October 2023 arXiv papers — page 50

Elena Cáceres, Rodrigo Castillo Vásquez, Karl Landsteiner, Ignacio Salazar Landea

We use the radial null energy condition to construct a monotonic $a$-function for a certain type of non-relativistic holographic RG flows. We test our $a$-function in three different geometries that feature a Boomerang RG flow, characterized by a domain wall between two AdS spaces with the same AdS radius, but with different (and sometimes directions depende

Xiaoyu Wang, Oskar Vafek

Magic-angle twisted bilayer graphene is the best studied physical platform featuring moire potential induced narrow bands with non-trivial topology and strong electronic correlations. Despite their significance, the Chern insulating states observed at a finite magnetic field -- and extrapolating to a band filling, $s$, at zero field -- remain poorly understo

Mario Raeth, Klaus Hallatschek

First of a kind 6D-Vlasov computer simulations of high frequency ion Bernstein wave turbulence for parameters relevant to the tokamak edge show transport comparable to sub-Larmor-frequency gyrokinetic turbulence. The customary restriction of magnetized plasma turbulence studies to the gyrokinetic approximation may not be based on physics but only a practical

Yusupjan Habibulla, Hai-Jun Zhou

We study the minimum dominating set problem as a representative combinatorial optimization challenge with a global topological constraint. The requirement that the backbone induced by the vertices of a dominating set should be a connected subgraph makes the problem rather nontrivial to investigate by statistical physics methods. Here we convert this global c

José Diaz Polanco, José Ayala, Maximiliano Ujevic

We present an exact, time-dependent solution for the Einstein field equations that models the coupling between an anisotropic fluid and a magnetic field in an axially symmetric space-time. By carefully selecting the metric components, we achieve a convenient separation of variables that enables us to solve Einstein's field equations and obtain a solution tha

Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi

Graph deep learning methods have become popular tools to process collections of correlated time series. Unlike traditional multivariate forecasting methods, graph-based predictors leverage pairwise relationships by conditioning forecasts on graphs spanning the time series collection. The conditioning takes the form of architectural inductive biases on the fo

Vincenzo Imperati, Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini

In recent years, major social media platforms have implemented increasingly strict moderation policies, resulting in bans and restrictions on conspiracy theory-related content. To circumvent these restrictions, conspiracy theorists are turning to alternatives, such as Telegram, where they can express and spread their views with fewer limitations. Telegram of

Zhen Qin, Zhishuai Liu, Pan Xu

signSGD is attractive in nonconvex optimization because it communicates sign-valued rather than full-precision gradients. Several standard analyses assume independent stochastic-gradient samples, whereas a common finite-sum implementation reshuffles the data and processes them sequentially. We study this variant, signSGD with random reshuffling (SignRR), and

Di Chen, Meixin Zhu, Hao Yang, Xuesong Wang

Autonomous vehicles (AVs) have the potential to significantly revolutionize society by providing a secure and efficient mode of transportation. Recent years have witnessed notable advancements in autonomous driving perception and prediction, but the challenge of validating the performance of AVs remains largely unresolved. Data-driven microscopic traffic sim

Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano

For a sequence of classification tasks that arrive over time, it is common that tasks are evolving in the sense that consecutive tasks often have a higher similarity. The incremental learning of a growing sequence of tasks holds promise to enable accurate classification even with few samples per task by leveraging information from all the tasks in the sequen

Guozhen Lu, Qiaohua Yang

Using the scattering theory on the hyperbolic space $\mathbb{H}^n$, we give the explicit formulas of the fractional GJMS operators $P_{\gamma}$ for all $\gamma\in(0,\frac{n}{2})\setminus\mathbb{N}$ on $\mathbb{H}^n$.These $P_{\gamma}$ for $\gamma\in(0,\frac{n}{2})\setminus\mathbb{N}$ are neither conformal to the fractional Laplacians on $\mathbb{R}^n_{+}$ no

Shuai Feng, Liang Feng Zhang

In single-cloud storage, ciphertext-policy attribute-based encryption (CP-ABE) allows one to encrypt any data under an access structure to a cloud server, specifying what attributes are required to decrypt. In multi-cloud storage, a secret sharing scheme (SSS) allows one to split any data into multiple shares, one to a single server, and specify which subset

A. R. P. Rau

The multiple puns in the title play on a curiosity, that the rescue of a person overboard at sea and the dominance of the second Born term in charge transfer in atomic collisions share common elements of physics. Essentials and commonality in the two are explained.

