October 2023 arXiv papers — page 52

Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar, S Ramaneswaran

We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effective data augmentations of legal documents - legal language, with its specialized vocabulary and complex semantics, morphology, and syntax, does not benefit from data augmentations

João Henrique Andrade, Jeffrey S. Case, Paolo Piccione, Juncheng Wei

Given a conformally variational scalar Riemannian invariant $I$, we identify a sufficient condition for a compact Riemannian manifold to admit finite regular coverings with many nonhomothetic conformal rescalings with $I$ constant. We also identify a sufficient condition for the universal cover to admit infinitely many geometrically distinct periodic conform

Jiaang Li, Quan Wang, Yi Liu, Licheng Zhang

Representation Learning on Knowledge Graphs (KGs) is essential for downstream tasks. The dominant approach, KG Embedding (KGE), represents entities with independent vectors and faces the scalability challenge. Recent studies propose an alternative way for parameter efficiency, which represents entities by composing entity-corresponding codewords matched from

Holger Dette, Martin Schumann

The plausibility of the ``parallel trends assumption'' in Difference-in-Differences estimation is usually assessed by a test of the null hypothesis that the difference between the average outcomes of both groups is constant over time before the treatment. However, failure to reject the null hypothesis does not imply the absence of differences in time trends

Andrés Aceña, Juan Barranco, Argelia Bernal, Ericson López

In spherical symmetry, the gravitational potential is uniquely determined by the rotational velocity profile. Numerous galaxies exhibit a universal velocity profile from which a universal gravitational profile is inferred. When treating dark matter as either an ideal gas, a Fermi gas, or a Bose gas, only the latter can produce a gravitational profile consist

Han Xu, Bochen Shi, Zhujun Yu, Jialin Zheng

Simulation is an efficient tool in the design and control of power electronic systems. However, quick and accurate simulation of them is still challenging, especially when the system contains a large number of switches and state variables. Conventional general-purpose integration algorithms assume nonlinearity within systems but face inefficiency in handling

Louis Falissard, Vincent Guigue, Laure Soulier

This article focuses on large language models (LLMs) fine-tuning in the scarce data regime (also known as the "few-shot" learning setting). We propose a method to increase the generalization capabilities of LLMs based on neural network subspaces. This optimization method, recently introduced in computer vision, aims to improve model generalization by identif

Xin Xu, Jinsong Liu, Henglin Mu, Yan Li

Accurate position and posture measurements of the freely-falling test mass are crucial for the success of spaceborne gravitational wave detection missions. This paper presents a novel laboratory-developed test mass motion readout that utilizes quadrant photodetectors to measure the translation and tilt of a test mass. Departing from conventional methods like

Yuanyuan Fang, Jing Feng, Dan Xie

We systematically study the AdS/CFT correspondence induced by D3 branes probing three dimensional Gorenstein quotient singularity $\mathbb{C}^3/G$. The field theory is given by the McKay quiver, which has a vanishing NSVZ beta function assuming that all the chiral fields have the $U(1)_R$ charge $\frac{2}{3}$. Various physical quantities such as quiver Hilbe

Ettore Zaffaroni

SND@LHC is a compact and stand-alone experiment to perform measurements with neutrinos produced at the LHC in a hitherto unexplored pseudo-rapidity region of $7.2 < \eta < 8.4$, complementary to all the other experiments at the LHC. The experiment is located 480 m downstream of IP1 in the unused TI18 tunnel. The detector is composed of a hybrid system based

Samuel Sarria Hurtado, Todd Mullen, Taku Onodera, Paul Sheridan

A term in a corpus is said to be ``bursty'' (or overdispersed) when its occurrences are concentrated in few out of many documents. In this paper, we propose Residual Inverse Collection Frequency (RICF), a statistical significance test inspired heuristic for quantifying term burstiness. The chi-squared test is, to our knowledge, the sole test of statistical s

Damian Kurpiewski, Wojciech Jamroga, Łukasz Maśko, Łukasz Mikulski

Formal verification of multi-agent systems is hard, both theoretically and in practice. In particular, studies that use a single verification technique typically show limited efficiency, and allow to verify only toy examples. Here, we propose some new techniques and combine them with several recently developed ones to see what progress can be achieved for a

