October 2022 arXiv papers — page 106

Haozhe An, Zongxia Li, Jieyu Zhao, Rachel Rudinger

A common limitation of diagnostic tests for detecting social biases in NLP models is that they may only detect stereotypic associations that are pre-specified by the designer of the test. Since enumerating all possible problematic associations is infeasible, it is likely these tests fail to detect biases that are present in a model but not pre-specified by t

Malin Horstmann, Andreas Schafer, Alexey Vladimirov

The worm-gear-T function parameterizes the probability to find a longitudinally polarized quark inside a transversely polarized hadron. We extract it from data on polarized semi-inclusive deep-inelastic scattering (SIDIS) measured at COMPASS and HERMES. As a theoretical model, we use a Wandzura-Wilczek-type approximation at the next-to-leading order. We find

Andrew Lifson, Olivier Mattelaer

In this paper, we present an extension of MadGraph5_aMC@NLO which is able to evaluate tree-level QCD matrix-elements up to $2\to 6$ (one more particle than before). To achieve this, we implemented Berends-Giele-like recursion, and re-implemented the way colour is computed such that we can now expand the colour matrix in powers of 1/Nc and truncate this expan

Anuvab Banerjee, Vibhore Negi, Ravi Joshi, Nagendra Kumar

We investigate the possible presence of quasi-periodic oscillation (QPO) signals in 2103 blazars from the Zwicky Transient Facility (ZTF) time-domain survey. We detect a low-frequency QPO signal in five blazars observed over these 3.8-year-long optical r-band ZTF light curves. These periods range from 144 days to 196 days detected at $\gtrsim 4\sigma$ signif

Panagiotis Kotetes, Hano O. M. Sura, Brian M. Andersen

We explore the spin density and charge currents arising on the surface of a topological insulator and in a 2D Rashba metal due to magnetization gradients. For topological insulators a single interconversion coefficient controls the generation of both quantities. This coefficient is quantized to a value proportional to the vorticity of the Dirac point which c

Xiaozhou Feng, Brian Skinner, Adam Nahum

Monitored many-body systems fall broadly into two dynamical phases, ``entangling'' or ``disentangling'', separated by a transition as a function of the rate at which measurements are made on the system. Producing an analytical theory of this measurement-induced transition is an outstanding challenge. Recent work made progress in the context of tree tensor ne

Emanuele Polino, Davide Poderini, Giovanni Rodari, Iris Agresti

In a Bell experiment, it is natural to seek a causal account of correlations wherein only a common cause acts on the outcomes. For this causal structure, Bell inequality violations can be explained only if causal dependencies are modelled as intrinsically quantum. There also exists a vast landscape of causal structures beyond Bell that can witness nonclassic

Andreas Sinner, Pierre A. Pantaleón, Francisco Guinea

We study the effects of strain in moir\'e systems composed of honeycomb lattices. We elucidate the formation of almost perfect one-dimensional moir\'e patterns in twisted bilayer systems. The formation of such patterns is a consequence of an interplay between twist and strain which gives rise to a collapse of the reciprocal space unit cell. As a criterion fo

Brandon Dong, Hannah Graff, Joshua Mundinger, Skye Rothstein

For a finite group $G$ with integer-valued character table and a prime $p$, we show that almost every entry in the character table of $G \wr S_N$ is divisible by $p$ as $N \to \infty$. This result generalizes the work of Peluse and Soundararajan on the character table of $S_N$.

Rosalba Perna, Evgeni Grishin

In addition to a supermassive black hole (SMBH), the central parsec of the Milky Way hosts over a hundred of massive, high velocity young stars whose existence, and organisation of a subset of them in one, or possibly two, mis-aligned disks, is puzzling. Due to a combination of low medium density and strong tidal forces in the vicinity of Sgr A*, stars are n

Paras Jain, Sam Kumar, Sarah Wooders, Shishir G. Patil

Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applications. We demonstrate that it is possible to significantly improve inter-region cloud bulk transfer throughput by adapting network overlays to the cloud setting -- that is, by rou

Grisha Zeltyn, Benny Trakhtenbrot, Michael Eracleous, Jessie Runnoe

We report the discovery of a new ``changing-look'' active galactic nucleus (CLAGN) event, in the quasar SDSS J162829.17+432948.5 at z=0.2603, identified through repeat spectroscopy from the fifth Sloan Digital Sky Survey (SDSS-V). Optical photometry taken during 2020--2021 shows a dramatic dimming of ${\Delta}$g${\approx}$1 mag, followed by a rapid recovery