Salma Begum Tamanna, Gias Uddin, Lan Xia, Longyu Zhang

Modern programming languages like Java require runtime systems to support the implementation and deployment of software applications in diverse computing platforms and operating systems. These runtime systems are normally developed in GitHub-hosted repositories based on close collaboration between large software companies (e.g., IBM, Microsoft) and OSS devel

Darshan Prabhu, Preethi Jyothi, Sriram Ganapathy, Vinit Unni

Speech accents pose a significant challenge to state-of-the-art automatic speech recognition (ASR) systems. Degradation in performance across underrepresented accents is a severe deterrent to the inclusive adoption of ASR. In this work, we propose a novel accent adaptation approach for end-to-end ASR systems using cross-attention with a trainable set of code

Nuno Arala

For a pair of quadratic forms with rational coefficients in at least $10$ variables, we prove an asymptotic formula for the number of common zeros under the assumption that the two forms determine a projective variety with exactly two (geometric) singular points defined over an imaginary quadratic field. This extends work of Browning and Munshi with the help

J. W. Han, H. L. Ding, J. F. Zhu, H. K. Li

During the pulsed operation of the linear accelerator in DCLS (Dalian Coherent Light Source), we found a strong correlation between the klystron modulator's high voltage and the klystron output microwave, with noticeable jitter among adjacent microwaves. Therefore, we propose an intra-pulse feedforward algorithm and implement it in LLRF (Low-Level Radiofrequ

P. Schady, R. M. Yates, L. Christensen, A. De Cia

Much of what is known of the chemical composition of the universe is based on emission line spectra from star forming galaxies. Emission-based inferences are, nevertheless, model-dependent and they are dominated by light from luminous star forming regions. An alternative and sensitive probe of the metallicity of galaxies is through absorption lines imprinted

R. Alawadhi, D. Angella, A. Leonardo, T. Schettini Gherardini

We construct all possible complete intersection Calabi-Yau five-folds in a product of four or less complex projective spaces, with up to four constraints. We obtain $27068$ spaces, which are not related by permutations of rows and columns of the configuration matrix, and determine the Euler number for all of them. Excluding the $3909$ product manifolds among

Yun-Hua Chen, Meng-Lin Du, Feng-Kun Guo

We perform a unified description of the experimental data of the $\pi^+\pi^-$ and $J/\psi\pi^\pm$ invariant mass spectra for $e^+e^- \rightarrow J/\psi \pi^+\pi^-$ and the $D^0 D^{\ast-}$ mass spectrum for $e^+e^- \rightarrow D^0 D^{\ast-} \pi^+$ at $e^+e^-$ center-of-mass energies 4.23 and 4.26 GeV. The analysis takes into account open-charm meson loops tha

Marco Caliendo, Nico Pestel, Rebecca Olthaus

We study the long-term effects of the 2015 German minimum wage introduction and its subsequent increases on regional employment. Using data from two waves of the Structure of Earnings Survey allows us to estimate models that account for changes in the minimum wage bite over time. While the introduction mainly affected the labour market in East Germany, the r

Massimiliano Berti, Scipio Cuccagna, Francisco Gancedo, Stefano Scrobogna

In this paper we paralinearize the contour dynamics equation for sharp-fronts of $\alpha$-SQG, for any $ \alpha \in (0,1) \cup (1,2) $, close to a circular vortex. This turns out to be a quasi-linear Hamiltonian PDE. After deriving the asymptotic expansion of the linear frequencies of oscillations at the vortex disk and verifying the absence of three wave in

Michael X. Zhang, An Gu

We employ a coalescence model to form deuterons ($\rm d$), tritons (${\rm t}$) and helium-3 ($^3{\rm He}$) nuclei from a uniformly distributed volume of protons ({\rm p}) and neutrons ({\rm n}). We study the ratio $N_{\rm t} N_{\rm p}/N_{\rm d}^2$ of light nuclei yields as a function of the neutron density fluctuations. We investigate the effect of finite tr

Szymon Antoniak, Michał Krutul, Maciej Pióro, Jakub Krajewski

Mixture of Experts (MoE) models based on Transformer architecture are pushing the boundaries of language and vision tasks. The allure of these models lies in their ability to substantially increase the parameter count without a corresponding increase in FLOPs. Most widely adopted MoE models are discontinuous with respect to their parameters - often referred

