February 2024 arXiv papers — page 118

Shir Ashury-Tahan, Ariel Gera, Benjamin Sznajder, Leshem Choshen

Model selection for a given target task can be costly, as it may entail extensive annotation of the quality of outputs of different models. We introduce DiffUse, an efficient method to make an informed decision between candidate text generation models based on preference annotations. DiffUse reduces the required amount of annotations, thus saving valuable ti

Ayesha Siddika Nipu, Siming Liu, Anthony Harris

Distributed decision-making in multi-agent systems presents difficult challenges for interactive behavior learning in both cooperative and competitive systems. To mitigate this complexity, MAIDRL presents a semi-centralized Dense Reinforcement Learning algorithm enhanced by agent influence maps (AIMs), for learning effective multi-agent control on StarCraft

Mugdha Khedkar, Eric Bodden

Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). Since app developers are not legal experts, they find it difficult to write privacy-aware source code. Moreover, they

Nicolas Borghini, Hendrik Roch, Alicia Schütte

We determine the uncorrelated modes that characterize the fluctuations in a semi-realistic model for the initial state of high-energy nuclear collisions, consisting of hot spots whose positions are distributed independently. Varying the number of hot spots, their size, and the weights with which they contribute to the initial state, we find that the paramete

Mateusz Kuniej, Paweł Machnikowski, Michał Gawełczyk

State transfer between different quantum systems is key for successful quantum technologies. Over long distances, photons are irreplaceable, but on short ranges in miniaturized complex devices or hybrid systems, coupling via orders of magnitude shorter-wavelength acoustic waves has great potential. With interfaces to light, acoustic waves, and more, opticall

Akiyoshi Park, Adrian Llanos, Chun-I Lu, Yinan Chen

Quantum Anomalous Hall (QAH) state in six quintuple layer Cr$_{0.1}$(Bi$_{0.2}$Sb$_{0.8}$)$_{1.9}$Te$_3$ thin films were studied through scanning tunneling spectroscopy (STS) and electrical transport measurements. While the surface state is gapless above the Curie temperature ($T_\mathrm{C} \approx 30$ K), scanning tunneling spectroscopy (STS) of the sample

Adam F. Kowalski

Magnetic storms on stars manifest as remarkable, randomly occurring changes of the luminosity over durations that are tiny in comparison to the normal evolution of stars. These stellar flares are bursts of electromagnetic radiation from X-ray to radio wavelengths, and they occur on most stars with outer convection zones. They are analogous to the events on t

Erfan Mehdipour Abadi, Masoud H. Nazari

The evolving landscape of electric power networks, influenced by the integration of distributed energy resources require the development of novel power system monitoring and control architectures. This paper develops algorithm to monitor and detect anomalies of different parts of a power system that cannot be measured directly, by applying neighboring measur

Qiang Miao, Thomas Barthel

The optimization of quantum circuits can be hampered by a decay of average gradient amplitudes with increasing system size. When the decay is exponential, this is called the barren plateau problem. Considering explicit circuit parametrizations (in terms of rotation angles), it has been shown in Arrasmith et al., Quantum Sci. Technol. 7, 045015 (2022) that ba

Somi Gupta, Francesco Pavese

An affine spread is a set of subspaces of $\mathrm{AG}(n, q)$ of the same dimension that partitions the points of $\mathrm{AG}(n, q)$. Equivalently, an {\em affine spread} is a set of projective subspaces of $\mathrm{PG}(n, q)$ of the same dimension which partitions the points of $\mathrm{PG}(n, q) \setminus H_{\infty}$; here $H_{\infty}$ denotes the hyperpl

Hongliang Jiang, Arkady A. Tseytlin

We consider a $\frac{1}{2}$-BPS solution for a D3 brane probe in AdS$_5 \times S^5$ that has world-volume geometry of AdS$_3 \times S^1$. It intersects the boundary over a surface that represents a dimension 2 defect in the boundary N=4 SYM theory. The effective action of the probe brane is proportional to the logarithmically divergent volume of AdS$_3$ and

Rafael Ceja Ayala, Isaac Harris, Andreas Kleefeld

In this paper, we consider the direct and inverse problem for isotropic scatterers with two conductive boundary conditions. First, we show the uniqueness for recovering the coefficients from the known far-field data at a fixed incident direction for multiple frequencies. Then, we address the inverse shape problem for recovering the scatterer for the measured