A. Meenakshi McNamara, Sahil Saini, Parampreet Singh

In classical Bianchi-I spacetimes, underlying conditions for what dictates the singularity structure - whether it is anisotropic shear or energy density, can be easily determined from the generalized Friedmann equation. However, in non-singular bouncing anisotropic models these insights are difficult to obtain in the quantum gravity regime where the singular

Aaron J. Friedman, Oliver Hart, Rahul Nandkishore

We explore universality and phases of matter in hybrid quantum dynamics combining chaotic time evolution and projective measurements. We develop a unitary representation of measurements based on the Stinespring Theorem, which we crucially identify with the time evolution of the system and measurement apparatus, affording significant technical advantages and

Jorge Chávez-Carlos, Talía L. M. Lezama, Rodrigo G. Cortiñas, Jayameenakshi Venkatraman

Transmon qubits are the predominant element in circuit-based quantum information processing, such as existing quantum computers, due to their controllability and ease of engineering implementation. But more than qubits, transmons are multilevel nonlinear oscillators that can be used to investigate fundamental physics questions. Here, they are explored as sim

Assaf Voliovich, Mark S. Rudner, Yuval Oreg, Erez Berg

We investigate competing insulating phases in nearly metallic zigzag carbon nanotubes, under conditions where an applied magnetic flux approximately closes the single particle gap in one valley. Recent experiments have shown that an energy gap persists throughout magnetic field sweeps where the single-particle picture predicts that the gap should close and r

Herbi K. Dreiner, Dominik Köhler, Saurabh Nangia

The $R$-parity-violating Minimal Supersymmetric Standard Model (RPV-MSSM) can naturally accommodate massive neutrinos as required by the oscillation data. However, studying the phenomenology is complicated due to the large number of undetermined parameters involved. Thus, studies are usually restricted to specific submodels. In this work, we develop an appro

Zhoujian Zhang, Brendan P. Bowler, Trent J. Dupuy, Timothy D. Brandt

We present the latest and most precise characterization of the architecture for the ancient ($\approx 11$ Gyr) Kepler-444 system, which is composed of a K0 primary star (Kepler-444 A) hosting five transiting planets, and a tight M-type spectroscopic binary (Kepler-444 BC) with an A-BC projected separation of 66 au. We have measured the system's relative astr

Nadav Drukker, Maxime Trépanier

We present here a careful study of the holographic duals of BPS surface operators in the 6d ${\cal N}=(2,0)$ theory. Several different classes of surface operators have been recently identified and each class has a specific calibration form - a 3-form in $AdS_7\times S^4$ whose pullback to the M2-brane world-volume is equal to the volume form. In all but one

Till Sawala, Meri Teeriaho, Peter H. Johansson

The total mass of the Local Group (LG) and the masses of its primary constituents, the Milky Way and M31, are important anchors for several cosmological questions. In recent years, independent measurements have consistently yielded halo masses close to $10^{12} \mathrm{M_\odot}$ for the MW, and $1-2 \times 10^{12} \mathrm{M_\odot}$ for M31, while estimates d

Isaac H. Laseter, Steven L. Finkelstein, Micaela J. Bagley, Dustin M. Davis

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is a large-volume spectroscopic survey without pre-selection of sources, searching ~ 540 deg^2 for Lyman-alpha emitting galaxies (LAEs) at 1.9 < z < 3.5. Taking advantage of such a wide-volume survey, we perform a pilot study using early HETDEX data to search for lensed Lyman-alpha emitters. After pe

Davide Pelliciari, Sofia Contarini, Federico Marulli, Lauro Moscardini

Galaxy clusters and cosmic voids, the most extreme objects of our Universe in terms of mass and size, trace two opposite sides of the large-scale matter density field. By studying their abundance as a function of their mass and radius, respectively, i.e. the halo mass function (HMF) and void size function (VSF), it is possible to achieve fundamental constrai

Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou

Out-of-distribution (OOD) detection is vital to safety-critical machine learning applications and has thus been extensively studied, with a plethora of methods developed in the literature. However, the field currently lacks a unified, strictly formulated, and comprehensive benchmark, which often results in unfair comparisons and inconclusive results. From th

Yanjie Ze, Nicklas Hansen, Yinbo Chen, Mohit Jain

A prominent approach to visual Reinforcement Learning (RL) is to learn an internal state representation using self-supervised methods, which has the potential benefit of improved sample-efficiency and generalization through additional learning signal and inductive biases. However, while the real world is inherently 3D, prior efforts have largely been focused

Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner

Modern quantum annealers can find high-quality solutions to combinatorial optimisation objectives given as quadratic unconstrained binary optimisation (QUBO) problems. Unfortunately, obtaining suitable QUBO forms in computer vision remains challenging and currently requires problem-specific analytical derivations. Moreover, such explicit formulations impose

Hanan Gani, Muzammal Naseer, Mohammad Yaqub

Vision Transformer (ViT), a radically different architecture than convolutional neural networks offers multiple advantages including design simplicity, robustness and state-of-the-art performance on many vision tasks. However, in contrast to convolutional neural networks, Vision Transformer lacks inherent inductive biases. Therefore, successful training of s

Menelaos Kanakis, Thomas E. Huang, David Bruggemann, Fisher Yu

Multi-task learning promises better model generalization on a target task by jointly optimizing it with an auxiliary task. However, the current practice requires additional labeling efforts for the auxiliary task, while not guaranteeing better model performance. In this paper, we find that jointly training a dense prediction (target) task with a self-supervi

Zhi-Wei Sun

For each positive integer $m$, the $m$th order harmonic numbers are given by $$H_n^{(m)}=\sum_{0<k\le n}\frac1{k^m}\ \ (n=0,1,2,\ldots).$$ We discover exact values of some series involving harmonic numbers of order not exceeding four. For example, we conjecture that $$\sum_{k=0}^\infty(6k+1)\frac{\binom{2k}k^3}{256^k}\left(H_{2k}^{(3)}-\frac{7}{64}H_{k}^{(3)

Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie

Molecular dynamics (MD) simulation techniques are widely used for various natural science applications. Increasingly, machine learning (ML) force field (FF) models begin to replace ab-initio simulations by predicting forces directly from atomic structures. Despite significant progress in this area, such techniques are primarily benchmarked by their force/ene

Kuan-Lin Chen, Harinath Garudadri, Bhaskar D. Rao

A deep neural network using rectified linear units represents a continuous piecewise linear (CPWL) function and vice versa. Recent results in the literature estimated that the number of neurons needed to exactly represent any CPWL function grows exponentially with the number of pieces or exponentially in terms of the factorial of the number of distinct linea

Robin Schäfer, Benedikt Placke, Owen Benton, Roderich Moessner

We propose a simple family of valence-bond crystals as potential ground states of the $S=1/2$ and $S=1$ Heisenberg antiferromagnet on the pyrochlore lattice. Exponentially numerous in the linear size of the system, these can be visualized as hard-hexagon coverings, with each hexagon representing a resonating valence-bond ring. This ensemble spontaneously bre

Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li

The recent proliferation of NISQ devices has made it imperative to understand their computational power. In this work, we define and study the complexity class $\textsf{NISQ} $, which is intended to encapsulate problems that can be efficiently solved by a classical computer with access to a NISQ device. To model existing devices, we assume the device can (1)

Andrés Prados-Torreblanca, José M. Buenaposada, Luis Baumela

Top-performing landmark estimation algorithms are based on exploiting the excellent ability of large convolutional neural networks (CNNs) to represent local appearance. However, it is well known that they can only learn weak spatial relationships. To address this problem, we propose a model based on the combination of a CNN with a cascade of Graph Attention

Tan Yu, Jun Zhi, Yufei Zhang, Jian Li

APP-installation information is helpful to describe the user's characteristics. The users with similar APPs installed might share several common interests and behave similarly in some scenarios. In this work, we learn a user embedding vector based on each user's APP-installation information. Since the user APP-installation embedding is learnable without depe

E. Aprile, K. Abe, F. Agostini, S. Ahmed Maouloud

The XENON collaboration has published stringent limits on specific dark matter -nucleon recoil spectra from dark matter recoiling on the liquid xenon detector target. In this paper, we present an approximate likelihood for the XENON1T 1 tonne-year nuclear recoil search applicable to any nuclear recoil spectrum. Alongside this paper, we publish data and code

Tariq Yasin, Harry Desmond, Julien Devriendt, Adrianne Slyz

Rotation curves are the key observational manifestation of the dark matter distribution around late-type galaxies. In a halo model context, the precision of constraints on halo parameters is a complex function of the properties of the measurements as well as properties of the galaxy itself. Forthcoming surveys will resolve rotation curves to varying degrees

Kevin Meng, Arnab Sen Sharma, Alex Andonian, Yonatan Belinkov

Recent work has shown exciting promise in updating large language models with new memories, so as to replace obsolete information or add specialized knowledge. However, this line of work is predominantly limited to updating single associations. We develop MEMIT, a method for directly updating a language model with many memories, demonstrating experimentally