Saeid Bayat, James T. Allison

Active components, such as actuators, constitute a fundamental aspect of engineering systems, affording the freedom to shape system behavior as desired. However, this capability necessitates energy consumption, primarily in the form of electricity. Thus, a trade-off emerges between energy usage and desired outcomes. While open-loop optimal control methods st

Junda Wang, Zonghai Yao, Zhichao Yang, Huixue Zhou

We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues. NoteChat embodies the principle that an ensemble of role-specific LLMs, through structured role-play and strategic prompting, can perform their assigned roles more effectively. The synergy among these role-playing

Simon Hellmann, Terrance Wilms, Stefan Streif, Sören Weinrich

Dynamic operation of biological processes, such as anaerobic digestion (AD), requires reliable process monitoring to guarantee stable operating conditions at all times. Unscented Kalman filters (UKF) are an established tool for nonlinear state estimation, and there exist numerous variants of UKF implementations, treating state constraints, improvements of nu

Koti S. Jaddu, Paul A. Bilokon

High-frequency trading is prevalent, where automated decisions must be made quickly to take advantage of price imbalances and patterns in price action that forecast near-future movements. While many algorithms have been explored and tested, analytical methods fail to harness the whole nature of the market environment by focusing on a limited domain. With the

Viktor T. Toth

We investigate the propagation of light signals across multiple gravitational lenses, with particular emphasis on the "communication bridge" scenario of two lenses with collinear source and observer. The lenses are assumed to be non-coplanar, far enough from one another for each lens to be treated independently as thin lenses in the limit of weak gravity. We

Suvra Pal, Sandip Barui

A simple yet effective way of modeling survival data with cure fraction is by considering Box-Cox transformation cure model (BCTM) that unifies mixture and promotion time cure models. In this article, we numerically study the statistical properties of the BCTM when applied to interval censored data. Time-to-events associated with susceptible subjects are mod

Manyuan Zhang, Guanglu Song, Yu Liu, Hongsheng Li

The introduction of DETR represents a new paradigm for object detection. However, its decoder conducts classification and box localization using shared queries and cross-attention layers, leading to suboptimal results. We observe that different regions of interest in the visual feature map are suitable for performing query classification and box localization

Ali Rida, Satish I. Rao, Jaafar A. El-Awady

Plasticity in hexagonal close packed (HCP) metals and alloys such as Titanium (Ti) and Zirconium (Zr) is carried out by the motion of $\langle a \rangle$ dislocations. Above room temperature, in situ transmission electron microscopy straining experiments have shown that basal slip of $\langle a \rangle$ screw dislocations in Ti is activated and its preponder

David Cushing, Supanat Kamtue, Riikka Kangaslampi, Shiping Liu

In this article we study two discrete curvature notions, Bakry-\'Emery curvature and Ollivier Ricci curvature, on Cayley graphs. We introduce Right Angled Artin-Coxeter Hybrids (RAACHs) generalizing Right Angled Artin and Coxeter groups (RAAGs and RACGs) and derive the curvatures of Cayley graphs of certain RAACHs. Moreover, we show for general finitely pres

Xing Shen, Hengguan Huang, Brennan Nichyporuk, Tal Arbel

Once deployed, medical image analysis methods are often faced with unexpected image corruptions and noise perturbations. These unknown covariate shifts present significant challenges to deep learning based methods trained on "clean" images. This often results in unreliable predictions and poorly calibrated confidence, hence hindering clinical applicability.

H. L. Ding, J. F. Zhu, H. K. Li, J. W. Han

DCLS (Dalian Coherent Light Source) is an FEL (Free-Electron Laser) user facility at EUV (Extreme Ultraviolet). The primary accelerator of DCLS operates at a repetition rate of 20 Hz, and the beam is divided at the end of the linear accelerator through Kicker to make two 10 Hz beamlines work simultaneously. In the past year, we have completed the upgrade of

Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss

The problem of nearest neighbor condensing has enjoyed a long history of study, both in its theoretical and practical aspects. In this paper, we introduce the problem of weighted distance nearest neighbor condensing, where one assigns weights to each point of the condensed set, and then new points are labeled based on their weighted distance nearest neighbor

Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su

Recommender systems have seen significant advancements with the influence of deep learning and graph neural networks, particularly in capturing complex user-item relationships. However, these graph-based recommenders heavily depend on ID-based data, potentially disregarding valuable textual information associated with users and items, resulting in less infor

