February 2024 arXiv papers — page 39

Xiaowen Dong

We construct Toda brackets in unstable motivic homotopy theory and prove some fundamental properties of them. Furthermore we construct some examples of motivic Toda brackets.

Ashfiqun Mustari, Rushmia Ahmed, Afsara Tasnim, Jakia Sultana Juthi

This paper proposes an efficient system for classifying cervical cancer cells using pre-trained convolutional neural networks (CNNs). We first fine-tune five pre-trained CNNs and minimize the overall cost of misclassification by prioritizing accuracy for certain classes that have higher associated costs or importance. To further enhance the performance of th

Felix Brandt, Matthias Greger, Erel Segal-Halevi, Warut Suksompong

We study the problem of aggregating distributions, such as budget proposals, into a collective distribution. An ideal aggregation mechanism would be Pareto efficient, strategyproof, and fair. Most previous work assumes that agents evaluate budgets according to the $\ell_1$ distance to their ideal budget. We investigate and compare different models from the l

Guangyu Zhu, Yiqin Deng, Xianhao Chen, Haixia Zhang

Federated learning (FL) allows multiple parties (distributed devices) to train a machine learning model without sharing raw data. How to effectively and efficiently utilize the resources on devices and the central server is a highly interesting yet challenging problem. In this paper, we propose an efficient split federated learning algorithm (ESFL) to take f

Martin Buck, Kasso Okoudjou

A graph short-time Fourier transform is defined using the eigenvectors of the graph Laplacian and a graph heat kernel as a window parametrized by a non-negative time parameter $t$. We show that the corresponding Gabor-like system forms a frame for $\mathbb{C}^d$ and give a description of the spectrum of the corresponding frame operator in terms of the graph

Andrea Porro, Thomas Duguet, Jean-Paul Ebran, Mikael Frosini

Giant resonances (GRs) are a striking manifestation of collective motions in atomic nuclei. The present paper is the second in a series of four dedicated to the use of the projected generator coordinate method (PGCM) for the ab initio determination of the isoscalar giant monopole resonance (GMR) in closed- and open-shell mid-mass nuclei. While the first pape

Andrey Belogaev, Xiaoman Shen, Chun Pan, Xingfeng Jiang

Real-time applications (RTA) tend to play a crucial role in people's everyday life. Such applications are among the key use cases for the next generations of wireless technologies. RTA applications are characterized by strict guaranteed delay requirements (in the order of a few milliseconds). One of the pillars of enabling RTA in next-generation Wi-Fi standa

Alexander Kastner, Clark Lyons

We give an elementary proof that in a Borel family of games, the set of games for which player II has a winning strategy is Baire measurable, universally measurable, and completely Ramsey in the case where $X = [\mathbb{N}]^{\aleph_0}$.

Xiangyu Gao, Youchen Luo, Ali Alansari, Yaping Sun

This paper introduces MMW-Carry, a system designed to predict the probability of individuals carrying various objects using millimeter-wave radar signals, complemented by camera input. The primary goal of MMW-Carry is to provide a rapid and cost-effective preliminary screening solution, specifically tailored for non-super-sensitive scenarios. Overall, MMW-Ca

S. Arbabi, P. Deuar, R. Bennacer, Z. Che

With most of the focus to date having been on the coalescence of freely suspended droplets, much less is known about the coalescence of sessile droplets, especially in the case of droplets laden with surfactant. Here, we employ large-scale molecular dynamics simulations to investigate this phenomenon on substrates with different wettability. In particular, w

Ying Shen, Zhiyang Xu, Qifan Wang, Yu Cheng

Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in diverse tasks across different domains, with an increasing focus on improving their zero-shot generalization capabilities for unseen multimodal tasks. Multimodal instruction tuning has emerged as a successful strategy for achieving zero-shot generalization by fine-tuning pre

Jinkun Cao, Jiangmiao Pang, Kris Kitani

We propose a new visual hierarchical representation paradigm for multi-object tracking. It is more effective to discriminate between objects by attending to objects' compositional visual regions and contrasting with the background contextual information instead of sticking to only the semantic visual cue such as bounding boxes. This compositional-semantic-co

