October 2023 arXiv papers — page 73

Alex H. Lumpkin, Henry P. Freund, Matthias Reinsch, Peter J. M. van der Slot

The Fermilab Accelerator Science and Technology (FAST) facility is currently in operation with its linac based on TESLA-type superconducting rf cavities. Using a 3-MHz micropulse repetition rate with a long macropulse composed of up to 3000 micropulses, and with beam energies demonstrated at 300 MeV and projected to reach 800 MeV with two additional cryomodu

K. D. Belashchenko

Crystallographic anisotropy of the spin-dependent conductivity tensor can be exploited to generate transverse spin-polarized current in a ferromagnetic film. This ferromagnetic spin Hall effect is analogous to the spin-splitting effect in altermagnets and does not require spin-orbit coupling. First-principles screening of 41 non-cubic ferromagnets revealed t

Kaustubh Agashe, Sagar Airen, Roberto Franceschini, Doojin Kim

We show that the $m_W$ measurement is a direct probe of New Physics (NP) contributing to lepton and missing transverse momentum ($\ell+MET$), independently from indirect tests via the electroweak fit. Such NP modifies the kinematic distributions used to extract $m_W$, necessitating a simultaneous fit to $m_W$ and NP. This effect can in principle bias the $m_

Jordan Kodner, Salam Khalifa, Sarah Payne

Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supplement that approach with language-specific probes designed to test aspects of morphological generalization. Testing these probes on three morphologically distinct languages, Engli

Ryo Higuchi, Syuhei Iguro, Shohei Okawa, Yuji Omura

We study phenomenology of a light scalar dark matter (DM). In the model, there are an inert doublet scalar and a singlet Dirac fermion $\psi$, both charged under a global $Z_2$ symmetry. The mass of the lightest inert scalar $H$ can be lighter than 10 GeV by imposing appropriate relations between three scalar quartic couplings. The lightest $Z_2$ odd particl

Nikolay Kuznetsov

One isoperimetric inequality for the fundamental sloshing eigenvalue is derived under the assumption that containers have vertical side walls and either finite or infinite depth. It asserts that among all such containers, whose free surfaces are convex, have two axes of symmetry and a given perimeter length, this eigenvalue is maximized by infinitely deep on

Gabriel Oliveira dos Santos, Diego A. B. Moreira, Alef Iury Ferreira, Jhessica Silva

This work introduces CAPIVARA, a cost-efficient framework designed to enhance the performance of multilingual CLIP models in low-resource languages. While CLIP has excelled in zero-shot vision-language tasks, the resource-intensive nature of model training remains challenging. Many datasets lack linguistic diversity, featuring solely English descriptions for

Moshe Berchansky, Peter Izsak, Avi Caciularu, Ido Dagan

Fusion-in-Decoder (FiD) is an effective retrieval-augmented language model applied across a variety of open-domain tasks, such as question answering, fact checking, etc. In FiD, supporting passages are first retrieved and then processed using a generative model (Reader), which can cause a significant bottleneck in decoding time, particularly with long output

Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, Furqan Khan

Edge device participation in federating learning (FL) is typically studied through the lens of device-server communication (e.g., device dropout) and assumes an undying desire from edge devices to participate in FL. As a result, current FL frameworks are flawed when implemented in realistic settings, with many encountering the free-rider dilemma. In a step t

Jiongzhi Zheng, Changpeng Lin, Chongjia Lin, Baoling Huang

Fundamental understanding of thermal transport in compounds with ultra-low thermal conductivity remains challenging, primarily due to the limitations of conventional lattice dynamics and heat transport models. In this study, we investigate the thermal transport in quasi-one-dimensional (1D) copper halide CsCu2I3 by employing a combination of first principles

Fernando J. Barros

Simulation models have been described using different perspectives, or worldviews. In the process interaction world view (PI), every entity is modeled by a sequence of actions describing its life cycle, offering a comprehensive model that groups the events involving each entity. In this paper we describe piHyFlow, a formalism for representing hybrid models u

Razieh Veisi, Nahal Hadi, Shahram Nazarian, Javad Fathi

Background: Shigella is one of the major cause of dysenteric diarrhea, which is known shigelosis. Shigelosis causes 160,000 deaths annually of diarrheal disease in a global scale especially children less than 5 years old. No licensed vaccine is available against shigelosis, therefore, efforts for develop an effective and safe vaccine against shigella as befo

