October 2023 arXiv papers — page 59

Tenghao Huang, Ehsan Qasemi, Bangzheng Li, He Wang

Storytelling's captivating potential makes it a fascinating research area, with implications for entertainment, education, therapy, and cognitive studies. In this paper, we propose Affective Story Generator (AffGen) for generating interesting narratives. AffGen introduces "intriguing twists" in narratives by employing two novel techniques-Dynamic Beam Sizing

Klaus Deckelnick, Philip J. Herbert, Michael Hinze

Built upon previous work of the authors in (Deckelnick, Herbert, and Hinze, ESAIM: COCV 28 (2022)), we present a general shape optimisation framework based on the method of mappings in the $W^{1,\infty}$ topology together with a suitable finite element discretisation. For the numerical solution of the respective discrete shape optimisation problems we propos

Ronald Cardenas, Bingsheng Yao, Dakuo Wang, Yufang Hou

Science journalism refers to the task of reporting technical findings of a scientific paper as a less technical news article to the general public audience. We aim to design an automated system to support this real-world task (i.e., automatic science journalism) by 1) introducing a newly-constructed and real-world dataset (SciTechNews), with tuples of a publ

Veronica Arena, Andrea Di Lorenzo, Giovanni Inchiostro, Siddharth Mathur

We establish a criterion for determining when a smooth Deligne-Mumford stack is a weighted blow-up. More precisely, given a smooth Deligne-Mumford stack $\mathcal{X}$ and a Cartier divisor $\mathcal{E} \subset \mathcal{X}$ such that (1) $\mathcal{E}$ is a weighted projective bundle over a smooth Deligne-Mumford stack $\mathcal{Y}$ and (2) for every $y\in\mat

Fangyu Lei, Tongxu Luo, Pengqi Yang, Weihao Liu

Table-based question answering (TableQA) is an important task in natural language processing, which requires comprehending tables and employing various reasoning ways to answer the questions. This paper introduces TableQAKit, the first comprehensive toolkit designed specifically for TableQA. The toolkit designs a unified platform that includes plentiful Tabl

Xiaoyun Liu, Divya Saxena, Jiannong Cao, Yuqing Zhao

Neural architecture search (NAS) has gained significant traction in automating the design of neural networks. To reduce search time, differentiable architecture search (DAS) reframes the traditional paradigm of discrete candidate sampling and evaluation into a differentiable optimization over a super-net, followed by discretization. However, most existing DA

Jinyu Li, Xiaokun Pan, Gan Huang, Ziyang Zhang

It is typically challenging for visual or visual-inertial odometry systems to handle the problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems. Firstly, we propose an IMU-PARSAC algorithm which can robustly detect and match keypoints in a two-stag

J. Khatua, B. Sana, A. Zorko, M. Gomilšek

Frustration in magnetic materials arising from competing exchange interactions can prevent the system from adopting long-range magnetic order and can instead lead to a diverse range of novel quantum and topological states with exotic quasiparticle excitations. Here, we review prominent examples of such emergent phenomena, including magnetically-disordered an

Qingning Zhou, Kin Yau Wong

The case-cohort design is a commonly used cost-effective sampling strategy for large cohort studies, where some covariates are expensive to measure or obtain. In this paper, we consider regression analysis under a case-cohort study with interval-censored failure time data, where the failure time is only known to fall within an interval instead of being exact

Benjamin B Chu, Jiaqi Gu, Zhaomeng Chen, Tim Morrison

Conditional testing via the knockoff framework allows one to identify -- among large number of possible explanatory variables -- those that carry unique information about an outcome of interest, and also provides a false discovery rate guarantee on the selection. This approach is particularly well suited to the analysis of genome wide association studies (GW

Eymen Ünay, Bora İnan, Emrecan Yiğit

The rise of hardware accelerators with custom instructions necessitates custom compiler backends supporting these accelerators. This study provides detailed analyses of LLVM and its RISC-V backend, supplemented with case studies providing end-to-end overview of the mentioned transformations. We discuss that instruction design should consider both hardware an

B. A. Nicholson, S. Aigrain, N. L. Eisner, M. Cretignier

We present the characterisation of the two transiting planets around HD 152843 (TOI 2319, TIC 349488688) using an intensive campaign of HARPS-N radial velocities, and two sectors of TESS data. These data reveal a unique and fascinating system: HD 152843 b and c have near equal masses of around 9 M$_\oplus$ but differing radii of $3.05 \pm 0.11$ R$_\oplus$ an