Mosh Levy, Shauli Ravfogel, Yoav Goldberg

Recent applications of LLMs in Machine Reading Comprehension (MRC) systems have shown impressive results, but the use of shortcuts, mechanisms triggered by features spuriously correlated to the true label, has emerged as a potential threat to their reliability. We analyze the problem from two angles: LLMs as editors, guided to edit text to mislead LLMs; and

Ashwin Renganathan, Kade E. Carlson

Classical evolutionary approaches for multiobjective optimization are quite accurate but incur a lot of queries to the objectives; this can be prohibitive when objectives are expensive oracles. A sample-efficient approach to solving multiobjective optimization is via Gaussian process (GP) surrogates and Bayesian optimization (BO). Multiobjective Bayesian opt

Khanh-Binh Nguyen

Semi-supervised learning (SSL) has become popular in recent years because it allows the training of a model using a large amount of unlabeled data. However, one issue that many SSL methods face is the confirmation bias, which occurs when the model is overfitted to the small labeled training dataset and produces overconfident, incorrect predictions. To addres

Matthew Ashman, Tommy Rochussen, Adrian Weller

The global inducing point variational approximation for BNNs is based on using a set of inducing inputs to construct a series of conditional distributions that accurately approximate the conditionals of the true posterior distribution. Our key insight is that these inducing inputs can be replaced by the actual data, such that the variational distribution con

Noam Soker

I examine the morphologies of the brightest planetary nebulae (PNe) in the Milky Way Galaxy and conclude that violent binary interaction processes eject the main nebulae of the brightest PNe. The typical morphologies of the brightest PNe are multipolar, namely have been shaped by two or more major jet-launching episodes at varying directions, and possess sma

Jide Edu, Mark Hooper, Carsten Maple, Jon Crowcroft

Electronic identification (eID) systems allow citizens to assert and authenticate their identities for various purposes, such as accessing government services or conducting financial transactions. These systems improve user access to rights, services, and the formal economy. As eID systems become an essential facet of national development, any failure, compr

Nicolas Baù, Antimo Marrazzo

Topological invariants are global properties of the ground-state wave function, typically defined as winding numbers in reciprocal space. Over the years, a number of topological markers in real space have been introduced, allowing to map topological order in heterogeneous crystalline and disordered systems. Notably, even if these formulations can be expresse

M. Ellwarth, B. Ehmann, S. Schäfer, A. Reiners

Solar convection is visible as a net blueshift of absorption lines, which becomes apparent when observing quiet Sun granulation. This blueshift exhibits variations from the disc centre to the solar limb due to differing projection angles onto the solar atmosphere. Our goal is to investigate convective Doppler velocities based on observations from the disc ce

Ling-Long Gao, Yan Liu, Hong-Da Lyu

We construct hairy rotating black hole solutions in three dimensional Einstein gravity coupled to a complex scalar field. When we turn on a real and uniform source on the dual CFT, the black hole is stationary with two Killing vectors and we show that there is no inner horizon for the black hole and the system evolves smoothly into a Kasner universe. When we

Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen

Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality, especially as mobile applications have become an integral part of our daily lives. Despite the growing popularity of learning-based techniques in automated GUI testing due to their ability to generate human-like interactions, they still suffer from several limitati

Jorge A. Vila

Proteins have evolved through mutations, amino acid substitutions, since life appeared on Earth, some 109 years ago. The study of these phenomena has been of particular significance because of their impact on protein stability, function, and structure. Three of the most recent findings in these areas deserve to be highlighted. First, an innovative method has

Lennart Alexander Van der Goten, Kevin Smith

MRI scans provide valuable medical information, however they also contain sensitive and personally identifiable information that needs to be protected. Whereas MRI metadata is easily sanitized, MRI image data is a privacy risk because it contains information to render highly-realistic 3D visualizations of a patient's head, enabling malicious actors to possib

Yizhe Yang, Huashan Sun, Jiawei Li, Runheng Liu

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by developing increasingly large-scale models, there could be another branch to develop lightweight custom models that better serve

Robert Allen, Dominic Verdon

The problem of extending the insights and techniques of categorical quantum mechanics to infinite-dimensional systems was considered in (Coecke and Heunen, 2016). In that work the $\mathrm{CP}^{\infty}$-construction, which recovers the category of Hilbert spaces and quantum operations from the category of Hilbert spaces and bounded linear maps, was defined.