Mame Gor Ngom, Ibrahima Faye, Diaraf Seck

Coastal erosion is a major and growing environmental problem describing the movement of sand caused by tides, waves or currents. Several phenomena contribute to the significant advance of the sea. These include climate change, with rising sea levels due to the melting of ice at the Earth's poles, the amplification of the tidal effect, leading to the transpor

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini, Alberto Del Bimbo

Analog magnetic tapes have been the main video data storage device for several decades. Videos stored on analog videotapes exhibit unique degradation patterns caused by tape aging and reader device malfunctioning that are different from those observed in film and digital video restoration tasks. In this work, we present a reference-based approach for the res

Arya D. McCarthy, Hao Zhang, Shankar Kumar, Felix Stahlberg

One challenge in speech translation is that plenty of spoken content is long-form, but short units are necessary for obtaining high-quality translations. To address this mismatch, we adapt large language models (LLMs) to split long ASR transcripts into segments that can be independently translated so as to maximize the overall translation quality. We overcom

Samyadeep Basu, Nanxuan Zhao, Vlad Morariu, Soheil Feizi

Text-to-Image Diffusion Models such as Stable-Diffusion and Imagen have achieved unprecedented quality of photorealism with state-of-the-art FID scores on MS-COCO and other generation benchmarks. Given a caption, image generation requires fine-grained knowledge about attributes such as object structure, style, and viewpoint amongst others. Where does this in

Teodora Mihailescu, David H. Brooks, J. Martin Laming, Deborah Baker

The plasma composition of the solar corona is different from that of the solar photosphere. Elements that have a low first ionisation potential (FIP) are preferentially transported to the corona and, therefore, show enhanced abundances in the corona compared to the photosphere. The level of enhancement is measured using the FIP bias parameter. In this work,

Mario Giulianelli, Sarenne Wallbridge, Raquel Fernández

We present information value, a measure which quantifies the predictability of an utterance relative to a set of plausible alternatives. We introduce a method to obtain interpretable estimates of information value using neural text generators, and exploit their psychometric predictive power to investigate the dimensions of predictability that drive human com

Jiahao Xu, Yubin Ruan, Wei Bi, Guoping Huang

Back translation (BT) is one of the most significant technologies in NMT research fields. Existing attempts on BT share a common characteristic: they employ either beam search or random sampling to generate synthetic data with a backward model but seldom work studies the role of synthetic data in the performance of BT. This motivates us to ask a fundamental

Haojiang Ying, Yi-Fan Li, Yiyang Chen

Convolutional neural network (CNN), as an important model in artificial intelligence, has been widely used and studied in different disciplines. The computational mechanisms of CNNs are still not fully revealed due to the their complex nature. In this study, we focused on 4 extensively studied CNNs (AlexNet, VGG11, VGG13, and VGG16) which has been analyzed a

Sullam Jeoung, Yubin Ge, Jana Diesner

Large Language Models (LLMs) have been observed to encode and perpetuate harmful associations present in the training data. We propose a theoretically grounded framework called StereoMap to gain insights into their perceptions of how demographic groups have been viewed by society. The framework is grounded in the Stereotype Content Model (SCM); a well-establ

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini, Alberto Del Bimbo

No-Reference Image Quality Assessment (NR-IQA) aims to develop methods to measure image quality in alignment with human perception without the need for a high-quality reference image. In this work, we propose a self-supervised approach named ARNIQA (leArning distoRtion maNifold for Image Quality Assessment) for modeling the image distortion manifold to obtai

Mircea Merca, Maxie D. Schmidt

In this paper, we use the Lambert series generating function for Euler's totient function to introduce a new identity for the number of $1$'s in the partitions of $n$. A new expansion for Euler's partition function $p(n)$ is derived in this context. These surprising new results connect the famous classical totient function from multiplicative number theory t

Liliana Arrachea, Alfredo Levy Yeyati, Carlos Balseiro

We study the behavior of the conductance and the current-noise in three-terminal configurations of edge modes of a quantum Hall system in the nu=2 filling factor with normal and s-wave superconducting contacts. We discuss the impact of spin-orbit coupling in the quantum Hall system and the possibility of effectively inducing triplet pairing in the egde state

Ruida Wang, Wangchunshu Zhou, Mrinmaya Sachan

*Data Synthesis* is a promising way to train a small model with very little labeled data. One approach for data synthesis is to leverage the rich knowledge from large language models to synthesize pseudo training examples for small models, making it possible to achieve both data and compute efficiency at the same time. However, a key challenge in data synthe