M. Koussour, N. Myrzakulov, Alnadhief H. A. Alfedeel, Amare Abebe

Despite the significant accomplishments of general relativity, numerous unresolved issues persist in our understanding of the cosmos. One of the most perplexing challenges is the ongoing accelerated expansion of the Universe, which continues to elude a complete explanation. Consequently, scientists have proposed various alternative theories to GR in pursuit

Te-Lin Wu, Yu Zhou, Nanyun Peng

The ability to actively ground task instructions from an egocentric view is crucial for AI agents to accomplish tasks or assist humans virtually. One important step towards this goal is to localize and track key active objects that undergo major state change as a consequence of human actions/interactions to the environment without being told exactly what/whe

Qingxiao Zheng, Zhongwei Xu, Abhinav Choudhry, Yuting Chen

This empirical study serves as a primer for interested service providers to determine if and how Large Language Models (LLMs) technology will be integrated for their practitioners and the broader community. We investigate the mutual learning journey of non-AI experts and AI through CoAGent, a service co-creation tool with LLM-based agents. Engaging in a thre

Jeffrey Shallit, Arseny M. Shur, Stefan Zorcic

We revisit the topic of power-free morphisms, focusing on the properties of the class of complementary morphisms. Such morphisms are defined over a $2$-letter alphabet, and map the letters 0 and 1 to complementary words. We prove that every prefix of the famous Thue-Morse word $\mathbf{t}$ gives a complementary morphism that is $3^+$-free and hence $\alpha$-

Giuseppe Fabiano, Flavio Mercati

In this study, we construct a 1+1-dimensional, relativistic, free, complex scalar Quantum Field Theory on the noncommutative spacetime known as lightlike $\kappa$-Minkowski. The associated $\kappa$-Poincar\'e quantum group of isometries is triangular, and its quantum R matrix enables the definition of a braided algebra of N points that retains $\kappa$-Poinc

A. Scordo, L. Abbene, F. Artibani, M. Bazzi

The SIDDHARTA-2 collaboration at the INFN Laboratories of Frascati (LNF) aims to perform groundbreaking measurements on kaonic atoms. In parallel and beyond the ongoing kaonic deuterium, presently running on the DA$\Phi$NE collider at LNF, we plan to install additional detectors to perform further kaonic atoms' studies, taking advantage of the unique low ene

Xinyi Chen, Raquel Fernández, Sandro Pezzelle

Despite the impressive performance achieved by pre-trained language-and-vision models in downstream tasks, it remains an open question whether this reflects a proper understanding of image-text interaction. In this work, we explore to what extent they handle basic linguistic constructions -- active-passive voice, coordination, and relative clauses -- that ev

Diwen Chang, Jin Gao, Zhenyu Yu, Junda Zhang

In this paper, we study the weak monotonicity property of p-energy related Korevaar-Schoen norms on connected nested fractals for $1 < p < \infty$. Such property has many important applications on fractals and other metric measure spaces, such as constructing p-energies (when $p = 2$ this is basically a Dirichlet form), generalizing the classical Sobolev typ

Iman Nematollahi, Kirill Yankov, Wolfram Burgard, Tim Welschehold

A long-standing challenge for a robotic manipulation system operating in real-world scenarios is adapting and generalizing its acquired motor skills to unseen environments. We tackle this challenge employing hybrid skill models that integrate imitation and reinforcement paradigms, to explore how the learning and adaptation of a skill, along with its core gro

Congkai Huang

We prove that in every metric space where no line contains all the points, there are at least $\Omega(n^{2/3})$ lines. This improves the previous $\Omega(\sqrt{n})$ lower bound on the number of lines in general metric space, and also improves the previous $\Omega(n^{4/7})$ lower bound on the number of lines in metric spaces generated by connected graphs.

Chaopeng Zhang, Wenshuo Wang, Zhaokun Chen, Jian Zhang

Driving style is usually used to characterize driving behavior for a driver or a group of drivers. However, it remains unclear how one individual's driving style shares certain common grounds with other drivers. Our insight is that driving behavior is a sequence of responses to the weighted mixture of latent driving styles that are shareable within and betwe

Tho Nguyen Duc

The purpose of this article is to study pseudospectral properties of the one-dimensional Schr\"{o}dinger operator perturbed by a complex steplike potential. By constructing the resolvent kernel, we show that the pseudospectrum of this operator is trivial if and only if the imaginary part of the potential is constant. As a by-product, a new method to obtain a