E. Santamaría, J. A. Toalá, M. A. Guerrero, G. Ramos-Larios

We present the analysis of archival Very Large Telescope (VLT) MUSE and multi-epoch Hubble Space Telescope (HST) WFPC2 and WFC3/UVIS narrow-band observations of the remnant associated with the ejecta of the mid-nineteenth century outburst of the recurrent nova T Pyx. These data sets are used to investigate its true 3D physical structure and the nebular expan

Giacomo Zonneveld, Lorenzo Principi, Marco Baldi

Early detection of network intrusions and cyber threats is one of the main pillars of cybersecurity. One of the most effective approaches for this purpose is to analyze network traffic with the help of artificial intelligence algorithms, with the aim of detecting the possible presence of an attacker by distinguishing it from a legitimate user. This is common

Yangxinyu Xie, Bowen Jiang, Tanwi Mallick, Joshua David Bergerson

Recent advancement of large language models (LLMs) represents a transformational capability at the frontier of artificial intelligence. However, LLMs are generalized models, trained on extensive text corpus, and often struggle to provide context-specific information, particularly in areas requiring specialized knowledge, such as wildfire details within the b

Victor Zhong, Dipendra Misra, Xingdi Yuan, Marc-Alexandre Côté

We introduce Language Feedback Models (LFMs) that identify desirable behaviour - actions that help achieve tasks specified in the instruction - for imitation learning in instruction following. To train LFMs, we obtain feedback from Large Language Models (LLMs) on visual trajectories verbalized to language descriptions. First, by using LFMs to identify desira

Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes

In modern machine learning, models can often fit training data in numerous ways, some of which perform well on unseen (test) data, while others do not. Remarkably, in such cases gradient descent frequently exhibits an implicit bias that leads to excellent performance on unseen data. This implicit bias was extensively studied in supervised learning, but is fa

Daniele Marchei, Emanuela Merelli, Andrew Francis

Finding a minimal factorization for a generic semigroup can be done by using the Froidure-Pin Algorithm, which is not feasible for semigroups of large sizes. On the other hand, if we restrict our attention to just a particular semigroup, we could leverage its structure to obtain a much faster algorithm. In particular, $\mathcal{O}(N^2)$ algorithms are known

Robert Quigley

It is shown that any two clauses in an instance of 3SAT sharing the same terminal which is positive in one clause and negated in the other can imply a new clause composed of the remaining terms from both clauses. Clauses can also imply other clauses as long as all the terms in the implying clauses exist in the implied clause. It is shown an instance of 3SAT

Mauricio Godoy Molina

We give sufficient conditions on a labeled direct graph to determine whether the Tanaka prolongation of its associated Lie algebra is infinite-dimensional. In the case that all directed edges are labeled differently, the corresponding graph Lie algebra is of infinite type if and only if the graph has a vertex of degree one.

Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao

Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interaction with the world, for example robotic control. However, VLMs produce only textual outputs, while robotic control and other spatial tasks require outputting continuous coordinates,

Jakub Krajewski, Jan Ludziejewski, Kamil Adamczewski, Maciej Pióro

Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties, incorporating an expanded range of variables. Specifically, we introduce a new hyperparameter, granularity, whose adjustment enables precise control over the size of the experts. B

Artem Chernikov, Henry Towsner

We investigate various forms of (model-theoretic) stability for hypergraphs and their corresponding strengthenings of the hypergraph regularity lemma with respect to partitions of vertices. On the one hand, we provide a complete classification of the various possibilities in the ternary case. On the other hand, we provide an example of a family of slice-wise

Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines

We study asynchronous federated learning mechanisms with nodes having potentially different computational speeds. In such an environment, each node is allowed to work on models with potential delays and contribute to updates to the central server at its own pace. Existing analyses of such algorithms typically depend on intractable quantities such as the maxi

Yacine Mehtar-Tani, Daniel Pablos, Konrad Tywoniuk

Azimuthal anisotropies of high-$p_T$ particles produced in heavy-ion collisions are understood as an effect of a geometrical selection bias. Particles oriented in the direction in which the QCD medium formed in these collisions is shorter, suffer less energy loss, and thus, are over-represented in the final ensemble compared to those oriented in the directio

Sahel Iqbal, Adrien Corenflos, Simo Särkkä, Hany Abdulsamad

In this paper, we propose a novel approach to Bayesian experimental design for non-exchangeable data that formulates it as risk-sensitive policy optimization. We develop the Inside-Out SMC$^2$ algorithm, a nested sequential Monte Carlo technique to infer optimal designs, and embed it into a particle Markov chain Monte Carlo framework to perform gradient-base