Daiju Kanaoka, Motoharu Sonogashira, Hakaru Tamukoh, Yasutomo Kawanishi

Novel view synthesis has recently made significant progress with the advent of Neural Radiance Fields (NeRF). DietNeRF is an extension of NeRF that aims to achieve this task from only a few images by introducing a new loss function for unknown viewpoints with no input images. The loss function assumes that a pre-trained feature extractor should output the sa

Philip John Gorinski, Matthieu Zimmer, Gerasimos Lampouras, Derrick Goh Xin Deik

The advent of large pre-trained language models in the domain of Code Synthesis has shown remarkable performance on various benchmarks, treating the problem of Code Generation in a fashion similar to Natural Language Generation, trained with a Language Modelling (LM) objective. In addition, the property of programming language code being precisely evaluable

Claudio Fiandrino, Leonardo Bonati, Salvatore D'Oro, Michele Polese

The Open Radio Access Network (RAN) paradigm is transforming cellular networks into a system of disaggregated, virtualized, and software-based components. These self-optimize the network through programmable, closed-loop control, leveraging Artificial Intelligence (AI) and Machine Learning (ML) routines. In this context, Deep Reinforcement Learning (DRL) has

Anna C Nelson, Melissa M Rolls, Maria-Veronica Ciocanel, Scott A McKinley

The microtubule cytoskeleton is responsible for sustained, long-range intracellular transport of mRNAs, proteins, and organelles in neurons. Neuronal microtubules must be stable enough to ensure reliable transport, but they also undergo dynamic instability, as their plus and minus ends continuously switch between growth and shrinking. This process allows for

François-Xavier Lehr, Aukse Gaizauskaite, Katarzyna Elżbieta Lipińska, Sara Gilles

Cell-free transcription and translation (TXTL) systems have emerged as a powerful tool for testing genetic regulatory elements and circuits. Cell-free prototyping can dramatically accelerate the design-build-test cycle of new functions in synthetic biology, in particular when linear DNA templates are used. Here we describe a Golden Gate assisted workflow to

Eliseo Bao, Anxo Pérez, Javier Parapar

Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those conversations contain important traces about individuals' health risks. Recently, researchers have exploited this online information to construct mental health detection models, which aim to identify users at risk on platforms like Twitte

Walker Melton, Filip Niewinski, Andrew Strominger, Tianli Wang

Families of Lorentz, but not Poincare, invariant vacua are constructed for a massless scalar field in 4D Minkowski space. These are generalizations of the Rindler vacuum with a larger symmetry group. Explicit expressions are given as squeezed excitations of the Poincare vacuum. The effective reduced vacua on the 3D hyperbolic de Sitter slices are the well-kn

Ravikiran Hegde, Nirban Bose, Archana Pai

The three observational runs of advanced LIGO and Virgo detectors have detected $\sim$ 90 compact binary coalescence events with most of them being quasicircular compact binary merger events. Astrophysical models predict compact binary mergers with appreciable nonzero eccentricity if in dense stellar environments like globular clusters, active galactic nucle

Amr Keleg, Walid Magdy

Automatic Arabic Dialect Identification (ADI) of text has gained great popularity since it was introduced in the early 2010s. Multiple datasets were developed, and yearly shared tasks have been running since 2018. However, ADI systems are reported to fail in distinguishing between the micro-dialects of Arabic. We argue that the currently adopted framing of t

Arvind Rajaraman, Alexander Stewart, Christopher B. Verhaaren

We perform a general analysis of thin-wall Q-balls in AdS space. We provide numeric solutions and highly accurate analytic approximations over much of the parameter space. These analytic solutions show that AdS Q-balls exhibit significant differences from the corresponding flat space solitons. This includes having a maximum radius beyond which the Q-balls ar

Adithya Bhaskar, Tushar Tomar, Ashutosh Sathe, Sunita Sarawagi

Research in Text-to-SQL conversion has been largely benchmarked against datasets where each text query corresponds to one correct SQL. However, natural language queries over real-life databases frequently involve significant ambiguity about the intended SQL due to overlapping schema names and multiple confusing relationship paths. To bridge this gap, we deve

Mircea Merca, Maxie D. Schmidt

In this paper, we investigate decompositions of the partition function $p(n)$ from the additive theory of partitions considering the famous M\"{o}bius function $\mu(n)$ from multiplicative number theory. Some combinatorial interpretations are given in this context. Our work extends several analogous identities proved recently relating $p(n)$ and Euler's toti