Luana Hildever, Thiago Ferro, José Holanda

Fundamental interactions are the basis of the most diverse phenomena in science that allow the dazzling of possible applications. In this work, we report a new interaction, which we call chemical-quantum-magnetic interaction. This interaction arises due to the difference in valence that the Fe3O4/PANI nanostructure acquires under certain conditions. In this

Charles Champagne Cossette, Mitchell Cohen, Vassili Korotkine, Arturo del Castillo Bernal

The ability to rapidly test a variety of algorithms for an arbitrary state estimation task is valuable in the prototyping phase of navigation systems. Lie group theory is now mainstream in the robotics community, and hence estimation prototyping tools should allow state definitions that belong to manifolds. A new package, called navlie, provides a framework

Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez, Sweta Agrawal

We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how well off-the-shelf LLMs can solve this challenging task, assessing a total of 44 models, differing in size, architecture, pre-training methods, and accessibility, on three test sets f

Dominique Geissler, Abdurahman Maarouf, Stefan Feuerriegel

Hate speech on social media threatens the mental and physical well-being of individuals and contributes to real-world violence. Resharing is an important driver behind the spread of hate speech on social media. Yet, little is known about who reshares hate speech and what their characteristics are. In this paper, we analyze the role of user characteristics in

Shin'ichi Nojiri, G. G. L. Nashed

We propose a class of models, in which stable gravastar with large surface redshift becomes a solution. In recent decades, gravastars have become a plausible substitute for black holes. Researchers have explored stable gravastar models in various alternative gravity theories, in addition to the conventional framework of general relativity. In this paper, we

Vincenzo Basco

In the last decades, control problems with infinite horizons and discount factors have become increasingly central not only for economics but also for applications in artificial intelligence and machine learning. The strong links between reinforcement learning and control theory have led to major efforts towards the development of algorithms to learn how to

Soichiro Kuwahara, Kipp Cannon

We previously described the development of a detection system for a novel class of transient gravitational-wave sources taking the form of Cherenkov-like bursts. Here, we have applied the system to the data of the LIGO/Virgo/KAGRA O3 science run, and report a null result. The ad hoc waveform model is motivated by the conjectured emission of gravitational wav

Lijia Jiang, Fei Gao, Yu-xin Liu

To identify first-order phase transitions in the dynamical process similar to the relativistic heavy-ion collisions, we investigate the dynamical behaviors of the first-order phase transition criterion in the Fokker-Planck framework. In the thermodynamic limit, the criterion can be expressed as combinations of cumulants or coefficients of an Ising-like effec

J. R. Bravo, J. A. Hernández, S. Ares de Parga, R. Rossi

This paper is concerned with quadrature/cubature rules able to deal with multiple subspaces of functions, in such a way that the integration points are common for all the subspaces, yet the weights are tailored to each specific subspace. These subspace-adaptive weights cubature rules can be used to accelerate computational mechanics applications requiring ef

Amos Lapidoth, Ligong Wang, Yiming Yan

A formula is derived for the capacity of the Gaussian channel with a benevolent message-cognizant rate-limited helper that provides a noncausal description of the noise to the encoder and decoder. This capacity is strictly larger than when the helper is message oblivious, with the difference being particularly pronounced at low signal-to-noise ratios. It is

Hao Li, Quanwei Liu, Jianan Liu, Xiling Liu

Magnetic resonance imaging (MRI) is crucial for enhancing diagnostic accuracy in clinical settings. However, the inherent long scan time of MRI restricts its widespread applicability. Deep learning-based image super-resolution (SR) methods exhibit promise in improving MRI resolution without additional cost. Due to lacking of aligned high-resolution (HR) and

Minh Nguyen, Alan Q. Wang, Heejong Kim, Mert R. Sabuncu

Healthcare data often come from multiple sites in which the correlations between confounding variables can vary widely. If deep learning models exploit these unstable correlations, they might fail catastrophically in unseen sites. Although many methods have been proposed to tackle unstable correlations, each has its limitations. For example, adversarial trai

