various computer vision applications, post-hoc explanations of their internal mechanisms remain largely unexplored. Vision Transformers extract visual information by representing image regions as transformed tokens and integrating them via attention weights. However, existing post-hoc explanation methods m

Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas

Today's most accurate language models are trained on orders of magnitude more language data than human language learners receive - but with no supervision from other sensory modalities that play a crucial role in human learning. Can we make LMs' representations and predictions more accurate (and more human-like) with more ecologically plausible supervision?

Bertrand Kian Hassani, Yacoub Bahini

This paper introduces and defines a novel concept in sustainable investing, termed crosswashing, and explore its impact on ESG (Environmental, Social, and Governance) ratings through quantitative analysis using a Multi-Criteria Decision Making (MCDM) model. The study emphasises that this specific form of greenwashing is not currently considered in existing E

Yosuke Fukuchi, Seiji Yamada

Communication robots have the potential to contribute to effective human-XAI interaction as an interface that goes beyond textual or graphical explanations. One of their strengths is that they can use physical and vocal expressions to add detailed nuances to explanations. However, it is not clear how a robot can apply such expressions, or in particular, how

Raymond J. Pfeiffer

The current literature is rather vague regarding how to calculate the exact numerical value of the resonant ion scattering cross-section that should be used for a specific bandpass of finite width. Such a value was needed in order to calculate the ion and mass densities in the shock fronts of hot, close binary star systems. This was done based on a modeling