Claudia Bucur

In this paper, we study the existence of solutions of the equation $(-\Delta)_1^s u=f$ in a bounded open set with Lipschitz boundary $\Omega\subset \Rn$, vanishing on $\Co \Omega$, for some given $s\in (0,1)$, and asymptotics as $p\to 1$ of solutions of $(-\Delta)_p^s u=f$. We obtain existence and convergence by comparing the $L^{\frac{n}{s}}$ norm of $f$ to

Samuel G. Gessow, Brett T. Lopez

This work presents a new sufficient condition for synthesizing nonlinear controllers that yield bounded closed-loop tracking error transients despite the presence of unmatched uncertainties that are concurrently being learned online. The approach utilizes contraction theory and addresses fundamental limitations of existing approaches by allowing the contract

Md. Taufiqul Haque Khan Tusar, Md. Touhidul Islam, Abul Hasnat Sakil

One of the most catastrophic neurological disorders worldwide is Parkinson's Disease. Along with it, the treatment is complicated and abundantly expensive. The only effective action to control the progression is diagnosing it in the early stage. However, this is challenging because early detection necessitates a large and complex clinical study. This experim

Tam Le, Truyen Nguyen, Kenji Fukumizu

We study optimal transport (OT) problem for probability measures supported on a tree metric space. It is known that such OT problem (i.e., tree-Wasserstein (TW)) admits a closed-form expression, but depends fundamentally on the underlying tree structure over supports of input measures. In practice, the given tree structure may be, however, perturbed due to n

Andrey V. Matetskiy, Valeria Milotti, Polina M. Sheverdyaeva, Paolo Moras

Dimensionality can strongly influence the magnetic structure of solid systems. Here, we predict theoretically and confirm experimentally that the antiferromagnetic (AFM) ground state of bulk gadolinium germanide metalloxene, which has a quasi-layered defective GdGe$_2$ structure, is preserved in the ultrathin film limit. \textit{Ab initio} calculations demon

Hannah Dell, Augustinas Jacovskis, Franco Rota

Let $Y$ admit a rectangular Lefschetz decomposition of its derived category, and consider a cyclic cover $X\to Y$ ramified over a divisor $Z$. In a setting not considered by Kuznetsov and Perry, we define a subcategory $\mathcal{A}_Z$ of the equivariant derived category of $X$ which contains, rather than is contained in, $\mathrm{D}^{\mathrm{b}}(Z)$. We then

Haodong Duan, Jueqi Wei, Chonghua Wang, Hongwei Liu

Interacting with human via high-quality multi-turn dialogues is a key feature of large language models (LLMs). However, human-based evaluation of such capability involves intensive manual labor. This report provides a preliminary evaluation of existing large language models for human-style multi-turn chatting, through an LLM-based approach. We start from rea

Miklos Bona

We use a recent result of Alin Bostan to prove that the generating functions of two infinite sequences of permutation classes are not algebraic.

Zixuan Wang, Haoran Tang, Haibo Wang, Bo Qin

Despite the remarkable results that can be achieved by data-driven intelligent fault diagnosis techniques, they presuppose the same distribution of training and test data as well as sufficient labeled data. Various operating states often exist in practical scenarios, leading to the problem of domain shift that hinders the effectiveness of fault diagnosis. Wh

Muhammad Waseem, Teerath Das, Aakash Ahmad, Peng Liang

Artificial Intelligence has demonstrated its significance in software engineering through notable improvements in productivity, accuracy, collaboration, and learning outcomes. This study examines the impact of generative AI tools, specifically ChatGPT, on the software development experiences of undergraduate students. Over a three-month project with seven st

Athul Krishna Sundarrajan, Yong Hoon Lee, James T Allison, Daniel Zalkind

This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines in an integrated manner using linear parameter-varying models. Multiple linearized models derived from aeroelastic simulation software in different operating regions characterized by the incoming wind speed are combined to construct an app

Bom Soo Kim

We observe significant, 6.5 - 12%, differences between skyrmion and antiskyrmion Hall angles in existing experimental data. To account for them, the Thiele equation is generalized with the transverse velocity component in the collective coordinate of magnetization vector. The corresponding generalized Hall angle is formulated, and its consequences are compar

Mattia Villani

In this work, we aim at solving the Teukolsky equations for a fermion with mass $m_e\neq 0$ in the presence of a rotating black hole with mass $M$. We consider two different regimes: $\tilde{m}_e= M^{-1} m_e\ll 1$ and $a\omega \ll 1$; $\tilde{m}_e\ll 1$ and $a\omega \gtrsim 1$. We treat each of these two regimes in different ways: we use a perturbative appro