Charles Goulas, Fabrice Vidal, Raphaël Galicher, Johan Mazoyer

SAXO+ is a proposed upgrade to SAXO, the AO system of the SPHERE instrument on the ESO Very Large Telescope. It will improve the capabilities of the instrument for the detection and characterization of young giant planets. It includes a second stage adaptive optics system composed of a dedicated near-infrared wavefront sensor and a deformable mirror. This se

Khanh-Binh Nguyen

Recent studies on semi-supervised learning (SSL) have achieved great success. Despite their promising performance, current state-of-the-art methods tend toward increasingly complex designs at the cost of introducing more network components and additional training procedures. In this paper, we propose a simple method named Ensemble Projectors Aided for Semi-s

Ki-Seok Kim, Shinsei Ryu

We investigate the monotonicity of the renormalization group (RG) flow from the perspectives of nonequilibrium thermodynamics. Applying the Martin-Siggia-Rose formalism to the Wilsonian RG transformation, we incorporate the RG flow equations manifestly in an effective action, where all coupling functions are dynamically promoted. As a result, we obtain an em

Derong Tang

Current graph systems can easily process billions of data, however when increased to exceed hundred billions, the performance decreases dramatically, time series data always be very huge, consequently computation on time series graphs still remains challenging nowadays. In current piece of work, we introduces SharkGraph, a (distributed file system) DFS-based

Anne Templeton, Hui Xie, Steve Gwynne, Aoife Hunt

Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus,

L. Contessi, M. Schäfer, U. van Kolck

We present an improved action for renormalizable effective field theories (EFTs) of systems near the two-body unitarity limit. The ordering of EFT interactions is constrained, but not entirely fixed, by the renormalization group. The remaining freedom can be used to improve the theory's convergence, to simplify its applications, and to connect it to phenomen

Xing-Yu Zhang, Runze Chi, Yang Liu, Lei Wang

Understanding the excitation spectrum in two-dimensional quantum many-body systems has long been a challenging task. We present an approach by introducing an excitation ansatz based on an infinite matrix product state (MPS) on a helix structure. With the canonical form of MPS states, we can accurately extract key properties such as energy, degeneracy, spectr

Dominic Petrak, Nafise Sadat Moosavi, Ye Tian, Nikolai Rozanov

Learning from free-text human feedback is essential for dialog systems, but annotated data is scarce and usually covers only a small fraction of error types known in conversational AI. Instead of collecting and annotating new datasets from scratch, recent advances in synthetic dialog generation could be used to augment existing dialog datasets with the neces

Michiel van der Meer, Piek Vossen, Catholijn M. Jonker, Pradeep K. Murukannaiah

Disagreements are common in online discussions. Disagreement may foster collaboration and improve the quality of a discussion under some conditions. Although there exist methods for recognizing disagreement, a deeper understanding of factors that influence disagreement is lacking in the literature. We investigate a hypothesis that differences in personal val

Longguang Li

In this paper, we study two types of optical wireless channels under average-intensity constraints. One is called the Gaussian optical intensity channel, where the channel output models the converted electrical current corrupted by additive white Gaussian noise. The other one is the Poisson optical intensity channel, where the channel output models the numbe

Tomohiro Uchiyama

In this paper, we study economic dynamics in a standard overlapping generations model without production. In particular, using numerical methods, we obtain a necessary and sufficient condition for the existence of a topological chaos. This is a new application of a recent result characterising the existence of a topological chaos for a unimodal interval map

Svein Høgemo

Graph parameters measure the amount of structure (or lack thereof) in a graph that makes it amenable to being decomposed in a way that facilitates dynamic programming. Graph decompositions and their associated parameters are important both in practice (as a tool for designing robust algorithms for NP-hard problems) and in theory (relating large classes of pr

S. Arabeei, S. Subbey

The schooling behavior of fish can be studied through simulations involving a large number of interacting particles. In such systems, each individual particle is guided by behavior rules, which include aggregation towards a centroid, collision avoidance, and direction alignment. The movement vector of each particle may be expressed as a linear combination of

Dennis Fucci, Marco Gaido, Sara Papi, Mauro Cettolo

When translating words referring to the speaker, speech translation (ST) systems should not resort to default masculine generics nor rely on potentially misleading vocal traits. Rather, they should assign gender according to the speakers' preference. The existing solutions to do so, though effective, are hardly feasible in practice as they involve dedicated