Tin Nguyen, Jiannan Xu, Aayushi Roy, Hal Daumé

Recent research at the intersection of AI explainability and fairness has focused on how explanations can improve human-plus-AI task performance as assessed by fairness measures. We propose to characterize what constitutes an explanation that is itself "fair" -- an explanation that does not adversely impact specific populations. We formulate a novel evaluati

Jack Good, Jimit Majmudar, Christophe Dupuy, Jixuan Wang

Continual Federated Learning (CFL) combines Federated Learning (FL), the decentralized learning of a central model on a number of client devices that may not communicate their data, and Continual Learning (CL), the learning of a model from a continual stream of data without keeping the entire history. In CL, the main challenge is \textit{forgetting} what was

Jian Qin, Pengjie Zhang, Haojie Xu, Yu Yu

Alternative to weak lensing measurements through cosmic shear, we present a weak lensing convergence $\hat{\kappa}$ map reconstructed through cosmic magnification effect in DECaLS galaxies of the DESI imaging surveys DR9. This is achieved by linearly weighing $12$ maps of galaxy number overdensity in different magnitude bins of $grz$ photometry bands. The we

Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu

Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones. This is essential for addressing the challenges of data storage and training costs. Prevalent methods facilitate knowledge transfer by matching the gradients, embedding distributions, or training trajectories of sy

Ali Maatouk, Fadhel Ayed, Nicola Piovesan, Antonio De Domenico

We introduce TeleQnA, the first benchmark dataset designed to evaluate the knowledge of Large Language Models (LLMs) in telecommunications. Comprising 10,000 questions and answers, this dataset draws from diverse sources, including standards and research articles. This paper outlines the automated question generation framework responsible for creating this d

Haojia Li, Haokun Wang, Chen Feng, Fei Gao

The robotics community is increasingly interested in autonomous aerial transportation. Unmanned aerial vehicles with suspended payloads have advantages over other systems, including mechanical simplicity and agility, but pose great challenges in planning and control. To realize fully autonomous aerial transportation, this paper presents a systematic solution

Francesca Bianchi, Enis Kaya, J. Steffen Müller

We develop a theory of $p$-adic N\'eron functions on abelian varieties, depending on various auxiliary choices, and show that the global $p$-adic height functions constructed by Mazur and Tate can be decomposed into a sum of $p$-adic N\'eron functions if the same auxiliary choices are made. We also consider a decomposition of the $p$-adic height constructed

Chengyue Song, Jun Wang

We present a fast adaptive method for the evaluation of heat potentials, which plays a key role in the integral equation approach for the solution of the heat equation, especially in a non-stationary domain. The algorithm utilizes a sum-of-exponential based fast Gauss transform that evaluates the convolution of a Gaussian with either discrete or continuous v

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec, Tegan Maharaj

We demonstrate that LLMs may learn indicators of document usefulness and modulate their updates accordingly. We introduce random strings ("tags") as indicators of usefulness in a synthetic fine-tuning dataset. Fine-tuning on this dataset leads to implicit meta-learning (IML): in further fine-tuning, the model updates to make more use of text that is tagged a

Saswat Mishra, Alejandro Strachan

The crystallization of complex, concentrated alloys can result in atomic-level short-range order, composition gradients, and phase separation. These features govern the properties of the resulting alloy. While nucleation and growth in single-element metals are well understood, several open questions remain regarding the crystallization of multi-principal com

Navid Keshtiarast, Pradyumna Kumar Bishoyi, Marina Petrova

Joint communication and sensing (JCAS) networks are envisioned as a key enabler for a variety of applications which demand reliable wireless connectivity along with accurate and robust sensing capability. When sensing and communication share the same spectrum, the communication links in the JCAS networks experience interference from both sensing and communic

Banafsheh Adami, Sara Tehranipoor, Nasser Nasrabadi, Nima Karimian

With the increasing integration of smartphones into our daily lives, fingerphotos are becoming a potential contactless authentication method. While it offers convenience, it is also more vulnerable to spoofing using various presentation attack instruments (PAI). The contactless fingerprint is an emerging biometric authentication but has not yet been heavily

Yusuke Akamatsu, Terumi Umematsu, Hitoshi Imaoka

Video-based heart and respiratory rate measurements using facial videos are more useful and user-friendly than traditional contact-based sensors. However, most of the current deep learning approaches require ground-truth pulse and respiratory waves for model training, which are expensive to collect. In this paper, we propose CalibrationPhys, a self-supervise