Wei Zou, Runpeng Geng, Binghui Wang, Jinyuan Jia

Large language models (LLMs) have achieved remarkable success due to their exceptional generative capabilities. Despite their success, they also have inherent limitations such as a lack of up-to-date knowledge and hallucination. Retrieval-Augmented Generation (RAG) is a state-of-the-art technique to mitigate these limitations. The key idea of RAG is to groun

Anthony Bazhenov, Pahan Dewasurendra, Giri Krishnan, Jean Erik Delanois

The performance of artificial neural networks (ANNs) degrades when training data are limited or imbalanced. In contrast, the human brain can learn quickly from just a few examples. Here, we investigated the role of sleep in improving the performance of ANNs trained with limited data on the MNIST and Fashion MNIST datasets. Sleep was implemented as an unsuper

Kathryn E. Kirchoff, James Wellnitz, Joshua E. Hochuli, Travis Maxfield

Nearest neighbor-based similarity searching is a common task in chemistry, with notable use cases in drug discovery. Yet, some of the most commonly used approaches for this task still leverage a brute-force approach. In practice this can be computationally costly and overly time-consuming, due in part to the sheer size of modern chemical databases. Previous

Zhenhuan Liu, Xingjian Zhang, Yue-Yang Fei, Zhenyu Cai

Quantum error mitigation is a key approach for extracting target state properties on state-of-the-art noisy machines and early fault-tolerant devices. Using the ideas from flag fault tolerance and virtual state purification, we develop the virtual channel purification (VCP) protocol, which consumes similar qubit and gate resources as virtual state purificati

Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang

Visually-conditioned language models (VLMs) have seen growing adoption in applications such as visual dialogue, scene understanding, and robotic task planning; adoption that has fueled a wealth of new models such as LLaVa, InstructBLIP, and PaLI-3. Despite the volume of new releases, key design decisions around image preprocessing, architecture, and optimiza

Jordan Taylor, Ellen Simpson, Anh-Ton Tran, Jed Brubaker

LGBTQ+ people have received increased attention in HCI research, paralleling a greater emphasis on social justice in recent years. However, there has not been a systematic review of how LGBTQ+ people are researched or discussed in HCI. In this work, we review all research mentioning LGBTQ+ people across the HCI venues of CHI, CSCW, DIS, and TOCHI. Since 2014

Tamio-Vesa Nakajima, Stanislav Živný

Goemans and Williamson designed a 0.878-approximation algorithm for Max-Cut in undirected graphs [JACM'95]. Khot, Kindler, Mosel, and O'Donnel showed that the approximation ratio of the Goemans-Williamson algorithm is optimal assuming Khot's Unique Games Conjecture [SICOMP'07]. In the problem of maximum cuts in directed graphs (Max-DiCut), in which we seek a

Philipp Schoenegger, Peter S. Park, Ezra Karger, Sean Trott

Large language models (LLMs) match and sometimes exceeding human performance in many domains. This study explores the potential of LLMs to augment human judgement in a forecasting task. We evaluate the effect on human forecasters of two LLM assistants: one designed to provide high-quality ("superforecasting") advice, and the other designed to be overconfiden

Ashutosh Marwah, Frédéric Dupuis

Device imperfections and memory effects can result in undesired correlations among the states generated by a realistic quantum source. These correlations are called source correlations. Proving the security of quantum key distribution (QKD) protocols in the presence of these correlations has been a persistent challenge. We present a simple and general method

J. Serrano Bell, R. F. Díaz, G. Hébrard, E. Martioli

We report the characterization of two planet candidates detected by the Transiting Exoplanet Survey Satellite (TESS), TOI-1199 b and TOI-1273 b, with periods of 3.7 and 4.6 days, respectively. Follow-up observations for both targets, which include several ground-based light curves, confirmed the transit events. High-precision radial velocities from the SOPHI

Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu

A major threat to the peer-review systems of computer science conferences is the existence of "collusion rings" between reviewers. In such collusion rings, reviewers who have also submitted their own papers to the conference work together to manipulate the conference's paper assignment, with the aim of being assigned to review each other's papers. The most s

Mirelle Bueno, Roberto Lotufo, Rodrigo Nogueira

Language models are now capable of solving tasks that require dealing with long sequences consisting of hundreds of thousands of tokens. However, they often fail on tasks that require repetitive use of simple rules, even on sequences that are much shorter than those seen during training. For example, state-of-the-art LLMs can find common items in two lists w

Bradley T. Baker, Mustafa S. Salman, Zening Fu, Armin Iraji

In the clinical treatment of mood disorders, the complex behavioral symptoms presented by patients and variability of patient response to particular medication classes can create difficulties in providing fast and reliable treatment when standard diagnostic and prescription methods are used. Increasingly, the incorporation of physiological information such a

Florian Dorsch

We prove that arbitrary simplicial manifolds satisfy Kan conditions in a suitable local sense. This allows us to expand a technique for differentiating higher Lie groupoids worked out in current research to the setting of general simplicial manifolds. Consequently, we derive a method to differentiate simplicial manifolds into higher Lie algebroids.