Anna Ziegler, Robert Hahn, Victoria Isensee, Anh Duc Nguyen

Shape optimization with respect to eigenvalues of a cavity plays an important role in the design of new resonators or in the optimization of existing ones. In our paper, we propose a gradient-based optimization scheme, which we enhance with closed-form shape derivatives of the system matrices. Based on these, we can compute accurate derivatives of eigenvalue

Abijith Jagannath Kamath, Chandra Sekhar Seelamantula

Neuromorphic sampling is a bioinspired and opportunistic analog-to-digital conversion technique, where the measurements are recorded only when there is a significant change in the signal amplitude. Neuromorphic sampling has paved the way for a new class of vision sensors called event cameras or dynamic vision sensors (DVS), which consume low power, accommoda

Amir Ali

In recent times, the use of chest Computed Tomography (CT) images for detecting coronavirus infections has gained significant attention, owing to their ability to reveal bilateral changes in affected individuals. However, classifying patients from medical images presents a formidable challenge, particularly in identifying such bilateral changes. To tackle th

Zhen He, Zhaoyang Yin

In this paper, we prove the norm inflation and get the ill-posedness for the modified Camassa-Holm equation in $B_{\infty,1}^0$. Therefore we completed all well-posedness and ill-posedness problem for the modified Camassa-Holm equation in all critical spaces $B_{p,1}^\frac{1}{p}$ with $p\in[1,\infty]$.

Vyacheslav D. Sedykh

We prove that the complement to the caustic of a stable Lagrangian map germ of type $E_6^\pm$ has seven connected components, six of which are contractible and one is homotopy equivalent to a circle. The inverse image of the noncontractible component under this map has three connected components. The restriction of the map to one of them is a two-sheeted cov

Dohwan Ko, Ji Soo Lee, Wooyoung Kang, Byungseok Roh

Large Language Models (LLMs) have shown remarkable performances on a wide range of natural language understanding and generation tasks. We observe that the LLMs provide effective priors in exploiting $\textit{linguistic shortcuts}$ for temporal and causal reasoning in Video Question Answering (VideoQA). However, such priors often cause suboptimal results on

Zeyuan Yang, Peng Li, Yang Liu

Large Language Models (LLMs) have showcased impressive performance. However, due to their inability to capture relationships among samples, these frozen LLMs inevitably keep repeating similar mistakes. In this work, we propose our Tuning-free Rule Accumulation (TRAN) framework, which guides LLMs in improving their performance by learning from previous mistak

Moongul Byun

It is well known that perturbative solutions of the Langevin equation can be used to calculate correlation functions in stochastic quantization. However, this work is challenging due to the absence of generalized rules. In this paper, we address this difficulty by studying correlation functions up to certain orders for self-interacting scalar fields. Through

Dries Van Leemput, Jeroen Hoebeke, Eli De Poorter

Industrial wireless sensor networks enable real-time data collection, analysis, and control by interconnecting diverse industrial devices. In these industrial settings, power outlets are not always available, and reliance on battery power can be impractical due to the need for frequent battery replacement or stringent safety regulations. Battery-less energy

Yuta Hozumi, Guo-Wei Wei

Single-cell RNA sequencing (scRNA-seq) is a relatively new technology that has stimulated enormous interest in statistics, data science, and computational biology due to the high dimensionality, complexity, and large scale associated with scRNA-seq data. Nonnegative matrix factorization (NMF) offers a unique approach due to its meta-gene interpretation of re

Shiao Meng, Xuming Hu, Aiwei Liu, Shu'ang Li

How to identify semantic relations among entities in a document when only a few labeled documents are available? Few-shot document-level relation extraction (FSDLRE) is crucial for addressing the pervasive data scarcity problem in real-world scenarios. Metric-based meta-learning is an effective framework widely adopted for FSDLRE, which constructs class prot

Alexander Jenkins, Zehua Chen, Fu Siong Ng, Danilo Mandic

Pulsative signals such as the electrocardiogram (ECG) are extensively collected as part of routine clinical care. However, noisy and poor-quality recordings are a major issue for signals collected using mobile health systems, decreasing the signal quality, leading to missing values, and affecting automated downstream tasks. Recent studies have explored the i