Miguel Sofo-Haro, Kevan Donlon, Juan Estrada, Steve Holland

We introduce a new output amplifier for fully-depleted thick p-channel CCDs based on double-gate MOSFETs. The charge amplifier is an n-type MOSFET specifically designed and operated to couple the fully-depleted CCD with high charge-transfer efficiency. The junction coupling between the CCD and MOSFET channels has enabled high sensitivity, demonstrating sub-e

Meng-Lun Lee, Xiao Liang, Boyi Hu, Gulcan Onel

Product disassembly plays a crucial role in the recycling, remanufacturing, and reuse of end-of-use (EoU) products. However, the current manual disassembly process is inefficient due to the complexity and variation of EoU products. While fully automating disassembly is not economically viable given the intricate nature of the task, there is potential in usin

Alberto Megías

The statistical-physical study of granular matter is essential to understand, from a fundamental point of view, the many different phenomena emerging in these classical many-body systems. Under rapid-flow conditions, granular materials exhibit a gas-like behavior, which can be described from the kinetic theory of gases. However, unlike molecular gases, a gra

Yongxi Wu, Guangnian Ji, Peizhi Zhang

Noise generation attributed to the flow around a cylinder and its control is of paramount importance in a multitude of engineering applications. In this study, we employ computational fluid dynamics (CFD) coupled with acoustic analogy, complemented by an analysis grounded in vortex dynamics theory, to explore the potential of wavy cylinder shapes in improvin

Md Tanvir Emrose, Emily L. Payne, Chenglong You, Georgios Veronis

We introduce multilayer structures with the phase-change material Ge$_2$Sb$_2$Te$_5$ (GST) for use as broadband switchable absorbers in the infrared wavelength range. We optimize both the material composition and the layer thicknesses of the multilayer structures, in order to maximize the difference between the absorption for GST in its crystalline phase and

Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn

Reinforcement Learning from Human Feedback (RLHF) has emerged as a popular paradigm for aligning models with human intent. Typically RLHF algorithms operate in two phases: first, use human preferences to learn a reward function and second, align the model by optimizing the learned reward via reinforcement learning (RL). This paradigm assumes that human prefe

Andrei Gruzinov

Recent discovery of 20 TeV radiation from the Vela pulsar confirms (tentatively, at the level of crude estimates) the Aristotelian Electrodynamics picture of pulsar radiation: pulsars shine, mostly in GeV, by annihilating colliding Poynting fluxes into curvature radiation near the light cylinder. The observed GeV photons are the curvature radiation of electr

Krzysztof Kurowski, Piotr Rydlichowski, Konrad Wojciechowski, Tomasz Pecyna

Current technological advancements of quantum computers highlight the need for application-driven, practical and well-defined methods of benchmarking their performance. As the existing NISQ device's quality of two-qubit gate errors rate is even around one percent and the number of qubits is still limited to a few or several dozen, naturally, we need to propo

Guillaume Beaulieu, Fabrizio Minganti, Simone Frasca, Vincenzo Savona

In open quantum systems, first- and second-order dissipative phase transitions (DPTs) can emerge in the thermodynamic limit from the competition between unitary evolution, driving terms, and dissipation. The order of a DPT is defined by the continuity properties of the steady state. Until now, second-order DPTs have predominantly been investigated theoretica

Zhentong Wei, Chong Chen

Spatiotemporal dynamic medical imaging is critical in clinical applications, such as tomographic imaging of the heart or lung. To address such kind of spatiotemporal imaging problems, essentially, a time-dependent dynamic inverse problem, the variational model with intensity, edge feature and topology preservations was proposed for joint image reconstruction

Tomasz Maciazek, Mia Conlon

Determination of optimal control protocols for Majorana zero modes during their exchange is a crucial step towards the realisation of the topological quantum computer. In this paper, we study the finite-time exchange process of Majorana zero modes on a network formed by coupled p-wave superconducting one-dimensional nanowires. We provide scalable computation

Chan Ieong Kuan, David Lowry-Duda, Alexander Walker, Tinghao Huang

For a fixed natural number $h$, we prove meromorphic continuation of the two-variable Dirichlet series $\sum_m r_2(m) \sigma_w(m + h) (m + h)^{-s + w}$ to $\mathbb{C}^2$ and use this to obtain asymptotics for $\sum_{m^2 + n^2 \leq X} \sigma_w(m^2 + n^2 + h)$. We approach this continuation through spectral theory. Our results are comparable to earlier work of

Lorenzo Bernazzani, Guido Burkard

We investigate a system composed of two coupled oscillators subject to stochastic fluctuations in its internal parameters. In particular, we answer the question whether the well-known classical analogy of the quantum dynamics of two-level systems (TLS), i.e. qubits, provided by two coupled oscillators can be extended to simulate the dynamics of dissipative q

Scott Armstrong, Wei Wu

We prove that the scaling limit of the continuous solid-on-solid model in $\mathbb{Z}^d$ is a multiple of the Gaussian free field.