Karen M. Leighly, Hyunseop Choi, Michael Eracleous, Donald M. Terndrup

We present the optical-near infrared spectral energy distributions (SED) and near infrared variability properties of 30 low-redshift iron low-ionization Broad Absorption Line quasars (FeLoBALQs) and matched samples of LoBALQs and unabsorbed quasars. Significant correlations between the SED properties and accretion rate indicators found among the unabsorbed c

Ali Kheirkhah Barzoki

Chemical bioreactions play a significant role in many of the microfluidic devices, and their applications in biomedical science have seen substantial growth. Given that effective mixing is vital for initiating biochemical reactions in many applications, micromixers have become increasingly prevalent for high-throughput assays. In this study, numerical study

Abbas Taheri, Saeid Alikhani

A number $\alpha$ has a representation with respect to the numbers $\alpha_1,...,\alpha_n$, if there exist the non-negative integers $\lambda_1,... ,\lambda_n$ such that $\alpha=\lambda_1\alpha_1+...+\lambda_n \alpha_n$. The largest natural number that does not have a representation with respect to the numbers $\alpha_1,...,\alpha_n$ is called the Frobenius

Matthias Johann Steiner

Arora & Ge introduced a noise-free polynomial system to compute the secret of a Learning With Errors (LWE) instance via linearization. Albrecht et al. later utilized the Arora-Ge polynomial model to study the complexity of Gr\"obner basis computations on LWE polynomial systems under the assumption of semi-regularity. In this paper we revisit the Arora-Ge pol

Apoorva Narula, Aastha Jain, Jatin Batra, MN Rajeevan

The Indian summer monsoon is a highly complex and critical weather system that directly affects the livelihoods of over a billion people across the Indian subcontinent. Accurate short-term forecasting remains a major scientific challenge due to the monsoon's intrinsic nonlinearity and its sensitivity to multi-scale drivers, including local land-atmosphere in

Jose Manuel Iglesias, Elena Pascual, Maria J. Martin, Raul Rengel

In this paper we explore the capabilities of MoS2 and WS2 2D monolayers to produce radiation in the terahertz range by generation of high-order harmonics. This phenomenon, which is a result of the non-linear response of the electronic carrier population to the applied electric field, is studied by using a particle ensemble stochastic simulation approach base

Duston Wetzel, Paul Gailiunas, Moses Gaither-Ganim, William Holt

Weaving typically involves forming a sufrace by interlacing fibers into a mechanically stable arrangement, effectively making a two-dimensional object out of one-dimensional objects. Moorish Fretwork involves interweaving solid helical elements into mechanically stable two-dimensional arrangements by exploiting the helices' screw symmetry. A three-dimensiona

Indrani Nilima, Mujeeb Hasan, B. K. Singh, Mohammad Yousuf Jamal

In this study, we investigate the potential of heavy quarkonia within a magnetized hot QGP medium having finite momentum anisotropy. The phenomenon of inverse magnetic catalysis is introduced into the system, influencing the magnetic field-modified Debye mass and thereby altering the effective quark masses. Concurrently, the impact of momentum anisotropy in

Arnoldo Guerra, Narciso Román-Roy

In this paper, we define canonical lifts of vector fields to the multisymplectic multimomentum bundles of De Donder-Weyl Hamiltonian first-order field theories and to the appropriate premultisymplectic embedded constraint submanifolds on which singular field theories are studied. These new canonical lifts are used to study the so-called natural Noether symme

Bastian Boll, Daniel Gonzalez-Alvarado, Christoph Schnörr

This paper introduces a novel generative model for discrete distributions based on continuous normalizing flows on the submanifold of factorizing discrete measures. Integration of the flow gradually assigns categories and avoids issues of discretizing the latent continuous model like rounding, sample truncation etc. General non-factorizing discrete distribut

William Leeney, Ryan McConville

Graph Neural Networks (GNNs) can be trained to detect communities within a graph by learning from the duality of feature and connectivity information. Currently, the common approach for optimisation of GNNs is to use comparisons to ground-truth for hyperparameter tuning and model selection. In this work, we show that nodes can be clustered into communities w