Alessandro Goffi, Tommaso Leonori

This work addresses the problem of (global) maximal regularity for quasilinear evolution equations with sublinear gradient growth and right-hand side in Lebesgue spaces, complemented with Neumann boundary conditions. The proof relies on a suitable variation of the Bernstein technique and the Bochner identity, and provides new results even for the simpler par

An Vuong, Minh Nhat Vu, Toan Tien Nguyen, Baoru Huang

Scene synthesis is a challenging problem with several industrial applications. Recently, substantial efforts have been directed to synthesize the scene using human motions, room layouts, or spatial graphs as the input. However, few studies have addressed this problem from multiple modalities, especially combining text prompts. In this paper, we propose a lan

Yi-Ming Zhu, Yun Wang, Hao Zhou, Vladimir Lipunov

The long gamma-ray burst GRB 191221B has abundant observations in X-ray, optical and radio bands. In the literature, the observed optical light curve of GRB 191221B displays a plateau around 0.1-day, which is rather peculiar in gamma-ray bursts. Here we performed detailed analysis of the observational data from Swift/UVOT, VLT and LCO, obtained the light cur

Haidong Zhu, Wanrong Zheng, Zhaoheng Zheng, Ram Nevatia

Identifying individuals in unconstrained video settings is a valuable yet challenging task in biometric analysis due to variations in appearances, environments, degradations, and occlusions. In this paper, we present ShARc, a multimodal approach for video-based person identification in uncontrolled environments that emphasizes 3-D body shape, pose, and appea

Alexandre Sac-Morane, Manolis Veveakis, Hadrien Rattez

Considering a 3D sheared granular layer modeled with discrete elements, it is well known the rolling resistance significantly influences the mechanical behavior. Even if the rolling resistance role has been deeply investigated as it is commonly used to represent the the roughness of the grains and the interparticle locking, the role of rolling viscous dampin

Manuel Loparco, Jiaxin Qiao, Zimo Sun

We introduce a "radial" two-point invariant for quantum field theory in de Sitter (dS) analogous to the radial coordinate used in conformal field theory. We show that the two-point function of a free massive scalar in the Bunch-Davies vacuum has an exponentially convergent series expansion in this variable with positive coefficients only. Assuming a converge

Sila Ovgu Korkut, Oznur Oztunc Kaymak, Aytug Onan, Erman Ulker

In the new global era, determining trends can play an important role in guiding researchers, scientists, and agencies. The main faced challenge is to track the emerging topics among the stacked publications. Therefore, any study done to propose the trend topics in a field to foresee upcoming subjects is crucial. In the current study, the trend topics in the

F. Delgado, M. M. Otrokov, A. Arnau

The low energy excitation spectrum of a two-dimensional ferromagnetic material is dominated by single-magnon excitations that show a gapless parabolic dispersion relation with the spin wave vector. This occurs as long as magnetic anisotropy and anisotropic exchange are negligible compared to isotropic exchange. However, to maintain magnetic order at finite t

Iker García-Ferrero, Begoña Altuna, Javier Álvez, Itziar Gonzalez-Dios

Although large language models (LLMs) have apparently acquired a certain level of grammatical knowledge and the ability to make generalizations, they fail to interpret negation, a crucial step in Natural Language Processing. We try to clarify the reasons for the sub-optimal performance of LLMs understanding negation. We introduce a large semi-automatically g

Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew Kyle Lampinen

The Option Keyboard (OK) was recently proposed as a method for transferring behavioral knowledge across tasks. OK transfers knowledge by adaptively combining subsets of known behaviors using Successor Features (SFs) and Generalized Policy Improvement (GPI). However, it relies on hand-designed state-features and task encodings which are cumbersome to design f

Uten Yarach, Itthi Chatnuntawech, Congyu Liao, Surat Teerapittayanon

Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blurring. BUDA-cEPI reconstruction with S-based low-rank modeling of local k-space neighborhoods (S-LORAKS) is shown to be effective at reconstructing the highly under-sampled BUDA-cEP

Anshul Ahluwalia, Payman Behnam, Rohit Das, Alind Khare

Recent advancements in Graph Neural Networks (GNNs) have led to increased model sizes to enhance their capacity and accuracy. Such large models incur high memory usage, latency, and computational costs, thereby restricting their inference deployment. GNN compression techniques compress large GNNs into smaller ones with negligible accuracy loss. One of the mo