Jonathan Vandenburgh

Trusting machine learning algorithms requires having confidence in their outputs. Confidence is typically interpreted in terms of model reliability, where a model is reliable if it produces a high proportion of correct outputs. However, model reliability does not address concerns about the robustness of machine learning models, such as models relying on the

Markus Banagl, Jörg Schürmann, Dominik J. Wrazidlo

Brasselet, the second author and Yokura introduced Hodge-theoretic Hirzebruch-type characteristic classes $IT_{1, \ast}$, and conjectured that they are equal to the Goresky-MacPherson $L$-classes for pure-dimensional compact complex algebraic varieties. In this paper, we show that the framework of Gysin coherent characteristic classes of singular complex alg

Xinyu Yang, Jizhe Zhou

In artificial intelligence, any model that wants to achieve a good result is inseparable from a large number of high-quality data. It is especially true in the field of tamper detection. This paper proposes a modified total variation noise reduction method to acquire high-quality tampered images. We automatically crawl original and tampered images from the B

Bingzhi Li, Lucia Donatelli, Alexander Koller, Tal Linzen

The goal of compositional generalization benchmarks is to evaluate how well models generalize to new complex linguistic expressions. Existing benchmarks often focus on lexical generalization, the interpretation of novel lexical items in syntactic structures familiar from training; structural generalization tasks, where a model needs to interpret syntactic st

Qiaoyang Hao, Shenwei Zhou, Huigen Liu

Terrestrial planets in the habitable zone around nearby stars are of great interest and provide a good sample for further characteristics of their habitability. In this paper, we collect a nearby star catalog within 20 pc according to the Gaia Catalog of Nearby Stars, complete the physical parameters of the stars, and select stars that are not brown dwarfs o

Ž. Bajuk, M. Brešar, P. Fagundes, A. Ioppolo

Let $f=f(x_1,\dots,x_m)$ be a multilinear polynomial over a field $F$. An $F$-algebra $A$ is said to be $f$-zpd ($f$-zero product determined) if every $m$-linear functional $\varphi\colon A^{m}\rightarrow F$ which preserves zeros of $f$ is of the form $\varphi(a_1,\dots,a_m)=\tau(f(a_1,\dots,a_m))$ for some linear functional $\tau$ on $A$. We are primarily i

Antonio Sannia, Francesco Tacchino, Ivano Tavernelli, Gian Luca Giorgi

Variational quantum algorithms represent a powerful approach for solving optimization problems on noisy quantum computers, with a broad spectrum of potential applications ranging from chemistry to machine learning. However, their performances in practical implementations crucially depend on the effectiveness of quantum circuit training, which can be severely

Abhishek Sebastian, Pragna R

Our paper presents a robust framework for UWB-based static gesture recognition, leveraging proprietary UWB radar sensor technology. Extensive data collection efforts were undertaken to compile datasets containing five commonly used gestures. Our approach involves a comprehensive data pre-processing pipeline that encompasses outlier handling, aspect ratio-pre

Philip Arathoon

We consider the task of classifying relative equilibria for mechanical systems with rotational symmetry. We divide relative equilibria into two natural groups: a generic class which we call normal, and a non-generic abnormal class. The eigenvalues of the locked inertia tensor descend to shape-space and endow it with the geometric structure of a 3-web with th

Fausto Colantoni

In this paper, we present a comprehensive study on the generalization of skew Brownian motion and two-sided sticky Brownian motion by considering non-local operators at the origin for the heat equations on the real line. To begin, we introduce Marchaud-type operators and Caputo-Dzherbashian-type operators, providing an in-depth exposition of their fundamenta

N. Banerjee, G. Stancari, M. K. Bossard, J. Brandt

The Integrable Optics Test Accelerator at Fermilab will explore beam dynamics in a ring with intense space-charge using 2.5 MeV proton beams with an incoherent tune shift approaching -0.5. We will use this machine to explore the interplay between electron cooling, intense space-charge, and coherent instabilities. In this contribution, we describe the machine

Ivano Basile, Ulf Danielsson, Suvendu Giri, Daniel Panizo

Dark bubble cosmology is an alternative paradigm to compactification, which can circumvent issues of moduli stabilization and scale separation. In this paper we investigate how electromagnetic fields can be incorporated in this framework. Worldvolume fields backreact on the ambient universe in which the bubble expands, which in turn affects the energy-moment