Mingzhe Du, Anh Tuan Luu, Bin Ji, Qian Liu

Amidst the recent strides in evaluating Large Language Models for Code (Code LLMs), existing benchmarks have mainly focused on the functional correctness of generated code, neglecting the importance of their computational efficiency. To fill the gap, we present Mercury, the first code efficiency benchmark for Code LLMs. It comprises 1,889 Python tasks, each

Simone Cepollaro, Goffredo Chirco, Gianluca Cuffaro, Gianluca Esposito

How complex is the structure of quantum geometry? In several approaches, the spacetime atoms are obtained by the SU(2) intertwiner called quantum tetrahedron. The complexity of this construction has a concrete consequence in recent efforts to simulate such models and toward experimental demonstrations of quantum gravity effects. There are, therefore, both a

Yamen Hamdouni

We show that the uncertainty principle product for the position and momentum operators for a system described by the Hamiltonian $ \hat H= \frac{\hat{p}^2}{2m} +\frac{1}{2} m \omega^2 \hat{x}^2+\frac{\mu}{2}(\hat x \hat p+ \hat p \hat x)$ where $\mu<\omega$ reads $\Delta x \Delta p\ge\frac{\hbar \omega}{2\sqrt{\omega^2-\mu^2}}$. All the values bellow this lo

Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min

Membership inference attacks (MIAs) attempt to predict whether a particular datapoint is a member of a target model's training data. Despite extensive research on traditional machine learning models, there has been limited work studying MIA on the pre-training data of large language models (LLMs). We perform a large-scale evaluation of MIAs over a suite of l

Kenan Qu, Sebastian Meuren, Nathaniel J. Fisch

Although existing technology cannot yet directly produce fields at the Schwinger level, experimental facilities can already explore strong-field QED phenomena by taking advantage of the Lorentz boost of energetic electron beams. Recent studies show that QED cascades can create electron-positron pairs at sufficiently high density to exhibit collective plasma

Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann

Structural pruning of neural networks conventionally relies on identifying and discarding less important neurons, a practice often resulting in significant accuracy loss that necessitates subsequent fine-tuning efforts. This paper introduces a novel approach named Intra-Fusion, challenging this prevailing pruning paradigm. Unlike existing methods that focus

Masoud Molaei

A canonical formalism for quantum electrodynamics in curved spacetime is developed. This formalism enables a systematic investigation of photons in the Schwarzschild gravitational field, yielding novel results as well as refining previous results that were predicted by heuristic methods. The claim that "the gravitational redshift is a shift in the sharp freq

Jose Manuel Iglesias, Elena Pascual, Sergio Garcia-Sanchez, Raul Rengel

The transient high-frequency noise response of two-dimensional MoS2 under abrupt large signal switching field conditions is studied by means of an ensemble Monte Carlo simulator. Low-to-high and high-to-low transitions are analyzed at low (77 K) and room temperature, considering several underlying substrates. The incorporation of stochastic individual scatte

Mohammed Adjieteh, Vytaras Brazauskas

In this paper, the problem of robust estimation and validation of location-scale families is revisited. The proposed methods exploit the joint asymptotic normality of sample quantiles (of i.i.d random variables) to construct the ordinary and generalized least squares estimators of location and scale parameters. These quantile least squares (QLS) estimators a

Clement Yung

Call a subset of $\mathbf{FIN}_k$ small if it does not contain a copy of $\langle{A\rangle}$ for some infinite block sequence $A \in \mathbf{FIN}_k^{[\infty]}$. Gowers' $\mathbf{FIN}_k$ theorem asserts that the set of small subsets of $\mathbf{FIN}_k$ forms an ideal, so it is sensible to consider almost disjoint families of $\mathbf{FIN}_k$ with respect to t

Jose Manuel Iglesias, Alejandra Nardone, Raul Rengel, Karol Kalna

The effect of degeneracy and the impact of free-carrier screening on a low-field mobility and a high-field drift velocity in MoS2 and WS2 are explored using an in-house ensemble Monte Carlo simulator. Electron low field mobility increases to 8400 cm2/Vs for MoS2 and to 12040 cm2/Vs for WS2 when temperature decreases to 77 K and carrier concentration is aroun

Qiuhao Zeng, Wei Wang, Fan Zhou, Gezheng Xu

In the field of domain generalization, the task of constructing a predictive model capable of generalizing to a target domain without access to target data remains challenging. This problem becomes further complicated when considering evolving dynamics between domains. While various approaches have been proposed to address this issue, a comprehensive underst

Mark L. Lewis, Shannon M Tefft

Let $D(x_1, x_2, ..., x_n)=(x_1+x_2 \;\text{mod} \; m, x_2+x_3 \; \text{mod} \; m, ..., x_n+x_1 \; \text{mod} \; m)$ where $D \in End(\mathbb{Z}_m^n)$ be the Ducci function. The sequence $\{D^k(\mathbf{u})\}_{k=0}^{\infty}$ will eventually enter a cycle. If $n=3$, we aim to establish the longest a cycle can be for a given $m$.