Qianyun Yun, Wen-Biao Han, Qian Hu, Haiguang Xu

Gravitational waves (GWs) from binary black hole mergers provide unique opportunities for cosmological inference such as standard sirens. However, the accurate determination of the luminosity distance of the event is limited by the correlation between the distance and the angle between the binary's orbital angular momentum and the observer's line of sight. I

Tianjie Hu, Jindi Wu, Qun Li

Quantum networks serve as the means to transmit information, encoded in quantum bits or qubits, between quantum processors that are physically separated. Given the instability of qubits, the design of such networks is challenging, necessitating a careful balance between reliability and efficiency. Typically, quantum networks fall into two categories: those u

J. F. Amieva, A. Austoni, M. A. Brovelli, L. Ansalone

Change detection (CD) methods have been applied to optical data for decades, while the use of hyperspectral data with a fine spectral resolution has been rarely explored. CD is applied in several sectors, such as environmental monitoring and disaster management. Thanks to the PRecursore IperSpettrale della Missione operativA (PRISMA), hyperspectral-from-spac

R. Makaju, H. Kassar, S. M. Daloglu, A. Huynh

Coulomb drag experiments have been an essential tool to study strongly interacting low-dimensional systems. Historically, this effect has been explained in terms of momentum transfer between electrons in the active and the passive layer. Here, we report Coulomb drag measurements between laterally coupled GaAs/AlGaAs quantum wires in the multiple 1D sub-band

Sania Eskandari, Janet Lumpp

Melanoma is a dangerous form of skin cancer caused by the abnormal growth of skin cells. Fully Convolutional Network (FCN) approaches, including the U-Net architecture, can automatically segment skin lesions to aid diagnosis. The symmetrical U-Net model has shown outstanding results, but its use of a convolutional operation limits its ability to capture long

Johannes Markkanen, Antti Penttilä

The Radiative transfer coherent backscattering (RT-CB) code is extended to apply to dense discrete random media of optically soft spherical particles. This is achieved by utilizing the well-known static-structure-factor (SSF) correction derived from the Percus-Yevick approximation for sticky-hard-sphere (SHS) pair correlation function. The code is verified a

Janet Egan, Lennart Heim

To address security and safety risks stemming from highly capable artificial intelligence (AI) models, we propose that the US government should ensure compute providers implement Know-Your-Customer (KYC) schemes. Compute - the computational power and infrastructure required to train and run these AI models - is emerging as a node for oversight. KYC, a standa

Andrew Engel, Jan Strube

Physical constraints have been suggested to make neural network models more generalizable, act scientifically plausible, and be more data-efficient over unconstrained baselines. In this report, we present preliminary work on evaluating the effects of adding soft physical constraints to computer vision neural networks trained to estimate the conditional densi

F. Rescigno, G. Hébrard, A. Vanderburg, A. W. Mann

We present the characterisation of an inner mini-Neptune in a 9.2292005$\pm$0.0000063 day orbit and an outer mono-transiting sub-Saturn planet in a 95.50$^{+0.36}_{-0.25}$ day orbit around the moderately active, bright (mv=8.9 mag) K5V star TOI-2134. Based on our analysis of five sectors of TESS data, we determine the radii of TOI-2134b and c to be 2.69$\pm$

Matthew Gadd, Benjamin Ramtoula, Daniele De Martini, Paul Newman

Recalling the most relevant visual memories for localisation or understanding a priori the likely outcome of localisation effort against a particular visual memory is useful for efficient and robust visual navigation. Solutions to this problem should be divorced from performance appraisal against ground truth - as this is not available at run-time - and shou

Shigeo Koshitani, Caroline Lassueur, Benjamin Sambale

We classify principal $2$-blocks of finite groups $G$ with Sylow $2$-subgroups isomorphic to a wreathed $2$-group $C_{2^n}\wr C_2$ with $n\geq 2$ up to Morita equivalence and up to splendid Morita equivalence. As a consequence, we obtain that Puig's Finiteness Conjecture holds for such blocks. Furthermore, we obtain a classification of such groups modulo $O_