Pieter Dewulf, Michiel Stock, Bernard De Baets

Integral transforms are invaluable mathematical tools to map functions into spaces where they are easier to characterize. We introduce the hyperdimensional transform as a new kind of integral transform. It converts square-integrable functions into noise-robust, holographic, high-dimensional representations called hyperdimensional vectors. The central idea is

Luisa Gallee, Meinrad Beer, Michael Goetz

Interpretability is often an essential requirement in medical imaging. Advanced deep learning methods are required to address this need for explainability and high performance. In this work, we investigate whether additional information available during the training process can be used to create an understandable and powerful model. We propose an innovative

C. Brand, V. Tinnemann, A. Hanisch-Blicharski, M. Tajik

Upon impulsive optical excitation of solid-state materials, the non-equilibrium flow of energy from the excited electronic system to the lattice degrees of freedom typically happens in a few picoseconds. Here we identified the surface of thin Bi films grown on Si(001) as an additional subsystem which is excited much slower on a 100 ps timescale that is cause

Leandro Arosio, Filippo Bracci, Herv/'e Gaussier

We give an example of a parabolic holomorphic self-map $f$ of the unit ball $\mathbb B^2\subset \mathbb C^2$ whose canonical Kobayashi hyperbolic semi-model is given by an elliptic automorphism of the disc $\mathbb D\subset \mathbb C$, which can be chosen to be different from the identity. As a consequence, in contrast to the one dimensional case, this provi

A. Alonso-Izquierdo, D. Miguélez-Caballero, L. M. Nieto

The dynamics of a wobbling kink in a two-component coupled $\phi^4$ scalar field theory (with an excited orthogonal shape mode) is addressed. For this purpose, the vibration spectrum of the second order small kink fluctuation is studied in order to find the corresponding vibration modes associated to the first (longitudinal) and second (orthogonal) field com

Francesco Pezone, Osman Musa, Giuseppe Caire, Sergio Barbarossa

Semantic communication, rather than on a bit-by-bit recovery of the transmitted messages, focuses on the meaning and the goal of the communication itself. In this paper, we propose a novel semantic image coding scheme that preserves the semantic content of an image, while ensuring a good trade-off between coding rate and image quality. The proposed Semantic-

M. V. Klymenko, L. Z. Tan, S. P. Russo, J. H. Cole

Excitons in organic crystalline semiconductors play a crucial role in the operation of optoelectronic devices such as organic solar cells, light-emitting diodes, and photodetectors. The excitonic properties of materials are dramatically affected by the presence of surfaces and interfaces. In this work, we investigate the influence of a neutral hydrogen-passi

Hisham Sati, Urs Schreiber

The modern theory of functional programming languages uses monads for encoding computational side-effects and side-contexts, beyond bare-bone program logic. Even though quantum computing is intrinsically side-effectful (as in quantum measurement) and context-dependent (as on mixed ancillary states), little of this monadic paradigm has previously been brought

Laura Foglia, Björn Wehinger, Giovanni Perosa, Riccardo Mincigrucci

We present the generation of transient polarization gratings at the nanoscale, achieved using a tailored accelerator configuration of the FERMI free electron laser. We demonstrate the capabilities of such a transient polarization grating by comparing its induced dynamics with the ones triggered by a more conventional intensity grating on a thin film ferrimag

Hyun-Jeong Kim, Bon-Chul Koo, Takashi Onaka

IRAS 15099-5856 in the young supernova remnant (SNR) MSH 15-52 is the first and only SNR-associated object with crystalline silicate dust detected so far, although its nature and the origin of the crystalline silicate are still unclear. In this paper, we present high-resolution mid-infrared (MIR) imaging observations of the bright central compact source IRS1

Matti Würthen, Heer Zhao

Let $\mathcal{O}_{K}$ be a complete discrete valuation ring of mixed characteristic with perfect residue field, endowed with its canonical log-structure. We prove that log $p$-divisible groups over $\mathcal{O}_{K}$ correspond to Dieudonn\'e crystals on the absolute log-prismatic site of $\mathcal{O}_{K}$ endowed with the Kummer log-flat topology. The proof