Md Rafid Islam, Ratun Rahman

In the past few years, the number of IoT devices has grown substantially, and this trend is likely to continue. An increasing amount of effort is being put into developing software for the ever-increasing IoT devices. Every IoT system at its core has software that enables the devices to function efficiently. But security has always been a concern in this age

Máté Kedves, Tamás Pápai, Gergő Fülöp, Kenji Watanabe

We experimentally investigate the electronic transport properties of a three-terminal graphene Josephson junction. We find that self-heating effects strongly influence the behaviour of this multiterminal Josephson junction (MTJJ) system. We show that existing simulation methods based on resistively and capacitively shunted Josephson junction networks can be

Nathanael S. Schwindt, Mor Avidar, Razi Epsztein, Anthony P. Straub

Major efforts in recent years have been directed towards understanding molecular transport in polymeric membranes, in particular reverse osmosis and nanofiltration membranes. Transition-state theory is an increasingly common approach to explore mechanisms of transmembrane permeation with molecular details, but most applications treat all free energy barriers

Maryam Mudassar, Riley W. Chien, Daniel Gottesman

To implement a quantum error correction protocol, we first need a scheme to prepare our state in the correct subspace of the code, and this can be done using a unitary encoding circuit. Majorana codes are special since any gates that transform such codes must preserve fermionic parity. In this paper, we present an algorithm that uses the stabilizer matrix to

A. Sadeghi, F. Shojai, F. Bahmani

Here we consider the generalized Oppenheimer-Snyder collapse of a star into a four-dimensional Einstein-Gauss-Bonnet black hole as well as a class of regular black holes labeled by the polytropic index of the stellar matter. We then analyze the nature of the horizon and the corresponding surface gravity outside and inside the star. The Hayward and Nielsen-Vi

Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, Wei-Yin Ko

Recent breakthroughs in large language models (LLMs) have centered around a handful of data-rich languages. What does it take to broaden access to breakthroughs beyond first-class citizen languages? Our work introduces Aya, a massively multilingual generative language model that follows instructions in 101 languages of which over 50% are considered as lower-

Michael P. May

We apply the Inclusion-Exclusion Principle to a unique pair of prime number subsequences to determine whether these subsequences form a small set or a large set and thus whether the infinite sum of the inverse of their terms converges or diverges. In this paper, we analyze the complementary prime number subsequences P(prime) and P(double-prime) as well as re

Alexandre Arias Junior, Alessia Ascanelli, Marco Cappiello, Claudia Garetto

In this paper we investigate the well-posedness of the Cauchy problem for a Schr\"odinger operator with singular lower order terms. We allow distributional coefficients and we approach this problem via the regularising methods at the core of the theory of very weak solutions. We prove that a very weak solution exists and it is unique modulo negligible pertur

Kostas Karpouzis, Dimitris Pantazatos, Joanna Taouki, Kalliopi Meli

The advent of Generative AI (GenAI) in education presents a transformative approach to traditional teaching methodologies, which often overlook the diverse needs of individual students. This study introduces a GenAI tool, based on advanced natural language processing, designed as a digital assistant for educators, enabling the creation of customized lesson p

Severance Graham, Kathryn Volk

Neptune's external mean motion resonances play an important role in sculpting the observed population of transneptunian objects (TNOs). The population of scattering TNOs are known to 'stick' to Neptune's resonances while evolving in semimajor axis ($a$), though simulations show that resonance sticking is less prevalent at $a\gtrsim200-250$ au. Here we presen

Zhengzhong Yi, Zhipeng Liang, Zicheng Wang, Jiahan Chen

Quantum stabilizer codes face the problem of low coding rate. In this article, following the idea of recursively expanding Tanner graph proposed in our previous work, we try to construct new stabilizer codes with high coding rate, and propose XZ-type Tanner-graph-recursive-expansion (XZ-TGRE) code and Tanner-graph-recursive-expansion hypergraph product (TGRE