Emily Cheng, Corentin Kervadec, Marco Baroni

For a language model (LM) to faithfully model human language, it must compress vast, potentially infinite information into relatively few dimensions. We propose analyzing compression in (pre-trained) LMs from two points of view: geometric and information-theoretic. We demonstrate that the two views are highly correlated, such that the intrinsic geometric dim

Arushi Goel, Basura Fernando, Frank Keller, Hakan Bilen

In this paper, we study multimodal coreference resolution, specifically where a longer descriptive text, i.e., a narration is paired with an image. This poses significant challenges due to fine-grained image-text alignment, inherent ambiguity present in narrative language, and unavailability of large annotated training sets. To tackle these challenges, we pr

Carlos Efrain Quintero-Narvaez, Raul Monroy-Borja

We present an implementation of a Web3 platform that leverages the Groth16 Zero-Knowledge Proof schema to verify the validity of questionnaire results within Smart Contracts. Our approach ensures that the answer key of the questionnaire remains undisclosed throughout the verification process, while ensuring that the evaluation is done fairly. To accomplish t

Yujia Liu, Qi Xin, Chenzhuo Xiang, Yu Zhang

Smart mirrors have emerged as a new form of augmented reality (AR) interface for home environments. However, due to the parallax in human vision, one major challenge hindering their development is the depth misalignment between the 3D mirror reflection and the 2D screen display. This misalignment causes the display content to appear as if it is floating abov

Hamid Shamszare, Avishek Choudhury

This study investigated how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influenced users' trust in Chat Generative Pre-Trained Transformer (ChatGPT). We aimed to understand the nuances of user engagement and provide insights to improve future design and adoption strategies for similar technologies. A semi-structured,

Jean-Lou De Carufel, Paola Flocchini, Nicola Santoro, Frédéric Simard

A \emph{periodic graph} ${\cal G}=(G_0, G_1, G_2, \dots)$ with period $p$ is an infinite periodic sequence of graphs $G_i = G_{i + p} = (V,E_i)$, where $i \geq 0$. The graph $G=(V,\cup_i E_i)$ is called the footprint of ${\cal G}$. Recently, the arena where the Cops and Robber game is played has been extended from a graph to a periodic graph; in this case, t

An-Zi Yen, Wei-Ling Hsu

Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work has been done on investigating the pedagogical ability of LLMs in helping students to learn mathematics. In this position paper, we discuss the challenges associated with employin

Nasser Almousa, Nasser Alzamil, Abdullah Alshehri, Ahmad Sait

This project introduces an advanced English-to-Arabic translator surpassing conventional tools. Leveraging the Helsinki transformer (MarianMT), our approach involves fine-tuning on a self-scraped, purely literary Arabic dataset. Evaluations against Google Translate show consistent outperformance in qualitative assessments. Notably, it excels in cultural sens

Daniel Hausmann, Nir Piterman, Irmak Sağlam, Anne-Kathrin Schmuck

We consider two-player games over finite graphs in which both players are restricted by fairness constraints on their moves. Given a two player game graph $G=(V,E)$ and a set of fair moves $E_f\subseteq E$ a player is said to play "fair" in $G$ if they choose an edge $e \in E_f$ infinitely often whenever the source vertex of $e$ is visited infinitely often.

Lyonell Boulton, Marco Marletta

In this paper we examine the asymptotic structure of the pseudospectrum of the singular Sturm-Liouville operator $L=\partial_x(f\partial_x)+\partial_x$ subject to periodic boundary conditions on a symmetric interval, where the coefficient $f$ is a regular odd function that has only a simple zero at the origin. The operator $L$ is closely related to a remarka

Yanrui Du, Sendong Zhao, Haochun Wang, Yuhan Chen

Explaining black-box model behavior with natural language has achieved impressive results in various NLP tasks. Recent research has explored the utilization of subsequences from the input text as a rationale, providing users with evidence to support the model decision. Although existing frameworks excel in generating high-quality rationales while achieving h

Pratikshya Jena, Shradha Mishra

The collection of active agents often exhibits intriguing statistical and dynamical properties, particularly when considering human crowds. In this study, we have developed a computational model to simulate the recent experiment on real marathon races by Bain et al. Our primary goal is to investigate the impact of race staff on crowd dynamics. By comparing s