Martin Josifoski, Maxime Peyrard, Frano Rajic, Jiheng Wei

A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm remain unclear. Previous works only compare decoding algorithms in narrow scenarios, and their findings do not generalize across tasks. We argue that the misalignment between the mod

Benedikt Placke, Nikolas P. Breuckmann

We analyze the thermodynamic properties of the random-bond Ising model (RBIM) on closed hyperbolic surfaces using Monte Carlo and high-temperature series expansion techniques. We also analyze the dual-RBIM, that is the model that in the absence of disorder is related to the RBIM via the Kramers-Wannier duality. Even on self-dual lattices this model is differ

F. E. Brochero Martínez, L. Batista de Oliveira, C. R. Giraldo Vergara

In this article, we show explicitly the Wedderburn decomposition of the metacyclic group algebra $\mathbb F_qG$, where $G$ has a cyclic subgroup of index 2 and $\gcd(|G|,q)=1$. We also construct the complete set of central and left idempotents of these group algebras.

Yuhang Zang, Wei Li, Kaiyang Zhou, Chen Huang

Prompt tuning, a parameter- and data-efficient transfer learning paradigm that tunes only a small number of parameters in a model's input space, has become a trend in the vision community since the emergence of large vision-language models like CLIP. We present a systematic study on two representative prompt tuning methods, namely text prompt tuning and visu

Ronghang Hu, Shoubhik Debnath, Saining Xie, Xinlei Chen

Masked Autoencoding (MAE) has emerged as an effective approach for pre-training representations across multiple domains. In contrast to discrete tokens in natural languages, the input for image MAE is continuous and subject to additional specifications. We systematically study each input specification during the pre-training stage, and find sequence length i

Amr Abdelraouf, Mohamed Abdel-Aty, Zijin Wang, Ou Zheng

Surrogate safety measures in the form of conflict indicators are indispensable components of the proactive traffic safety toolbox. Conflict indicators can be classified into past-trajectory-based conflicts and predicted-trajectory-based conflicts. While the calculation of the former class of conflicts is deterministic and unambiguous, the latter category is

Samya Kumar Ray, Srijan Sarkar

In this article, we study the following question asked by Michael Hartz in a recent paper \cite{Hartz}: \textit{which operator spaces satisfy the column-row property?} We provide a complete classification of the column-row property for non-commutative $L_{p}$-spaces over semifinite von Neumann algebras. We study other relevant properties of operator spaces t

Nils Feldhus, Leonhard Hennig, Maximilian Dustin Nasert, Christopher Ebert

Saliency maps can explain a neural model's predictions by identifying important input features. They are difficult to interpret for laypeople, especially for instances with many features. In order to make them more accessible, we formalize the underexplored task of translating saliency maps into natural language and compare methods that address two key chall

T. Hurth, F. Mahmoudi, D. Martinez Santos, S. Neshatpour

We discuss the implications of $b \to s \ell^+\ell^-$ measurements and their deviations with respect to the Standard Model predictions in a model-independent framework. We highlight in particular the impact of the recent updated measurements including the updated $B_s \to \phi \mu^+\mu^-$ branching ratios and angular observables, the recent CMS measurement o

Erhard Scholz

This paper contains a case study of the work and self-definition of two important mathematicians during the rise of modern mathematics: Felx Hausdorff (1868--1942) and Hermann Weyl (1885--1955). The two had strongly diverging positions with regard to basic questions of mathematical methodology, which is reflected in the style and content of their mathematica

Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala

We study the convergence rate of discretized Riemannian Hamiltonian Monte Carlo on sampling from distributions in the form of $e^{-f(x)}$ on a convex body $\mathcal{M}\subset\mathbb{R}^{n}$. We show that for distributions in the form of $e^{-\alpha^{\top}x}$ on a polytope with $m$ constraints, the convergence rate of a family of commonly-used integrators is

V. Tiselko, O. Dogonasheva, A. Myshkin, O. Valba

The human structural connectome has a complex internal community organization, characterized by a high degree of overlap and related to functional and cognitive phenomena. We explored connectivity properties in connectome networks and showed that $k$-clique percolation of an anomalously high order is characteristic of the human structural connectome. The res

Bin Guo, Shaun Hampton

In the D1D5 CFT the twist operator of order 2 can twist together two copies in the untwisted sector into a single joined copy in the twisted sector. Traditionally, this effect is computed by using the covering map method. Recently, a new method was developed using the Bogoliubov ansatz and conformal symmetry to compute this effect in a toy model of one free