Chen Zhao, Zhihui Xu, Pukar Baral, Michel Esposito

Coronary artery disease (CAD) stands as the leading cause of death worldwide, and invasive coronary angiography (ICA) remains the gold standard for assessing vascular anatomical information. However, deep learning-based methods encounter challenges in generating semantic labels for arterial segments, primarily due to the morphological similarity between arte

Lunet Yifru, Ali Baheri

Reinforcement learning (RL) has revolutionized decision-making across a wide range of domains over the past few decades. Yet, deploying RL policies in real-world scenarios presents the crucial challenge of ensuring safety. Traditional safe RL approaches have predominantly focused on incorporating predefined safety constraints into the policy learning process

Abdelhak Kelious, Mounir Okirim

This study introduces a dedicated model aimed at solving the BRAINTEASER task 9 , a novel challenge designed to assess models lateral thinking capabilities through sentence and word puzzles. Our model demonstrates remarkable efficacy, securing Rank 1 in sentence puzzle solving during the test phase with an overall score of 0.98. Additionally, we explore the

Jozsef Konczer

This work contains the mathematical exploration of a few prototypical games in which central concepts from statistics and probability theory naturally emerge. The first two kinds of games are termed Fisher and Bayesian games, which are connected to Frequentist and Bayesian statistics, respectively. Later, a more general type of game is introduced, termed Sta

Jeremy M. Wachter

I describe the assessment framework of labor-based contract grading (LBCG). In a labor-based grading scheme, the time and effort ("labor") a student spends on an assignment determines the credit they receive; the contract component requires students to design projects with clearly-defined goals and deliverables which must be satisfied to earn credit. LBCG is

Sumit Goel, Wade Hann-Caruthers

We study a multi-agent contract design problem with moral hazard. In our model, each agent exerts costly effort towards an individual task at which it may either succeed or fail, and the principal, who wishes to encourage effort, has an exclusive-use budget that it can use to reward the agents. A motivating application is crowdsourcing for innovation, where

Gustavo Jasso, Julian Külshammer

This paper surveys recent contructions in higher Auslander--Reiten theory. We focus on those which, due to their combinatorial properties, can be regarded as higher dimensional analogues of path algebras of linearly oriented type $\mathbb{A}$ quivers. These include higher dimensional analogues of Nakayama algebras, of the mesh category of type $\mathbb{Z}\ma

Caglar Koca, Ozgur B. Akan

Molecular Communication (MC) architectures suffer from molecular build-up in the channel if they do not have appropriate reuptake mechanisms. The molecular build-up either leads to intersymbol interference (ISI) or reduces the transmission rate. To measure the molecular build-up, we derive analytic expressions for the incidence rate and absorption rate for o

Pieter Roffelsen, Alexander Stokes

Recently, B. Yang and J. Yang derived a family of rational solutions to the Sasa-Satsuma equation, and showed that any of its members constitutes a partial-rogue wave provided that an associated generalised Okamoto polynomial has no real roots or no imaginary roots. In this paper, we derive exact formulas for the number of real and the number of imaginary ro

Alexander Berkovich, Aritram Dhar

In this paper, we conjecture an extension to Bressoud's 1996 generalization of Borwein's famous 1990 conjecture. We then state a few infinite hierarchies of non-negative $q$-series identities which are interesting examples of our proposed conjecture and Bressoud's generalized conjecture. Finally, using certain positivity-preserving transformations for $q$-bi

Hamilton Sawczuk, Edinah Gnang

We propose an algebraic model of computation which formally relates symbolic listings, complexity of Boolean functions, and low depth arithmetic circuit complexity. In this model algorithms are arithmetic formula expressing symbolic listings of YES instances of Boolean functions, and computation is executed via partial differential operators. We consider the