Feiyu Deng, Zhi Wang, Yang Zhou

End of the world branes in AdS have been recently used to study problems deeply connected to quantum gravity, such as black hole evaporation and holographic cosmology. With non-critical tension and Neumann boundary condition, the end of the world brane often represents part of the degrees of freedom in AdS gravity and geometrically it is only part of the ent

Philipp Stammer, Javier Rivera-Dean, Andrew S. Maxwell, Theocharis Lamprou

Squeezing of optical fields, used as a powerful resource for many applications, and the radiation properties in the process of high harmonic generation have thus far been considered separately. In this Letter, we want to clarify that the joint quantum state of all the optical field modes in the process of high harmonic generation is in general entangled and

David Sauzin

Resurgence Theory and Mould Calculus were invented by J. Ecalle around 1980 in the context of analytic dynamical systems and are increasingly more used in the mathematical physics community, especially since the 2010s. We review the mathematical formalism and touch on the applications. This is an invited contribution to the 2nd edition of the Encyclopedia of

Jun Liu

This paper proves that the imaginary part of the Riemann $\xi$ function is strictly monotonic with $b$ in the region $S = \{t|t=a+bi,\ 0\leq a \leq 9.508,\ -1/2<b<1/2\}$. That leads to Im($\xi$)=0 being true only when $b=0$ in $S$.

Marie Ygouf, Charles Beichman, Jorge Llop-Sayson, Geoffrey Bryden

We report observations with the JWST/NIRCam coronagraph of the Fomalhaut system. This nearby A star hosts a complex debris disk system discovered by the IRAS satellite. Observations in F444W and F356W filters using the round 430R mask achieve a contrast ratio of ~ 4 x 10-7 at 1'' and ~ 4 x 10-8 outside of 3''. These observations reach a sensitivity limit <1

Xinliang Zhang, Mojtaba Vaezi

A deep autoencoder (DAE)-based structure for endto-end communication over the two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed in this paper. The proposed structure jointly optimizes the two encoder/decoder pairs and generates interference-aware constellations that dynamically adapt their shape based on interference intensity to

Yi Huang, Yihui Ren, Shinjae Yoo, Jin Huang

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high-energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed

Mohammed A. M. Elhassan, Changjun Zhou, Amina Benabid, Abuzar B. M. Adam

Recently, Transformer-based models have achieved promising results in various vision tasks, due to their ability to model long-range dependencies. However, transformers are computationally expensive, which limits their applications in real-time tasks such as autonomous driving. In addition, an efficient local and global feature selection and fusion are vital

Ekene Attoh, Beat Signer

With the rise of popular task automation or IoT platforms such as 'If This Then That (IFTTT)', users can define rules to enable interactions between smart devices in their environment and thereby improve their daily lives. However, the rules authored via these platforms are usually tied to the platforms and sometimes even to the specific devices for which th

Samiran Gode, Akshay Hinduja, Michael Kaess

In this paper, we address the challenging problem of data association for underwater SLAM through a novel method for sonar image correspondence using learned features. We introduce SONIC (SONar Image Correspondence), a pose-supervised network designed to yield robust feature correspondence capable of withstanding viewpoint variations. The inherent complexity

Manuel H. Muñoz-Arias, Stefanos Kourtis, Alexandre Blais

We introduce a quantum-inspired approximation algorithm for MaxCut based on low-depth Clifford circuits. We start by showing that the solution unitaries found by the adaptive quantum approximation optimization algorithm (ADAPT-QAOA) for the MaxCut problem on weighted fully connected graphs are (almost) Clifford circuits. Motivated by this observation, we dev

Zhiyuan Fan, Shizhu He

Open Information Extraction (OpenIE) is a fundamental yet challenging task in Natural Language Processing, which involves extracting all triples (subject, predicate, object) from a given sentence. While labeling-based methods have their merits, generation-based techniques offer unique advantages, such as the ability to generate tokens not present in the orig

Bo Ai, Zhanxin Wu, David Hsu

The data-driven approach to robot control has been gathering pace rapidly, yet generalization to unseen task domains remains a critical challenge. We argue that the key to generalization is representations that are (i) rich enough to capture all task-relevant information and (ii) invariant to superfluous variability between the training and the test domains.