Benjamin G. Janesko

This work presents a new class of hybrid density functional theory (DFT) approximations, incorporating nonlocal exact exchange in predefined states such as core atomic orbitals (AOs). These projected hybrid density functionals are a flexible generalization of range-separated hybrids. This work derives projected hybrids using the Adiabatic Projection formalis

Nicholas M. Rapidis

Recent theoretical advancements have made the QCD axion a stronger dark matter candidate, especially in the sub-$\mu\text{eV}$ range. While cavity haloscopes have made significant progress in excluding QCD axions in the $1 - 100\ \mu\text{eV}$ region, the $1 \text{ peV} - 1\ \mu\text{eV}$ region remains unexplored. The DMRadio program consists of a series of

Golam Mostafa Mondal

In this paper, we first consider the graph of $(F_1,F_{2},\cdots,F_{n})$ on $\overline{\mathbb{D}}^{n},$ where $F_{j}(z)=\bar{z}^{m_{j}}_{j}+R_{j}(z),j=1,2,\cdots,n,$ which has non-isolated CR-singularities if $m_{j}>1$ for some $j\in\{1,2,\cdots,n\}.$ We show that under certain condition on $R_{j},$ the graph is polynomially convex and holomorphic polynomia

Nikola Jovanović, Mislav Balunović, Dimitar I. Dimitrov, Martin Vechev

Fair representation learning (FRL) is a popular class of methods aiming to produce fair classifiers via data preprocessing. Recent regulatory directives stress the need for FRL methods that provide practical certificates, i.e., provable upper bounds on the unfairness of any downstream classifier trained on preprocessed data, which directly provides assurance

Joseph Bolarinwa, Alex Smith, Adnan Aijaz, Aleksandar Stanoev

Communication delays and packet losses are commonly investigated issues in the area of robotic teleoperation. This paper investigates application of a novel low-power wireless control technology (GALLOP) in a haptic teleoperation scenario developed to aid in nuclear decommissioning. The new wireless control protocol, which is based on an off-the-shelf Blueto

Chao-Qiang Geng, Xiang-Nan Jin, Chia-Wei Liu

We study the ratio of $R=2 \Gamma(\Xi_c^0 \to \Xi^- e^+ \nu_e )/3\Gamma(\Lambda_c^+ \to \Lambda e^+ \nu_e )$, which is found to be $R= 1 (0.8)$ from the exact (broken) $SU(3)$ flavor symmetry, in sharp contrast to the average value of $R_{av}=0.59\pm 0.10 $ from the ALICE collaboration and lattice QCD results. We propose to use the mixing of $\Xi_c-\Xi_c'$ t

Natalie B. Hogg, Pierre Fleury, Julien Larena, Matteo Martinelli

Line-of-sight effects in strong gravitational lensing have long been treated as a nuisance. However, it was recently proposed that the line-of-sight shear could be a cosmological observable in its own right, if it is not degenerate with lens model parameters. We firstly demonstrate that the line-of-sight shear can be accurately measured from a simple simulat

Jenna C. Fromer, Connor W. Coley

Molecular discovery is a multi-objective optimization problem that requires identifying a molecule or set of molecules that balance multiple, often competing, properties. Multi-objective molecular design is commonly addressed by combining properties of interest into a single objective function using scalarization, which imposes assumptions about relative imp

Wei Guo, Jannatul Ferdous Ema, Jing-Mei Qiu

In this paper, we propose a novel Local Macroscopic Conservative (LoMaC) low rank tensor method with discontinuous Galerkin (DG) discretization for the physical and phase spaces for simulating the Vlasov-Poisson (VP) system. The LoMaC property refers to the exact local conservation of macroscopic mass, momentum and energy at the discrete level. The recently

Dipam Goswami, René Schuster, Joost van de Weijer, Didier Stricker

In class-incremental semantic segmentation (CISS), deep learning architectures suffer from the critical problems of catastrophic forgetting and semantic background shift. Although recent works focused on these issues, existing classifier initialization methods do not address the background shift problem and assign the same initialization weights to both back

Saif M. Mohammad

Words play a central role in how we express ourselves. Lexicons of word-emotion associations are widely used in research and real-world applications for sentiment analysis, tracking emotions associated with products and policies, studying health disorders, tracking emotional arcs of stories, and so on. However, inappropriate and incorrect use of these lexico

E. F. Talantsev

Experimental discovery that compressed sulphur hydride exhibits superconducting transition temperature Tc=203 K (Drozdov et al 2015 Nature 525 73) sparked intensive studies of superconducting hydrides. However, this discovery was not a straight forward experimental examination of theoretically predicted phase, instead it was nearly five-decade long experimen

Yeor Hafouta

We obtain non-uniform Berry-Esseen type estimates for several classes of weakly dependent sequences of random variables, including uniformly elliptic inhomogeneous Markov chains, random and time-varying (partially) hyperbolic or expanding dynamical systems, products of random matrices and some classes of local statistics.