Alexander V. Bulgakov, Juraj Sládek, Jan Hrabovský, Inam Mirza

A study of damage and ablation of silicon induced by two individual femtosecond laser pulses of different wavelengths, 1030 and 515 nm, is performed to address the physical mechanisms of dual-wavelength ablation and reveal possibilities for increasing the ablation efficiency. The produced ablation craters and damaged areas are analyzed as a function of time

Stephen Pasteris, Chris Hicks, Vasilios Mavroudis

Running backpropagation end to end on large neural networks is fraught with difficulties like vanishing gradients and degradation. In this paper we present an alternative architecture composed of many small neural networks that interact with one another. Instead of propagating gradients back through the architecture we propagate vector-valued messages comput

Abdelkarim Ben Sada, Amar Khelloufi, Abdenacer Naouri, Huansheng Ning

The recent advancements in small-size inference models facilitated AI deployment on the edge. However, the limited resource nature of edge devices poses new challenges especially for real-time applications. Deploying multiple inference models (or a single tunable model) varying in size and therefore accuracy and power consumption, in addition to an edge serv

Michael C. Daugherty, Peter H. Jacobse, Jingwei Jiang, Joaquim Jornet-Somoza

The integration of low-energy states into bottom-up engineered graphene nanoribbons (GNRs) is a robust strategy for realizing materials with tailored electronic band structure for nanoelectronics. Low-energy zero-modes (ZMs) can be introduced into nanographenes (NGs) by creating an imbalance between the two sublattices of graphene. This phenomenon is exempli

Ward Struyve

Lorentz invariance is considered a fundamental property of relativistic quantum theory. However, in standard quantum theory this invariance is only partially realized: while relativistic wave equations like the Dirac equation are Lorentz invariant, the collapse postulate is not. In the non-relativistic domain, alternative theories have been formulated, like

Ramita Sarkar, Soumik Mahanti, Prasanta K. Panigrahi

This paper explores the fundamental relationship between the geometry of entanglement and von Neumann entropy, shedding light on the intricate nature of quantum correlations. We provide a comprehensive overview of entanglement, highlighting its crucial role in quantum mechanics. Our focus centers on the connection between entanglement, von Neumann entropy, a

Michał Stęchły

This document is a pdf version of the series of blogposts about variational quantum algorithms (VQA) I originally posted on my blog Musty Thoughts. It provides an explanation of the basic variational algorithms, such as Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA), as well as a more general framework for VQAs. I

Manuel D. De la Iglesia, Carlos F. Lardizabal

Quantum Markov chains (QMCs) are positive maps on a trace-class space describing open quantum dynamics on graphs. Such objects have a statistical resemblance with classical random walks, while at the same time it allows for internal (quantum) degrees of freedom. In this work we study continuous-time QMCs on the integer line, half-line and finite segments, so

Paul-Henry Leemann, Tatiana Nagnibeda, Alexandra Skripchenko, Georgii Veprev

To a subshift over a finite alphabet, one can naturally associate an infinite family of finite graphs, called its Rauzy graphs. We show that for a subshift of subexponential complexity the Rauzy graphs converge to the line $\mathbf{Z}$ in the sense of Benjamini-Schramm convergence if and only if its complexity function $p(n)$ is unbounded and satisfies $\lim

Oscar Amador, Ignacio Soto, Manuel Urueña, Maria Calderon

Vehicular networks use Decentralized Congestion Control (DCC) mechanisms to operate effectively, but this mechanism may introduce queuing delays. Freshness of Cooperative Awareness Messages (CAMs) is critical for their usefulness. In this letter we explore how the presence of other types of traffic additional to CAMs, even with lower priorities, has an impac

Mikolaj Fraczyk, Alexander Gorodnik, Amos Nevo

The present paper is devoted to establishing an optimal approximation exponent for the action of an irreducible uniform lattice subgroup of a product group on its proper factors. Previously optimal approximation exponents for lattice actions on homogeneous spaces were established under the assumption that the restriction of the automorphic representation to

Fatemeh Fazel Hesar, Bernard Foing

This study presents a comprehensive evaluation of various classification algorithms used for the detection of exoplanets using labeled time series data from the Kepler mission. The study investigates the performance of six commonly employed algorithms, namely Random Forest, Support Vector Machine, Logistic Regression, K-Nearest Neighbors, Naive Bayes, and De