Sarah L. Thomson, Léni K. Le Goff, Emma Hart, Edgar Buchanan

Morpho-evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and control. Previous research has provided empirical comparisons between encodings in terms of their performance with respect

Parikshit Gopalan, Lunjia Hu, Guy N. Rothblum

Consider a multi-class labelling problem, where the labels can take values in $[k]$, and a predictor predicts a distribution over the labels. In this work, we study the following foundational question: Are there notions of multi-class calibration that give strong guarantees of meaningful predictions and can be achieved in time and sample complexities polynom

Yethreb Essouda, Hung T. Diep, Mohamed Ellouze

We show by extensive Monte Carlo simulations that we need a multi-spin interaction in addition to pairwise interactions in order to reproduce the temperature dependence of the experimental magnetization observed in the perovskite compound Pr$_{0.67}$Sr$_{0.33}$MnO$_{3}$. The multi-spin interaction is introduced in the Hamiltonian as follows: each spin intera

Shivanand Venkanna Sheshappanavar, Tejas Anvekar, Shivanand Kundargi, Yufan Wang

Fine-grained grocery object recognition is an important computer vision problem with broad applications in automatic checkout, in-store robotic navigation, and assistive technologies for the visually impaired. Existing datasets on groceries are mainly 2D images. Models trained on these datasets are limited to learning features from the regular 2D grids. Whil

Z Liu, J Lou, W Bao, Y Hu

Fine-tuning on task-specific datasets is a widely-embraced paradigm of harnessing the powerful capability of pretrained LLMs for various downstream tasks. Due to the popularity of LLMs fine-tuning and its accompanying privacy concerns, differentially private (DP) fine-tuning of pretrained LLMs has been widely used to safeguarding the privacy of task-specific

Anna Mosolova, Marie Candito, Carlos Ramisch

While static word embeddings are blind to context, for lexical semantics tasks context is rather too present in contextual word embeddings, vectors of same-meaning occurrences being too different (Ethayarajh, 2019). Fine-tuning pre-trained language models (PLMs) using contrastive learning was proposed, leveraging automatically self-augmented examples (Liu et

H. Abdollahzadeh Ahangar, M. Chellali, S. M. Sheikholeslami, J. C. Valenzuela-Tripodoro

A Roman $\{2\}$-dominating function (R2F) is a function $f:V\rightarrow \{0,1,2\}$ with the property that for every vertex $v\in V$ with $f(v)=0$ there is a neighbor $u$ of $v$ with $f(u)=2$, or there are two neighbors $x,y$ of $v$ with $f(x)=f(y)=1$. A total Roman $\{2\}$-dominating function (TR2DF) is an R2F $f$ such that the set of vertices with $f(v)>0$

Qianyu Chen, Bradley Dirks, Mircea Mustaţă

We give an introduction to the theory of $V$-filtrations of Malgrange and Kashiwara. After discussing the basic properties of this construction (in the case of a smooth hypersurface and, later, in the general case), we describe the connection with the theory of $b$-functions. As an example, we treat the case of weighted homogeneous isolated singularities. We

Naseela Pervez, Alexander J. Titus

Biotechnology Industry 5.0 is advancing with the integration of cutting-edge technologies like Machine Learning (ML), the Internet Of Things (IoT), and cloud computing. It is no surprise that an industry that utilizes data from customers and can alter their lives is a target of a variety of attacks. This chapter provides a perspective of how Machine Learning

Ricardo Jesús Ramos Castillo

We study the geometry of super curves with a chosen supervolume form. We consider the algebra of divergence free vector fields $S(1|N)$ associated to such curves. When $N=2$ its derived algebra, called $S(2)$, defines a special family of curves, named $S(2)$-super curves. We exhibit an involution on the moduli space of such curves that generalizes Deligne's

Zhongpai Gao, Huayi Zhou, Abhishek Sharma, Meng Zheng

The detection of human parts (e.g., hands, face) and their correct association with individuals is an essential task, e.g., for ubiquitous human-machine interfaces and action recognition. Traditional methods often employ multi-stage processes, rely on cumbersome anchor-based systems, or do not scale well to larger part sets. This paper presents PBADet, a nov

James Creswell, Viatcheslav Mukhanov, Yaron Oz

Shell model turbulence is a simplified mathematical framework that captures essential features of incompressible fluid turbulence such as the energy cascade, intermittency and anomalous scaling of the fluid observables. We perform a precision analysis of shell model of a complex velocity field in the steady state turbulent regime, including a calculation of