Andrey Novikov

In this paper, we propose a computer-oriented method of construction of optimal group sequential hypothesis tests with variable group sizes. In particular, for independent and identically distributed observations we obtain the form of optimal group sequential tests which turn to be a particular case of sequentially planned probability ratio tests (SPPRTs, Sc

Anton Osokin, Irina Saparina, Ramil Yarullin

The task of generating a database query from a question in natural language suffers from ambiguity and insufficiently precise description of the goal. The problem is amplified when the system needs to generalize to databases unseen at training. In this paper, we consider the case when, at the test time, the system has access to an external criterion that eva

Ana Balibanu, Maxence Mayrand

We develop a general procedure for reduction along strong Dirac maps, which are a broad generalization of Poisson momentum maps. We recover a large number of familiar constructions in Poisson and quasi-Poisson geometry, and we introduce new examples of Poisson, quasi-Poisson, and Dirac reduced structures. In particular, we obtain quasi-Poisson analogues of s

Kaifeng Zhang, Yang Fu, Shubhankar Borse, Hong Cai

While 6D object pose estimation has wide applications across computer vision and robotics, it remains far from being solved due to the lack of annotations. The problem becomes even more challenging when moving to category-level 6D pose, which requires generalization to unseen instances. Current approaches are restricted by leveraging annotations from simulat

Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf

We study the class of location-scale or heteroscedastic noise models (LSNMs), in which the effect $Y$ can be written as a function of the cause $X$ and a noise source $N$ independent of $X$, which may be scaled by a positive function $g$ over the cause, i.e., $Y = f(X) + g(X)N$. Despite the generality of the model class, we show the causal direction is ident

Arsene Fansi Tchango, Rishab Goel, Julien Martel, Zhi Wen

The automation of the medical evidence acquisition and diagnosis process has recently attracted increasing attention in order to reduce the workload of doctors and democratize access to medical care. However, most works proposed in the machine learning literature focus solely on improving the prediction accuracy of a patient's pathology. We argue that this o

Ming Zhong, Yang Liu, Da Yin, Yuning Mao

Multi-dimensional evaluation is the dominant paradigm for human evaluation in Natural Language Generation (NLG), i.e., evaluating the generated text from multiple explainable dimensions, such as coherence and fluency. However, automatic evaluation in NLG is still dominated by similarity-based metrics, and we lack a reliable framework for a more comprehensive

Jacob Fox, Sammy Luo, Huy Tuan Pham, Yunkun Zhou

For a subset $A$ of an abelian group $G$, given its size $|A|$, its doubling $\kappa=|A+A|/|A|$, and a parameter $s$ which is small compared to $|A|$, we study the size of the largest sumset $A+A'$ that can be guaranteed for a subset $A'$ of $A$ of size at most $s$. We show that a subset $A'\subseteq A$ of size at most $s$ can be found so that $|A+A'| = \Ome

Ana Balibanu

In this note we show that the multiplicative Grothendieck-Springer space has a natural quasi-Poisson structure. The associated group-valued moment map is the resolution morphism, and the quasi-Hamiltonian leaves are the connected components of the preimages of Steinberg fibers. This is a multiplicative analogue of the standard Poisson structure on the additi

Vincent Russo, Andrea Mari, Nathan Shammah, Ryan LaRose

We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers to evaluate the performance of quantum error mitigation in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation which we call the improvement factor, and calculate this metric for each expe

Dustin D. Nguyen, Todd A. Thompson, Evan E. Schneider, Sebastian Lopez

The analytic galactic wind model derived by Chevalier and Clegg in 1985 (CC85) assumes $\textit{uniform}$ energy and mass-injection within the starburst galaxy nucleus. However, the structure of nuclear star clusters, bulges, and star-forming knots are non-uniform. We generalize to cases with spherically-symmetric energy/mass injection that scale as $r^{-\De

Sonja Žunar

Let $ \Gamma $ be a congruence subgroup of $ \mathrm{Sp}_{2n}(\mathbb Z) $. Using Poincar\'e series of $ K $-finite matrix coefficients of integrable discrete series representations of $ \mathrm{Sp}_{2n}(\mathbb R) $, we construct a spanning set for the space $ S_m(\Gamma) $ of Siegel cusp forms of weight $ m\in\mathbb Z_{>2n} $. We prove the non-vanishing o