Apostol Vassilev, Honglan Jin, Munawar Hasan

Detecting out of policy speech (OOPS) content is important but difficult. While machine learning is a powerful tool to tackle this challenging task, it is hard to break the performance ceiling due to factors like quantity and quality limitations on training data and inconsistencies in OOPS definition and data labeling. To realize the full potential of availa

Ricardo A. C. Cipriano, Tiberiu Harko, Francisco S. N. Lobo, Miguel A. S. Pinto

In this work, we analyze the possibility of gravitationally induced matter creation in the so-called Energy-Momentum-Squared gravity (EMSG), i.e. $f(R,T_{\mu\nu}T^{\mu\nu})$ gravity, in its dynamically equivalent scalar-tensor representation. Given the explicit nonminimal coupling between matter and geometry in this theory, the energy-momentum tensor is not

Zhongjian Qiao, Jiafei Lyu, Xiu Li

The primacy bias in model-free reinforcement learning (MFRL), which refers to the agent's tendency to overfit early data and lose the ability to learn from new data, can significantly decrease the performance of MFRL algorithms. Previous studies have shown that employing simple techniques, such as resetting the agent's parameters, can substantially alleviate

Robin Denz, Katharina Meiszl, Peter Ihle, Doris Oberle

With unprecedented speed, 192,248,678 doses of Covid-19 vaccines were administered in Germany by July 11, 2023 to combat the pandemic. Limitations of clinical trials imply that the safety profile of these vaccines is not fully known before marketing. However, routine health-care data can help address these issues. Despite the high proportion of insured peopl

AmirHossein Naghshzan, Latifa Guerrouj, Olga Baysal

Usually, programming languages have official documentation to guide developers with APIs, methods, and classes. However, researchers identified insufficient or inadequate documentation examples and flaws with the API's complex structure as barriers to learning an API. As a result, developers may consult other sources (StackOverflow, GitHub, etc.) to learn mo

Florian Thieben, Fynn Foerger, Fabian Mohn, Niklas Hackelberg

Since the initial patent in 2001, the Magnetic Particle Imaging (MPI) community has been striving to develop an MPI scanner suitable for human applications. Numerous contributions from different research fields, regarding tracer development, reconstruction methods, hardware engineering, and sequence design have been employed in pursuit of this objective. In

Yi Zhao, Ruibin Li, Aytac Kubilay, Yongling Zhao

Urban warming is evident in numerous cities. On especially hot days, building surfaces warm up, leading to buoyancy-driven flows adjacent to these surfaces. The dynamics of the flow structures are largely influenced by the interplay between incoming wind and the buoyancy-driven flows. In this study, we used large eddy simulations and wind tunnel measurements

Nuwan Sriyantha Bandara, Dilshan Pramudith Bandara

The cohabitation of elephants and humans has evolved into a human-elephant conflict (HEC) due to the increasing loss of historical elephant habitations. Since HEC is a substantial threat to both species, advanced sensing methods are utilized to develop HEC prevention frameworks which still lack unification. Here, we propose an end-to-end automated framework

Xiaojin Ding, Yue Lei, Yulong Zou, Gengxin Zhang

A spectrum-sharing satellite-ground integrated network is conceived, consisting of a pair of non-geostationary orbit (NGSO) constellations and multiple terrestrial base stations, which impose the co-frequency interference (CFI) on each other. The CFI may increase upon increasing the number of satellites. To manage the potentially severe interference, we prop

Parker Seegmiller, Sarah Masud Preum

The popularity of transformer-based text embeddings calls for better statistical tools for measuring distributions of such embeddings. One such tool would be a method for ranking texts within a corpus by centrality, i.e. assigning each text a number signifying how representative that text is of the corpus as a whole. However, an intrinsic center-outward orde

Nicolas Chenavier, Moritz Otto

We establish Poisson and compound Poisson approximations for stabilizing statistics of $\beta$-mixing point processes and give explicit rates of convergence. Our findings are based on a general estimate of the total variation distance of a stationary $\beta$-mixing process and its Palm version. As main contributions, this article (i) extends recent results o

Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin, Yuan Liu

In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry from 2D diffusion priors, but they typically suffer from time-consuming per-shape optimization and inconsistent geometry.

Matthieu Meeus, Shubham Jain, Marek Rei, Yves-Alexandre de Montjoye

With large language models (LLMs) poised to become embedded in our daily lives, questions are starting to be raised about the data they learned from. These questions range from potential bias or misinformation LLMs could retain from their training data to questions of copyright and fair use of human-generated text. However, while these questions emerge, deve

Mohammad Akhlaghi

The pointing pattern is an integral part of designing one's observation strategy for a certain scientific goal. But accounting for the particular science case or instrument artifacts (like distortion, vignetting or large areas of bad pixels) can make it hard to predict how the exposure map of the final stack will be. To help address this problem, Gnuastro 0.