Shengling Shi, Zhiyong Sun, Bart De Schutter

Networks of dynamical systems play an important role in various domains and have motivated many studies on the control and analysis of linear dynamical networks. For linear network models considered in these studies, it is typically pre-determined what signal channels are inputs and what are outputs. These models do not capture the practical need to incorpor

Kazuki Ikeda, Rajeev Singh, Robert-Jan Slager

We consider a quantum energy teleportation (QET) method to replicate the phase diagram of a one-dimensional $XXZ$ spin chain featuring a Kondo effect coupling. In this setup, the energy supplier and receiver are spatially separated from the point impurity and do not interact directly with it. Nonetheless, they may successfully generate phase diagrams that cl

Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm

A recent paper by Farina & Pipis (2023) established the existence of uncoupled no-linear-swap regret dynamics with polynomial-time iterations in extensive-form games. The equilibrium points reached by these dynamics, known as linear correlated equilibria, are currently the tightest known relaxation of correlated equilibrium that can be learned in polynomial

Bryan Kumara, Mark Hooper, Carsten Maple, Timothy Hobson

Redactable Signature Schemes and Zero-Knowledge Proofs are two radically different approaches to enable privacy. This paper analyses their merits and drawbacks when applied to decentralized identity system. Redactable Signatures, though competitively quick and compact, are not as expressive as zero-knowledge proofs and do not provide the same level of privac

David Kröger, Milijana Teodosic, Christian Rehtanz

The large-scale integration of flexible heating systems in the European electricity market leads to a substantial increase of transportation requirements and consecutively grid congestions in the continental transmission grid. Novel model formulations for the grid-aware operation of both individual small-scale heat pumps and large-scale power-to-heat (PtH) u

Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu

We study the problem of high-dimensional robust mean estimation in an online setting. Specifically, we consider a scenario where $n$ sensors are measuring some common, ongoing phenomenon. At each time step $t=1,2,\ldots,T$, the $i^{th}$ sensor reports its readings $x^{(i)}_t$ for that time step. The algorithm must then commit to its estimate $\mu_t$ for the

Weiye Zhang, Wenshuai Yu, Licong Zhuang, Xiaoyi Zhang

Autonomous exploration is a fundamental problem for various applications of unmanned aerial vehicles(UAVs). Existing methods, however, are demonstrated to static local optima and two-dimensional exploration. To address these challenges, this paper introduces GO-FEAP (Global Optimal UAV Planner Using Frontier-Omission-Aware Exploration and Altitude-Stratified

Yan Wang, Mengyi Sun, Xinchen Kang, Jingting Li

Dysarthric speech poses significant challenges for individuals with dysarthria, impacting their ability to communicate socially. Despite the widespread use of Automatic Speech Recognition (ASR), accurately recognizing dysarthric speech remains a formidable task, largely due to the limited availability of dysarthric speech data. To address this gap, we develo

Yun Li, Lin Niu, Xipeng Zhang, Kai Liu

Traditional pruning methods are known to be challenging to work in Large Language Models (LLMs) for Generative AI because of their unaffordable training process and large computational demands. For the first time, we introduce the information entropy of hidden state features into a pruning metric design, namely E-Sparse, to improve the accuracy of N:M sparsi

Carlota Parés Morlans, Claire Chen, Yijia Weng, Michelle Yi

We introduce AO-Grasp, a grasp proposal method that generates 6 DoF grasps that enable robots to interact with articulated objects, such as opening and closing cabinets and appliances. AO-Grasp consists of two main contributions: the AO-Grasp Model and the AO-Grasp Dataset. Given a segmented partial point cloud of a single articulated object, the AO-Grasp Mo

Markus Reineke

We verify the Mukai conjecture for Fano quiver moduli spaces associated to dimension vectors in the interior of the fundamental domain.

M. Cretignier, A. G. M. Pietrow, S. Aigrain

The detection of Earth-like planets with the radial-velocity method is currently limited by the presence of stellar activity signatures. On rotational timescales, spots and plages (or faculae) are known to introduce different RV signals, but their corrections require better activity proxies. The best-known chromospheric activity proxies in the visible are th

Luwenjia Zhou, Tao Wang, Emanuele Daddi, Rosemary Coogan

The study of distant galaxy groups and clusters at the peak epoch of star formation is limited by the lack of a statistically and homogeneously selected and spectroscopically confirmed sample. Recent discoveries of concentrated starburst activities in cluster cores have opened a new window to hunt for these structures based on their integrated IR luminositie