Jiajie Chen, Thomas Y. Hou

Inspired by numerical evidence of a potential 3D Euler singularity \cite{luo2014potentially,luo2013potentially-2}, we prove finite-time, nearly self-similar blowup of the 2D Boussinesq and 3D axisymmetric Euler equations with smooth initial data of finite energy and boundary. The proof encounters several essential difficulties. One of the essential difficult

Anne Theurkauf, Qi Heng Ho, Roland Ilyes, Nisar Ahmed

We consider the problem of autonomous navigation using limited information from a remote sensor network. Because the remote sensors are power and bandwidth limited, we use event-triggered (ET) estimation to manage communication costs. We introduce a fast and efficient sampling-based planner which computes motion plans coupled with ET communication strategies

Yen Meng, Hsuan-Jui Chen, Jiatong Shi, Shinji Watanabe

Compressing self-supervised models has become increasingly necessary, as self-supervised models become larger. While previous approaches have primarily focused on compressing the model size, shortening sequences is also effective in reducing the computational cost. In this work, we study fixed-length and variable-length subsampling along the time axis in sel

Ankita Gupta, Marzena Karpinska, Wenlong Zhao, Kalpesh Krishna

Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been collected via complex and lengthy guidelines that are curated for linguistic experts. These concerns have sparked a growing interest among researchers to curate a unified set of gui

Katherine Van Koevering, Yiquan Hong, Jon Kleinberg

The COVID-19 pandemic has been a global health crisis playing out in the age of social media. Even though the virtual environment makes interaction possible regardless of physical location, many of the most pressing issues during the pandemic -- case counts, lockdown policies, vaccine availability -- have played out in an intensely local fashion. Reflecting

Guan-Ting Lin, Chi-Luen Feng, Wei-Ping Huang, Yuan Tseng

Self-Supervised Learning (SSL) from speech data has produced models that have achieved remarkable performance in many tasks, and that are known to implicitly represent many aspects of information latently present in speech signals. However, relatively little is known about the suitability of such models for prosody-related tasks or the extent to which they e

Nelson Vadori, Leo Ardon, Sumitra Ganesh, Thomas Spooner

We study a game between liquidity provider and liquidity taker agents interacting in an over-the-counter market, for which the typical example is foreign exchange. We show how a suitable design of parameterized families of reward functions coupled with shared policy learning constitutes an efficient solution to this problem. By playing against each other, ou

Sachit Menon, Carl Vondrick

Vision-language models (VLMs) such as CLIP have shown promising performance on a variety of recognition tasks using the standard zero-shot classification procedure -- computing similarity between the query image and the embedded words for each category. By only using the category name, they neglect to make use of the rich context of additional information th

Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Dan MacKinlay

Machine learning-based modeling of physical systems has experienced increased interest in recent years. Despite some impressive progress, there is still a lack of benchmarks for Scientific ML that are easy to use but still challenging and representative of a wide range of problems. We introduce PDEBench, a benchmark suite of time-dependent simulation tasks b

Yang Fu, Ishan Misra, Xiaolong Wang

We propose a generalizable neural radiance fields - MonoNeRF, that can be trained on large-scale monocular videos of moving in static scenes without any ground-truth annotations of depth and camera poses. MonoNeRF follows an Autoencoder-based architecture, where the encoder estimates the monocular depth and the camera pose, and the decoder constructs a Multi

Oscar Mañas, Pau Rodriguez, Saba Ahmadi, Aida Nematzadeh

Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. We propose MAPL, a simple and parameter-efficient method that reuses frozen pre-trained unimodal models and leverages their strong generalization capabilities in multimodal vision-language (VL) settings. MAPL learns a lightw

Alexander Gorsky, Vladimir Kazakov, Fedor Levkovich-Maslyuk, Victor Mishnyakov

Using the matrix-forest theorem and the Parisi-Sourlas trick we formulate and solve a one-matrix model with non-polynomial potential which provides perturbation theory for massive spinless fermions on dynamical planar graphs. This is a lattice version of 2d quantum gravity coupled to massive spinless fermions. Our model equivalently describes the ensemble of

Kazuto Akiba, Nobuaki Umeshita, Tatsuo C. Kobayashi

We discover superconductivity (SC) in LaAgSb$_2$ at ambient pressure and its close correlation with a charge density wave (CDW) under pressure. The superconducting transition temperature ($T_c$) exhibits a sharp peak at the CDW critical pressure of 3.2 GPa. We demonstrate that the carriers inhabiting the Sb-square net is crucial not only in the formation of