Thomas Pouplin, Hao Sun, Samuel Holt, Mihaela van der Schaar

Large Language Models (LLMs) have demonstrated the strong potential to assist both clinicians and the general public with their extensive medical knowledge. However, their application in healthcare is constrained due to concerns about the privacy of data used in training, which prevents the integration of private and personal information because of security

David Antony Selby

PageRank and the Bradley-Terry model are competing approaches to ranking entities such as teams in sports tournaments or journals in citation networks. The Bradley-Terry model is a classical statistical method for ranking based on paired comparisons. The PageRank algorithm ranks nodes according to their importance in a network. Whereas Bradley-Terry scores a

Sergey Avvakumov, Alexander Nabutovsky

We investigate the dependence on the dimension in the inequalities that relate the Euclidean volume of a closed submanifold $M^n\subset \mathbb{R}^N$ with its $l^\infty$-width $W^{l^\infty}_{n-1}(M^n)$ defined as the infimum over all continuous maps $ϕ:M^n\longrightarrow K^{n-1}\subset\mathbb{R}^N$ of $sup_{x\in M^n}\Vert ϕ(x)-x\Vert_{l^\infty}$. We prove th

Simon Apers, Laurent Miclo

A quantum walk is the quantum analogue of a random walk. While it is relatively well understood how quantum walks can speed up random walk hitting times, it is a long-standing open question to what extent quantum walks can speed up the spreading or mixing rate of random walks on graphs. In this expository paper, inspired by a blog post by Terence Tao, we des

Julius Vetter, Guy Moss, Cornelius Schröder, Richard Gao

Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distribution estimation. This problem can be ill-posed, however, since many different source distributions might produce the same distribution of data-consistent simulations. To make a princ

Laure Marêché

The zero-temperature stochastic Ising model is a special case of the famous stochastic Ising model of statistical mechanics, and the voter model is another classical model in this field. In both models, each vertex of the graph $\mathbb{Z}^d$ can have one of two states, and can change state to match the state of its neighbors. In 2017, Morris proposed genera

Maude Wagner, Donald R. Hedeker, Tianhao Wang, Graciela Muniz-Terrera

Several mixed-effects models for longitudinal data have been proposed to accommodate the non-linearity of late-life cognitive trajectories and assess the putative influence of covariates on it. No prior research provides a side-by-side examination of these models to offer guidance on their proper application and interpretation. In this work, we examined five

Luis Angel Mayoral-Astorga, Masoud Shabaninezhad, Howard Northfield, Spyridon Ntais

We report the fabrication and characterization of a plasmonic metasurface comprising electrically contacted sub-wavelength gold dipole nanoantennas, conformally coated by a thin hafnia film, an indium tin oxide layer and a backside mirror, forming metal-oxide-semiconductor (MOS) capacitors, for use as an electrically-tunable reflectarray or metasurface. By v

A. Varghese, M. Arana-Catania, S. Mori, A. Encinas-Oropesa

Gas turbine superalloys experience hot corrosion, driven by factors including corrosive deposit flux, temperature, gas composition, and component material. The full mechanism still needs clarification and research often focuses on laboratory work. As such, there is interest in causal discovery to confirm the significance of factors and identify potential mis

Samuele Crespi, Mohamad Ali-Dib, Ian Dobbs-Dixon

One common approach for solving collisions between protoplanets in simulations of planet formation is to employ analytical scaling laws. The most widely used one was developed by Leinhardt & Stewart (2012) from a catalog of ~ 180 N-body simulations of rubble-pile collisions. In this work, we use a new catalogue of more than 20,000 SPH simulations to test the

Gen Li, Zhihan Huang, Yuting Wei

Consistency models, which were proposed to mitigate the high computational overhead during the sampling phase of diffusion models, facilitate single-step sampling while attaining state-of-the-art empirical performance. When integrated into the training phase, consistency models attempt to train a sequence of consistency functions capable of mapping any point

O. A. Ilinskaya, A. I. Ryzhov, S. N. Shevchenko

A theory of detection of microwave photons with a flux qubit-based detector is presented. We consider semiclassical approximation with the electromagnetic field being in a coherent state. Flux qubit is considered as a multilevel quantum system (qudit). By solving the Lindblad equation, we describe the time evolution of occupations of the qudit's levels for r

Toby Rodel, Daniel Bayliss, Samuel Gill, Faith Hawthorn

We present a study of the detection efficiency for the TESS mission, focusing on the yield of longer-period transiting exoplanets ($P > 25$ days). We created the Transit Investigation and Recoverability Application (TIaRA) pipeline to use real TESS data with injected transits to create sensitivity maps which we combine with occurrence rates derived from Kepl