Euclid Collaboration, D. Sciotti, S. Gouyou Beauchamps, V. F. Cardone

Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncertainties in the measurement of the cosmological parameters. Super-sample covariance (SSC) is among the largest of these non-Gaussian contributions, with the potential to significant

Naihuan Jing, Ning Liu

We introduce a new family of operators as multi-parameter deformation of the one-row Macdonald polynomials. The matrix coefficients of these operators acting on the space of symmetric functions with rational coefficients in two parameters $q,t$ (denoted by $\Lambda[q,t]$) are computed by assigning some values to skew Macdonald polynomials in $\lambda$-ring n

S. Parnovsky

In the famous textbook written by Landau and Lifshitz all the vacuum metrics of the general theory of relativity are derived, which depend on one coordinate in the absence of a cosmological constant. Unfortunately, when considering these solutions, the authors missed some of the possible solutions discussed in this article. An exact solution is demonstrated,

Macoto Kikuchi

The mutation-selection mechanism of Darwinian evolution gives rise not only to adaptation to environmental conditions but also to the enhancement of robustness against mutations. When two or more phenotypes have the same fitness value, the robustness distribution for different phenotypes can vary. Thus, we expect that some phenotypes are favored in evolution

Leonid Christophorov

The minimal 3-state scheme of kinetic cooperativity of monomeric enzymes is subjected to detailed analysis. The rigorous criteria of positive cooperativity and its sigmoidal version are established in terms of the system parameters (rate constants). It is shown that the cooperativity extent is especially sensitive to the rates and direction of the exchange b

Łukasz Mikulski, Wojciech Jamroga, Damian Kurpiewski

Formal verification of strategic abilities is a hard problem. We propose to use the methodology of assume-guarantee reasoning in order to facilitate model checking of alternating-time temporal logic with imperfect information and imperfect recall.

Zhen He, Zhaoyang Yin

In this paper,for a given conservative solution, we introduce a set of auxiliary variables tailored to this particular solution, and prove that these variables satisfy a particular semilinear system having unique solutions. In turn, we get the uniqueness of the conservative solution in the original variables.

Feng Gao, Jiaxu Leng, Ji Gan, Xinbo Gao

DEtection TRansformer (DETR) and its variants (DETRs) have been successfully applied to crowded pedestrian detection, which achieved promising performance. However, we find that, in different degrees of crowded scenes, the number of DETRs' queries must be adjusted manually, otherwise, the performance would degrade to varying degrees. In this paper, we first

Chaojun Xiao, Yuqi Luo, Wenbin Zhang, Pengle Zhang

Pre-trained language models (PLMs) have achieved remarkable results on NLP tasks but at the expense of huge parameter sizes and the consequent computational costs. In this paper, we propose Variator, a parameter-efficient acceleration method that enhances computational efficiency through plug-and-play compression plugins. Compression plugins are designed to

Marek Lukas, Granja Carlos, Jakubek Jan, Ingerle Jan

Hybrid semiconductor pixelated detectors from the Timepix family are advanced detectors for online particle tracking, offering energy measurement and precise time stamping capabilities for particles of various types and energies. This inherent capability makes them highly suitable for various applications, including imaging, medical fields such as radiothera

Kunze Wang, Soyeon Caren Han, Josiah Poon

Temporal Knowledge Graph Completion (TKGC) under the extrapolation setting aims to predict the missing entity from a fact in the future, posing a challenge that aligns more closely with real-world prediction problems. Existing research mostly encodes entities and relations using sequential graph neural networks applied to recent snapshots. However, these app

Ahina Nandy

Conner and Floyd determined the torsion in the special unitary bordism $\text{MSU}$ back in the late 1960s. One of the ingredients of their work was an interpolation between $\text{MSU}$ and unitary bordism $\text{MU}$. In this work, we prove an exactly similar relation between the special, and general linear algebraic cobordism $\text{MSL}$, and $\text{MGL}

Arvindh Arun, Jerrin John, Sanjai Kumaran

Language models have been shown to be rich enough to encode fMRI activations of certain Regions of Interest in our Brains. Previous works have explored transfer learning from representations learned for popular natural language processing tasks for predicting brain responses. In our work, we improve the performance of such encoders by creating an ensemble mo