Giuseppe Belgioioso, Saverio Bolognani, Giulia Pejrani, Florian Dörfler

Online feedback optimization (OFO) is an emerging control methodology for real-time optimal steady-state control of complex dynamical systems. This tutorial focuses on the application of OFO for the autonomous operation of large-scale transmission grids, with a specific goal of minimizing renewable generation curtailment and losses while satisfying voltage a

Laetitia Mottet, Carolanne Vouriot

The aim of this document is to show how Fluidity can be used to set up typical indoor simulations under a range of conditions. Further information can also be found in the Fluidity manual and online http://fluidityproject.github.io/. The purpose of this document is to allow a new Fluidity user to quickly become independent and start running simulations early

Yukimi Goto, Tohru Koma

We study a lattice Nambu-Jona-Lasinio model with SU(2) and SU(3) flavor symmetries of staggered fermions in the Kogut-Susskind Hamiltonian formalism. This type of four-fermion interactions has been widely used for describing low-energy behaviors of strongly interacting quarks as an effective model. In particular, we focus on the Nambu-Goldstone modes associa

Hiroto Kurita, Goro Kobayashi, Sho Yokoi, Kentaro Inui

The performance of sentence encoders can be significantly improved through the simple practice of fine-tuning using contrastive loss. A natural question arises: what characteristics do models acquire during contrastive learning? This paper theoretically and experimentally shows that contrastive-based sentence encoders implicitly weight words based on informa

S. Rosswog, P. Diener, F. Torsello, T. M. Tauris

Neutron star (NS) mergers where both stars have negligible spins are commonly considered as the most likely ``standard'' case. In globular clusters, however, the majority of NSs have been spun up to millisecond (ms) periods and, based on observed systems, we estimate that a non-negligible fraction of all double NS mergers ($\sim 4\pm2\;\%$) contains one comp

Paolo Stornati, Antonio Acin, Ulysse Chabaud, Alexandre Dauphin

This work introduces a novel approach to quantum simulation by leveraging continuous-variable systems within a photonic hardware-inspired framework. The primary focus is on simulating static properties of the ground state of Hamiltonians associated with infinite-dimensional systems, such as those arising in quantum field theory. We present a continuous-varia

Alessandro Fazzari

Assuming the Riemann Hypothesis, Goldston, Gonek and Montgomery \cite{GGM} studied the second moment of the log-derivative of $\zeta$, shifted away from the half line by $a/\log T$, and its connection with the pair correlation conjecture. In this paper, we consider a weighted version of this problem, where the average is tilted by $|\zeta(\frac{1}{2}+it)|^2$

Sandip Haldar

Borophosphene is investigated for hydrogen storage by density functional theory calculations through Li, Na and Ca decoration. Decoration enhances the binding energy from -0.047 eV/H2 to -0.20 -- -0.42 eV/H2. PDOS and Bader charge analysis elucidate the role of adatom decoration in charge transfer and better binding. Up to 10, 12 and 20 H2 molecules can be a

Roee Hendel, Mor Geva, Amir Globerson

In-context learning (ICL) in Large Language Models (LLMs) has emerged as a powerful new learning paradigm. However, its underlying mechanism is still not well understood. In particular, it is challenging to map it to the "standard" machine learning framework, where one uses a training set $S$ to find a best-fitting function $f(x)$ in some hypothesis class. H

Scott Smith, Robert Zhang

This paper develops a novel minimal-state operational semantics for higher-order functional languages that uses only the call stack and a source program point or a lexical level as the complete state information: there is no environment, no substitution, no continuation, etc. We prove this form of operational semantics equivalent to standard presentations. W

Anant Khandelwal

Pose-guided person image synthesis task requires re-rendering a reference image, which should have a photorealistic appearance and flawless pose transfer. Since person images are highly structured, existing approaches require dense connections for complex deformations and occlusions because these are generally handled through multi-level warping and masking

Mentzelos Melistas

Let $R$ be a complete discrete valuation ring with fraction field $K$ and perfect residue field $k$ of characteristic $p>0$. Let $E/K$ be an elliptic curve with a $K$-rational isogeny of prime degree $\ell$. In this article, we study the possible Kodaira types of reduction that $E/K$ can have. We also prove some related results for elliptic curves over $\mat

Qilei Li, Shaogang Gong

While deep learning has significantly improved ReID model accuracy under the independent and identical distribution (IID) assumption, it has also become clear that such models degrade notably when applied to an unseen novel domain due to unpredictable/unknown domain shift. Contemporary domain generalization (DG) ReID models struggle in learning domain-invari