Alexey A. Sokolik, Yurii E. Lozovik

Edge magnetoplasmons arise on a boundary of conducting layer in perpendicular magnetic field due to an interplay of electron cyclotron motion and Coulomb repulsion. Lateral electric field, which confines electrons inside the sample, drives their spiraling motion in magnetic field along the edge with the average drift velocity contributing to the total magnet

Michael Hanna, Yonatan Belinkov, Sandro Pezzelle

Animacy - whether an entity is alive and sentient - is fundamental to cognitive processing, impacting areas such as memory, vision, and language. However, animacy is not always expressed directly in language: in English it often manifests indirectly, in the form of selectional constraints on verbs and adjectives. This poses a potential issue for transformer

Haitz Sáez de Ocáriz Borde, Anastasis Kratsios

The inductive bias of a graph neural network (GNN) is largely encoded in its specified graph. Latent graph inference relies on latent geometric representations to dynamically rewire or infer a GNN's graph to maximize the GNN's predictive downstream performance, but it lacks solid theoretical foundations in terms of embedding-based representation guarantees.

Delphine Porquet, Scott Hagen, Nicolas Grosso, Andrew Lobban

[Abridged] The X-ray broadband spectra of the bare AGN Mrk 110, obtained by simultaneous XMM-Newton and NuSTAR observations (Nov 2019 and April 2020), are characterised by the presence of a prominent and absorption-free smooth soft X-ray excess, moderately broad OVII and Fe Kalpha emission lines, and a lack of a strong Compton hump. While relativistic reflec

Mohammed Osman

We consider complex, weakly non-Hermitian matrices $A = W_1 +i\sqrt{{\tau}_N}W_2$ , where $W_1$ and $W_2$ are Hermitian matrices and $\tau_N = O(N^{-1})$. We first show that for pairs of Hermitian matrices $(W_1 , W_2)$ such that $W_1$ satisfies a multi-resolvent local law and $W_2$ is bounded in norm, the bulk correlation functions of the weakly non-Hermiti

Julien du Crest, Francisco Garcia-Herrero, Mehdi Mhalla, Valentin Savin

The inherent degeneracy of quantum low-density parity-check codes poses a challenge to their decoding, as it significantly degrades the error-correction performance of classical message-passing decoders. To improve their performance, a post-processing algorithm is usually employed. To narrow the gap between algorithmic solutions and hardware limitations, we

Lorenzo Quarisa, José L. Rodrigo

We consider the problem of the stability of the Navier-Stokes equations in $\mathbb{T}\times \mathbb{R}_+$ near shear flows which are linearly unstable for the Euler equation. In \cite{greniernguyen}, the authors prove an $L^{\infty}$ instability result for the no-slip boundary condition which also denies the validity of the Prandtl boundary layer expansion.

Mark Berezovik

In this paper we continue the study of symplectically self-polar convex bodies started in arXiv:2211.14630. We construct symplectically self-polar convex bodies of the minimal Ekeland-Hofer-Zehnder capacity. This in turn proves that the lower bound for the Ekeland-Hofer-Zehnder capacity for centrally symmetric convex bodies obtained in arXiv:1801.00242 canno

Wei Liu, Songlin Yang, Yoon Kim, Kewei Tu

Scaling dense PCFGs to thousands of nonterminals via a low-rank parameterization of the rule probability tensor has been shown to be beneficial for unsupervised parsing. However, PCFGs scaled this way still perform poorly as a language model, and even underperform similarly-sized HMMs. This work introduces \emph{SimplePCFG}, a simple PCFG formalism with inde

Simon Waid, Andreas Gsponer, Jürgen Maier, Philipp Gaggl

The extremely low dark current of silicon carbide (SiC) detectors, even after high-fluence irradiation, was utilized to develop a beam monitoring system for a wide range of particle rates, i.e., from the kHz to the GHz regime. The system is completely built from off-the-shelve components and is focused on compactness and simple deployment. Beam tests using a

Yun Li, Benedek Valkó

We study the scaling limit of the rank-one truncation of various beta ensemble generalizations of classical unitary/orthogonal random matrices: the circular beta ensemble, the real orthogonal beta ensemble, and the circular Jacobi beta ensemble. We derive the scaling limit of the normalized characteristic polynomials and the point process limit of the eigenv