Tobias Schäfer, William Z. Van Benschoten, James J. Shepherd, Andreas Grüneis

We present a robust strategy to numerically sample the Coulomb potential in reciprocal space for periodic Born-von Karman cells of general shape. Our approach tackles two common issues of plane-wave based implementations of Coulomb integrals under periodic boundary conditions, the treatment of the singularity at the Brillouin-zone center, as well as quadratu

Irene Bonafonte, Cristina Bustos, Abraham Larrazolo, Gilberto Lorenzo Martinez Luna

The possibility of recognizing diverse aspects of human behavior and environmental context from passively captured data motivates its use for mental health assessment. In this paper, we analyze the contribution of different passively collected sensor data types (WiFi, GPS, Social interaction, Phone Log, Physical Activity, Audio, and Academic features) to pre

Dominik Macko, Robert Moro, Adaku Uchendu, Jason Samuel Lucas

There is a lack of research into capabilities of recent LLMs to generate convincing text in languages other than English and into performance of detectors of machine-generated text in multilingual settings. This is also reflected in the available benchmarks which lack authentic texts in languages other than English and predominantly cover older generators. T

Xinyu Zhang, Li Wang, Zhiqiang Jiang, Kun Dai

Local Feature Matching, an essential component of several computer vision tasks (e.g., structure from motion and visual localization), has been effectively settled by Transformer-based methods. However, these methods only integrate long-range context information among keypoints with a fixed receptive field, which constrains the network from reconciling the i

Sania Eskandari, Janet Lumpp, Luis Sanchez Giraldo

Melanoma, a dangerous type of skin cancer resulting from abnormal skin cell growth, can be treated if detected early. Various approaches using Fully Convolutional Networks (FCNs) have been proposed, with the U-Net architecture being prominent To aid in its diagnosis through automatic skin lesion segmentation. However, the symmetrical U-Net model's reliance o

Reiko Harada, Kipp Cannon, Kenta Hotokezaka, Koutarou Kyutoku

Elementary particles such as quarks and gluons are expected to be fundamental degrees of freedom at ultra high temperatures or densities, while natural phenomena in our daily lives are described in terms of hadronic degrees of freedom. Massive neutron stars and remnants of binary neutron star mergers may contain quark matter, but it is not known how the tran

Montie Avery

We describe the resulting spatiotemporal dynamics when a homogeneous equilibrium loses stability in a spatially extended system. More precisely, we consider reaction-diffusion systems, assuming only that the reaction kinetics undergo a transcritical, saddle-node, or supercritical pitchfork bifurcation as a parameter passes through zero. We construct travelin

Abramo Agosti, Robert Lasarzik, Elisabetta Rocca

In this article, we introduce the concept of energy-variational solutions for a large class of systems of nonlinear evolutionary partial differential equations. Under certain convexity assumptions, the existence of such solutions can be shown constructively by an adapted minimizing movement scheme. Weak-strong uniqueness follows by a suitable relative energy

Vage Karakhanyan, Roland Salut, Miguel Suarez, Nicolas Martin

Chirality is inherent to a broad range of systems, including in solid-state and wave physics. The precession (chiral motion) of electron spins in magnetic materials, forming spin waves, has various properties and many applications in magnetism and spintronics. We show that an optical analog of spin waves can be generated in arrays of plasmonic nanohelices. S

Giles Blaney, Angelo Sassaroli, Sergio Fantini

This compendium review focuses on the spatial distribution of sensitivity to localized absorption changes in optically diffuse media, particularly for measurements relevant to near-infrared spectroscopy. The three temporal domains, continuous-wave, frequency-domain, and time-domain, each obtain different optical data-types whose changes may be related to eff

Peter Coppola

How subjective experience (i.e., consciousness) arises out of objective material processes has been called the hard problem. The neuroscience of consciousness has set out to find the sufficient conditions for consciousness and theoretical and empirical endeavours have placed a particular focus on the cortex and subcortex, whilst discounting the cerebellum. H

Saroch Leedumrongwatthanakun, Luca Innocenti, Alessandro Ferraro, Mauro Paternostro

Extracting meaningful information about unknown quantum states without performing a full tomography is an important task. Low-dimensional projections and random measurements can provide such insight but typically require careful crafting. In this paper, we present an optical scheme based on sending unknown input states through a multimode fiber and performin

Samuel Grégoire, Christophe Vanderaa, Sébastien Pyr dit Ruys, Gabriel Mazzucchelli

Mass spectrometry (MS) based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells - proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team t