Valeriy Shevchenko, Daria Taniushkina, Aleksander Lukashevich, Aleksandr Bulkin

The United Nations has identified improving food security and reducing hunger as essential components of its sustainable development goals. As of 2021, approximately 828 million people worldwide are experiencing hunger and malnutrition, with numerous fatalities reported. Climate change significantly impacts agricultural land suitability, potentially leading

Rujing Xiong, Ke Yin, Tiebin Mi, Jialong Lu

A fair beam allocation framework through reconfigurable intelligent surfaces (RISs) is proposed, incorporating the Max-min criterion. This framework focuses on designing explicit beamforming functionalities through optimization. Firstly, realistic models, grounded in geometrical optics, are introduced to characterize the input/output behaviors of RISs, effec

Qinan Yu, Jack Merullo, Ellie Pavlick

Language Models (LMs) often must integrate facts they memorized in pretraining with new information that appears in a given context. These two sources can disagree, causing competition within the model, and it is unclear how an LM will resolve the conflict. On a dataset that queries for knowledge of world capitals, we investigate both distributional and mech

Hyunwoo Lee

Dirac's theorem determines the sharp minimum degree threshold for graphs to contain perfect matchings and Hamiltonian cycles. There have been various attempts to generalize this theorem to hypergraphs with larger uniformity by considering hypergraph matchings and Hamiltonian cycles. In this paper, we consider another natural generalization of perfect matchin

Evgenii E. Narimanov

A new frontier in optics research has been opened by the recent developments in non-perturbative optical modulation in both time and space that creates temporal boundaries generating ``time-reflection'' and ``time-refraction'' of light in the medium. The resulting formation of a Photonic Time Crystal within the modulated optical material leads to a broad ran

Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte

Linear reduced-order modeling (ROM) simplifies complex simulations by approximating the behavior of a system using a simplified kinematic representation. Typically, ROM is trained on input simulations created with a specific spatial discretization, and then serves to accelerate simulations with the same discretization. This discretization-dependence is restr

Fotis Koutroulis, Oleg Lebedev, Stefan Pokorski

We consider gravitational production of singlet fermions such as sterile neutrinos during and after inflation. The production efficiency due to classical gravity is suppressed by the fermion mass. Quantum gravitational effects, on the other hand, are expected to break conformal invariance of the fermion sector by the Planck scale-suppressed operators irrespe

Tal Levy, Omer Goldman, Reut Tsarfaty

The ability to identify and control different kinds of linguistic information encoded in vector representations of words has many use cases, especially for explainability and bias removal. This is usually done via a set of simple classification tasks, termed probes, to evaluate the information encoded in the embedding space. However, the involvement of a tra

Alan Cowap, Yvette Graham, Jennifer Foster

Recent developments in generative AI have shone a spotlight on high-performance synthetic text generation technologies. The now wide availability and ease of use of such models highlights the urgent need to provide equally powerful technologies capable of identifying synthetic text. With this in mind, we draw inspiration from psychological studies which sugg

Pengyu Li, Xiao Li, Yutong Wang, Qing Qu

We study deep neural networks for the multi-label classification (MLab) task through the lens of neural collapse (NC). Previous works have been restricted to the multi-class classification setting and discovered a prevalent NC phenomenon comprising of the following properties for the last-layer features: (i) the variability of features within every class col

Ángel Javier Alonso, Michael Kerber, Tung Lam, Michael Lesnick

The Delaunay filtration $\mathcal{D}_{\bullet}(X)$ of a point cloud $X\subset \mathbb{R}^d$ is a central tool of computational topology. Its use is justified by the topological equivalence of $\mathcal{D}_{\bullet}(X)$ and the offset (i.e., union-of-balls) filtration of $X$. Given a function $\gamma: X \to \mathbb{R}$, we introduce a Delaunay bifiltration $\

Zhiyi Li, Jida Zhang, Jieao Zhu, Shi Jin

Reconfigurable intelligent surfaces (RISs) are widely considered a promising technology for future wireless communication systems. As an important indicator of RIS-assisted communication systems in green wireless communications, energy efficiency (EE) has recently received intensive research interest as an optimization target. However, most previous works ha

Henry Robert Thackeray

For each positive integer n, if the sum of the factors of n is divided by n, then the result is called the abundancy index of n. If the abundancy index of some positive integer m equals the abundancy index of n but m is not equal to n, then m and n are called friends. A positive integer with no friends is called solitary. The smallest positive integer that i

Zakir Deniz

A vertex coloring of a graph G is called a 2-distance coloring if any two vertices at a distance at most 2 from each other receive different colors. Suppose that G is a planar graph with a maximum degree at most 5. We prove that G admits a 2-distance 16 coloring, which improves the result given by Hou et al. (Graphs and Combinatorics 39:20, 2023).