Ayan Datta, Aryan Chandramania, Radhika Mamidi

This document contains the details of the authors' submission to the proceedings of SemEval 2024's Task 8: Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection Subtask A (monolingual) and B. Detection of machine-generated text is becoming an increasingly important task, with the advent of large language models (LLMs). In t

Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng

The tension between persuasion and privacy preservation is common in real-world settings. Online platforms should protect the privacy of web users whose data they collect, even as they seek to disclose information about these data to selling advertising spaces. Similarly, hospitals may share patient data to attract research investments with the obligation to

Sam Buss, Emre Yolcu

Regular resolution is a refinement of the resolution proof system requiring that no variable be resolved on more than once along any path in the proof. It is known that there exist sequences of formulas that require exponential-size proofs in regular resolution while admitting polynomial-size proofs in resolution. Thus, with respect to the usual notion of si

Ziyi Yang, Xinyu Gao, Yangtian Sun, Yihua Huang

The recent advancements in 3D Gaussian splatting (3D-GS) have not only facilitated real-time rendering through modern GPU rasterization pipelines but have also attained state-of-the-art rendering quality. Nevertheless, despite its exceptional rendering quality and performance on standard datasets, 3D-GS frequently encounters difficulties in accurately modeli

Tong Chen, Alireza Ghasemi, Junyi Zhang, Liyu Shi

A supersolid is a quantum-entangled state of matter exhibiting the dual characteristics of superfluidity and solidity. Theory predicts that hard-core bosons with repulsive interactions on a triangular lattice can form supersolid phases at half filling and near complete filling. Leveraging an exact mapping between bosons and spin-$\frac{1}{2}$ degrees of free

Krishnendu De, Uday Chand De, Aydin Gezer

In this article, we presumed that a perfect fluid is the source of the gravitational field while analyzing the solutions to the Einstein field equations. With this new and creative approach, here we study $k$-almost yamabe solitons and gradient $k$-almost yamabe solitons. First, two examples are constructed to ensure the existence of gradient $k$-almost Yama

Tal Cohen, Tsachik Gelander

This book is concerned with analytic approaches of studying groups and their actions. Much attention is devoted to the study of amenability and Kazhdan's property (T), which are perhaps the most important analytic properties of a group, but we also discuss other analytic notions. We tried to introduce tricks, ideas and lemmas that repeatedly turn out to be u

Oskar Laverny, Philippe Lambert

We consider the class of Erlang mixtures for the task of density estimation on the positive real line when the only available information is given as local moments, a histogram with potentially higher order moments in some bins. By construction, the obtained moment problem is ill-posed and requires regularization. Several penalties can be used for such a tas

Li Pang, Xiangyu Rui, Long Cui, Hongzhong Wang

Hyperspectral image (HSI) restoration aims at recovering clean images from degraded observations and plays a vital role in downstream tasks. Existing model-based methods have limitations in accurately modeling the complex image characteristics with handcraft priors, and deep learning-based methods suffer from poor generalization ability. To alleviate these i

Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma

Obtaining the desired effect of drugs is highly dependent on their molecular geometries. Thus, the current prevailing paradigm focuses on 3D point-cloud atom representations, utilizing graph neural network (GNN) parametrizations, with rotational symmetries baked in via E(3) invariant layers. We prove that such models must necessarily disregard chirality, a g

A. Fronzetti Colladon., F. Grippa

Communication plays a pivotal role in driving change, influencing human behavior, and solving problems. Chapter 2 explores the pragmatic power of communication, drawing examples and research to illustrate its impact on people's perceptions and actions. The chapter examines how varied perceptions of reality impact responses and highlights the importance of un

Haotian Xia, Zhengbang Yang, Yuqing Wang, Rhys Tracy

A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP). This holds particular significance in the context of evaluating and advancing Large Language Models (LLMs), given the existing gap in specialized benchmarks. To bridge this gap, we introduce SportQA, a novel benchmark spe