Jong In Han, Sijong Kwak

It is well known that the Eisenbud-Goto regularity conjecture is true for arithmetically Cohen-Macaulay varieties, projective curves, smooth surfaces, smooth threefolds in $\mathbb{P}^5$, and toric varieties of codimension two. After J. McCullough and I. Peeva constructed counterexamples in 2018, it has been an interesting question to find the categories suc

Nadia Benlakhouy, Ahmed Jellal, El Houssine Atmani

The conductance through single-layer graphene (SLG) and AA/AB-stacked bilayer graphene (BLG) junctions is obtained by taking into account band gap and bias voltage terms. First, we consider gapped SLG, while in between, they are connected into pristine BLG. For Fermi energy larger than the interlayer hopping, the conductance as a function of the bilayer regi

Ali Baktash, Dieter Horns, Manuel Meyer

The nearby GRB221009A at redshift $z=0.1505$ has been observed up to a maximum energy of 18 TeV with the LHAASO air shower array. The expected optical depth for a photon with energy $E_\gamma=18$ TeV varies between 9.4 and 27.1 according to existing models of the extra-galactic background light (EBL) in the relevant mid infra-red range. The resulting suppres

Zheng Wang, Juncheng B Li, Shuhui Qu, Florian Metze

Quantization is an effective technique to reduce memory footprint, inference latency, and power consumption of deep learning models. However, existing quantization methods suffer from accuracy degradation compared to full-precision (FP) models due to the errors introduced by coarse gradient estimation through non-differentiable quantization layers. The exist

Subhajeet Karmakar, Sachindra Naik, Jeewan C. Pandey, Igor S. Savanov

We present an in-depth study of a large and long duration ($>$1.3 days) X-ray flare observed on an RS CVn type eclipsing binary system SZ Psc using observations from Swift observatory. In the 0.35$-$10 keV energy band, the peak luminosity is estimated to be 4.2$\times$10$^{33}$ erg s$^{-1}$. The quiescent corona of SZ Psc was observed $\sim$5.67 d after the

Dean P. Foster, Sergiu Hart

Calibration means that forecasts and average realized frequencies are close. We develop the concept of forecast hedging, which consists of choosing the forecasts so as to guarantee that the expected track record can only improve. This yields all the calibration results by the same simple basic argument while differentiating between them by the forecast-hedgi

Julia Beuster, Carsten Andrich, Michael Döbereiner, Steffen Schieler

This paper presents an experimental measurement platform for the research and development of unmanned aerial vehicles (UAVs) localization algorithms using radio emission and reflectivity. We propose a cost-effective, flexible testbed made from commercial off-the-shelf (COTS) devices to allow academic research regarding the upcoming integration of UAV surveil

Alina Dubovskaya, Susan C. Fennell, Kevin Burke, James P. Gleeson

Mean-field equations have been developed recently to approximate the dynamics of the Deffuant model of opinion formation. These equations can describe both fully-mixed populations and the case where individuals interact only along edges of a network. In each case, interactions only occur between individuals whose opinions differ by less than a given paramete

Pierre Salati

Dark matter particles could be the major component of the haloes of galaxies. Their mutual annihilations or decays would produce an indirect signature under the form of high-energy cosmic-rays. The focus of this presentation is on antimatter species, a component so rare that any excess over the background should be easily detected. After a recap on Galactic

Donato Bini, Thibault Damour, Andrea Geralico

We compute to high post-Newtonian accuracy the 4-momentum (linear momentum, and energy), radiated as gravitational waves in a two-body system undergoing gravitational scattering. We include, for the first time, all the relevant {\it time-asymmetric} effects that arise when consistently going three post Newtonian orders beyond the leading post Newtonian order

Kazuma Kobayashi, James Daniell, Shoaib Usman, Dinesh Kumar

The Gaussian Process (GP)-based surrogate model has the inherent capability of capturing the anomaly arising from limited data, lack of data, missing data, and data inconsistencies (noisy/erroneous data) present in the modeling and simulation component of the digital twin framework, specifically for the accident tolerant fuel (ATF) concepts. However, GP will

Shun-Sheng Li, Konrad Kuijken, Henk Hoekstra, Lance Miller

We present SKiLLS, a suite of multi-band image simulations for the weak lensing analysis of the complete Kilo-Degree Survey (KiDS), dubbed KiDS-Legacy analysis. The resulting catalogues enable joint shear and redshift calibration, enhancing the realism and hence accuracy over previous efforts. To create a large volume of simulated galaxies with faithful prop