Subhojeet Pramanik, Esraa Elelimy, Marlos C. Machado, Adam White

In this paper we investigate transformer architectures designed for partially observable online reinforcement learning. The self-attention mechanism in the transformer architecture is capable of capturing long-range dependencies and it is the main reason behind its effectiveness in processing sequential data. Nevertheless, despite their success, transformers

Alexandre Sac-Morane, Manolis Veveakis, Hadrien Rattez

This paper presents an extension of the discrete element method using a phase-field formulation to incorporate grain shape and its evolution. The introduction of a phase variable enables an effective representation of grain geometry and facilitates the application of physical laws, such as chemo-mechanical couplings, for modeling shape changes. These physica

Sinuo Zhang, Ivan Caicedo, Tomasz Hemperek, Toko Hirono

Silicon pixel sensors manufactured using commercial CMOS processes are promising instruments for high-energy particle physics experiments due to their high yield and proven radiation hardness. As one of the essential factors for the operation of detectors, the breakdown performance of pixel sensors constitutes the upper limit of the operating voltage. Six ty

Johannes Horn, Johannes Schwab

We study complex Lagrangians in Hitchin systems that factor through a proper subvariety of the Hitchin base non-trivially intersecting the regular locus. This gives a general framework for several examples in the literature. We compute the fiber-wise Fourier-Mukai transform of flat line bundles on visible Lagrangians. This proposes a construction of mirror d

A. C. Lehum, J. R. Nascimento, A. Yu. Petrov

In this study, we systematically calculate one-loop corrections to the Lorentz-violating vertices within the framework of CPT-odd Quantum Electrodynamics, encompassing scalar and photon fields in arbitrary gauge. Additionally, we ascertain the finite two-loop corrections to the Carroll-Field-Jackiw term. Furthermore, we analyze the UV divergent component of

J. Lerendegui-Marco, V. Alcayne, V. Babiano-Suarez, M. Bacak

Neutron capture cross-section measurements are fundamental in the study of the slow neutron capture (s-) process of nucleosynthesis and for the development of innovative nuclear technologies. One of the best suited methods to measure radiative neutron capture (n,$\gamma$) cross sections over the full stellar range of interest for all the applications is the

Ann-Kathrin Perrevoort

The observation of lepton flavour violation (LFV) in interactions involving charged leptons would be an unambiguous sign of physics beyond the Standard Model of particle physics. Given that muons can be produced at high intensities, searches for LFV with muons are particularly sensitive. In a global initiative, ongoing and upcoming experiments are aiming to

Hanlin Chen, Chen Li, Mengqi Guo, Zhiwen Yan

3D scene segmentation based on neural implicit representation has emerged recently with the advantage of training only on 2D supervision. However, existing approaches still requires expensive per-scene optimization that prohibits generalization to novel scenes during inference. To circumvent this problem, we introduce a generalizable 3D segmentation framewor

Matthew N. Palmer, Simone Faro, Stefano Scafiti

Online string matching is a computational problem involving the search for patterns or substrings in a large text dataset, with the pattern and text being processed sequentially, without prior access to the entire text. Its relevance stems from applications in data compression, data mining, text editing, and bioinformatics, where rapid and efficient pattern

Francesco Cordero, Hanna Pazniak, Thierry Ouisse, Jesus Gonzalez-Julian

A phase transition is found in Ti$_3$C$_2$T$_x$ MXene at 350 K, by measuring the complex Young's modulus of self-standing thick films. A step-like softening and increase of the mechanical losses is found below 350 K, indicative of a phase transition, where the square of the order parameter is coupled to strain. It is argued that it should be a ferroelectric

Hiroshi Morioka, Aapo Hyvärinen

A topic of great current interest is Causal Representation Learning (CRL), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is severely ill-posed since it is a combination of the two notoriously ill-posed problems of representation learning and causal discovery. Yet, finding practical identifiability condi

Imen Azaiz, Oliver Deckarm, Sven Strickroth

Timely formative feedback is considered as one of the most important drivers for effective learning. Delivering timely and individualized feedback is particularly challenging in large classes in higher education. Recently Large Language Models such as GPT-3 became available to the public that showed promising results on various tasks such as code generation