Tom Liu, Hui Lin, Aggelos K. Katsaggelos, Adrienne Kline

Coronary angiography remains the gold standard for diagnosis of coronary artery disease, the most common cause of death worldwide. While this procedure is performed more than 2 million times annually, there remain few methods for fast and accurate automated measurement of disease and localization of coronary anatomy. Here, we present our solution to the Auto

Linshan Liu, Mateusz B. Majka, Pierre Monmarché

We show the $L^2$-Wasserstein contraction for the transition kernel of a discretised diffusion process, under a contractivity at infinity condition on the drift and a sufficiently high diffusivity requirement. This extends recent results that, under similar assumptions on the drift but without the diffusivity restrictions, showed the $L^1$-Wasserstein contra

Anant Khandelwal

Dynamic scene graph generation (SGG) from videos requires not only a comprehensive understanding of objects across scenes but also a method to capture the temporal motions and interactions with different objects. Moreover, the long-tailed distribution of visual relationships is a crucial bottleneck for most dynamic SGG methods. This is because many of them f

Yirong Chen, Zhenyu Wang, Xiaofen Xing, huimin zheng

Large language models (LLMs) have performed well in providing general and extensive health suggestions in single-turn conversations, exemplified by systems such as ChatGPT, ChatGLM, ChatDoctor, DoctorGLM, and etc. However, the limited information provided by users during single turn results in inadequate personalization and targeting of the generated suggest

TRAPPIST-1 JWST Community Initiative, :, Julien de Wit, René Doyon

Ultra-cool dwarf stars are abundant, long-lived, and uniquely suited to enable the atmospheric study of transiting terrestrial companions with JWST. Amongst them, the most prominent is the M8.5V star TRAPPIST-1 and its seven planets. While JWST Cycle 1 observations have started to yield preliminary insights into the planets, they have also revealed that thei

Freya Behrens, Barbora Hudcová, Lenka Zdeborová

Discrete dynamical systems can exhibit complex behaviour from the iterative application of straightforward local rules. A famous example are cellular automata whose global dynamics are notoriously challenging to analyze. To address this, we relax the regular connectivity grid of cellular automata to a random graph, which gives the class of graph cellular aut

Kang Zhou

We propose a new bottom up method to construct tree amplitudes of non-linear sigma model (NLSM) and special Galileon theory (SG), based on assuming the universality of soft behaviors and the double copy structure. We extend the on-shell amplitudes to off-shell ones with two off-shell external legs, which allow the numbers of external legs to be odd. Then the

Marie-Eve Boulanger, Lu Chen, Vincent Oliviero, David Vignolles

It has recently become clear that phonons generate a sizable thermal Hall effect in cuprates, whether they are undoped, electron-doped or hole-doped (inside the pseudogap phase). At higher doping, where cuprates are reasonably good metals, mobile electrons also generate a thermal Hall effect, the thermal equivalent of the standard electrical Hall effect. Her

S. D. Seddon, A. Cooper, T. Fricke, S. G. Ebbinghaus

Magnetite has long been investigated across many disciplines due to the interplay between its ferroic order parameters, namely its ferrimagnetism, ferroelasticity and ferroelectricty. Despite this, the experimental difficulty in measuring low temperature real space images of the ferroelectric domains has meant that the local behaviour of ferroelectric domain

Sai Aparna Aketi, Kaushik Roy

The current state-of-the-art decentralized learning algorithms mostly assume the data distribution to be Independent and Identically Distributed (IID). However, in practical scenarios, the distributed datasets can have significantly heterogeneous data distributions across the agents. In this work, we present a novel approach for decentralized learning on het

Laetitia Mottet

The Indoor Geometry Generator (IGG) is able to generate automatically simplified indoor geometry and its associated unstructured mesh for Computational Fluid Dynamics (CFD) simulations purposes given very simple user inputs. A large number of indoor features are supported by IGG such as (non-exhaustive list): shelves, tills, tables, chairs, seats... Smaller