Hussein Mesmar, Frédéric Robert

We perform the apriori analysis of solutions to critical nonlinear elliptic equations on manifolds with boundary. The solutions are of minimizing type. The originality is that we impose no condition on the boundary, which leads us to assume $L^2-$concentration. We also analyze the effect of a non-homogeneous nonlinearity that results in the fast convergence

Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan Tu

As language models are applied to an increasing number of real-world applications, understanding their inner workings has become an important issue in model trust, interpretability, and transparency. In this work we show that representation dissimilarity measures, which are functions that measure the extent to which two model's internal representations diffe

Thomas Falconer, Jalal Kazempour, Pierre Pinson

Although machine learning tasks are highly sensitive to the quality of input data, relevant datasets can often be challenging for firms to acquire, especially when held privately by a variety of owners. For instance, if these owners are competitors in a downstream market, they may be reluctant to share information. Focusing on supervised learning for regress

Javier Cembrano, Svenja M. Griesbach, Maximilian J. Stahlberg

In the impartial selection problem, a subset of agents up to a fixed size $k$ among a group of $n$ is to be chosen based on votes cast by the agents themselves. A selection mechanism is impartial if no agent can influence its own chance of being selected by changing its vote. It is $\alpha$-optimal if, for every instance, the ratio between the votes received

Yuxi Lu, Ruth Angus, Daniel Foreman-Mackey, Soichiro Hattori

Gyrochronology, the field of age-dating stars using mainly their rotation periods and masses, is ideal for inferring the ages of individual main-sequence stars. However, due to the lack of physical understanding of the complex magnetic fields in stars, gyrochronology relies heavily on empirical calibrations that require consistent and reliable stellar age me

Steven Creech

In 2005, E. Noel and G. Panos constructed a formula to count the number of semiprimes less than a given value $x$. In 2006, this formula was rediscovered independently by R.G. Wilson V. However, each citation of this result was simply through personal communication, and a formal proof has not been written down anywhere in the literature. In this article, we

Matthijs Borst, Martijn Caspers

Let $W$ be a finitely generated right-angled Coxeter group with group von Neumann algebra $\mathcal{L}(W)$. We prove the following dichotomy: either $\mathcal{L}(W)$ is strongly solid or $W$ contains $\mathbb{Z} \times \mathbb{F}_2$ as a subgroup. This proves in particular strong solidity of $\mathcal{L}(W)$ for all non-hyperbolic Coxeter groups that do not

Amaury H. M. J. Triaud, Julien de Wit, Frieder Klein, Martin Turbet

The conventional observables to identify a habitable or inhabited environment in exoplanets, such as an ocean glint or abundant atmospheric O$_2$, will be challenging to detect with present or upcoming observatories. Here we suggest a new signature. A low carbon abundance in the atmosphere of a temperate rocky planet, relative to other planets of the same sy

Maria Cywinska, Mikolaj Rogalski, Filip Brzeski, Krzysztof Patorski

Fringe pattern based measurement techniques are the state-of-the-art in full-field optical metrology. They are crucial both in macroscale, e.g., fringe projection profilometry, and microscale, e.g., label-free quantitative phase microscopy. Accurate estimation of the local fringe orientation map can significantly facilitate the measurement process on various

Philip Janicki

A real number is called left-computable if there exists a computable increasing sequence of rational numbers converging to it. In this article we are investigating a proper subset of the left-computable numbers. We say that a real number $x$ is reordered computable if there exist a computable function $f \colon \mathbb{N} \to \mathbb{N}$ with $\sum_{k=0}^{\i

Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang

This paper explores the open research problem of understanding the social behaviors of LLM-based agents. Using Avalon as a testbed, we employ system prompts to guide LLM agents in gameplay. While previous studies have touched on gameplay with LLM agents, research on their social behaviors is lacking. We propose a novel framework, tailored for Avalon, feature

Andrea Tocchetti, Silvia Maria Talenti, Marco Brambilla

During the Covid-19 pandemic, research communities focused on collecting and understanding people's behaviours and feelings to study and tackle the pandemic indirect effects. Despite its consequences are slowly starting to fade away, such an interest is still alive. In this article, we propose a hybrid, gamified, story-driven data collection approach to spar

Michael Terry, Chinmay Kulkarni, Martin Wattenberg, Lucas Dixon

Modern AI enables a high-level, declarative form of interaction: Users describe the intended outcome they wish an AI to produce, but do not actually create the outcome themselves. In contrast, in traditional user interfaces, users invoke specific operations to create the desired outcome. This paper revisits the basic input-output interaction cycle in light o