Bryan R Christ, Jonathan Kropko, Thomas Hartvigsen

Math word problems are critical K-8 educational tools, but writing them is time consuming and requires extensive expertise. To be educational, problems must be solvable, have accurate answers, and, most importantly, be educationally appropriate. We propose that language models have potential to support K-8 math education by automatically generating word prob

Martin Bauer, Nicolas Charon, Tom Needham, Mao Nishino

Dynamical formulations of optimal transport (OT) frame the task of comparing distributions as a variational problem which searches for a path between distributions minimizing a kinetic energy functional. In applications, it is frequently natural to require paths of distributions to satisfy additional conditions. Inspired by this, we introduce a model for dyn

Uday Chand De, Krishnendu De, Fusun Ozen Zengin, Sezgin Altay Demirbag

The main aim of this article is to investigate a spacetime of quasi-constant sectional curvature. At first, the existence of such a spacetime is established by several examples. We have shown that a spacetime of quasi-constant sectional curvature agrees with the present state of the universe and it represents a Robertson Walker spacetime. Moreover, if the sp

Yuanzhe Peng, Jieming Bian, Jie Xu

The fusion of complementary multimodal information is crucial in computational pathology for accurate diagnostics. However, existing multimodal learning approaches necessitate access to users' raw data, posing substantial privacy risks. While Federated Learning (FL) serves as a privacy-preserving alternative, it falls short in addressing the challenges posed

Hui Chen, Pinjun Zheng, Yu Ge, Ahmed Elzanaty

High-frequency communication systems bring extremely large aperture arrays (ELAA) and large bandwidths, integrating localization and (bi-static) sensing functions without extra infrastructure. Such systems are likely to operate in the near-field (NF), where the performance of localization and sensing is degraded if a simplified far-field channel model is con

Vaishali Guleria, Eshete Gebrehana, Shashank Bhatnagar

In this work we study the E1 decay processes, $^3P_1$ $\rightarrow$ $^3S_1\gamma$, and $^3S_1$ $\rightarrow$ $^3P_1\gamma$ in the framework of Bethe-Salpeter equation and calculate their decay widths. We have used algebraic forms of Salpeter wave functions obtained through analytic solutions of mass spectral equations for ground and excited states of $^3S_1$

Atul Singh Arora, Jérémie Roland, Chrysoula Vlachou, Stephan Weis

Weak coin flipping is an important cryptographic primitive$\unicode{x2013}$it is the strongest known secure two-party computation primitive that classically becomes secure only under certain assumptions (e.g. computational hardness), while quantumly there exist protocols that achieve arbitrarily close to perfect security. This breakthrough result was establi

Young Jin Suh, Krishnendu De, Uday Chand De

This article concerns with the characterization of a spacetime and modified gravity, such as $f\left(R,G\right)$, $f\left(R,T\right)$ and $f\left(R,L_{m}\right)$-gravity equipped with the projective curvature tensor. We establish that a projectively flat perfect fluid spacetime represents dark energy era. Also, we prove that a projectively flat perfect fluid

Jiawei Zhou, Linye Lyu, Daojing He, Yu Li

Adversarial camouflage is a widely used physical attack against vehicle detectors for its superiority in multi-view attack performance. One promising approach involves using differentiable neural renderers to facilitate adversarial camouflage optimization through gradient back-propagation. However, existing methods often struggle to capture environmental cha

Jiazhao Zhang, Kunyu Wang, Rongtao Xu, Gengze Zhou

Vision-and-language navigation (VLN) stands as a key research problem of Embodied AI, aiming at enabling agents to navigate in unseen environments following linguistic instructions. In this field, generalization is a long-standing challenge, either to out-of-distribution scenes or from Sim to Real. In this paper, we propose NaVid, a video-based large vision

Prithwijita Ray, H. Pai, S. Chakraborty, A. Mukherjee

The negative parity states in 116Sn have been investigated in terms of octupole correlation. The same is probed by using the Indian National Gamma Array (INGA) facility at Variable Energy Cyclotron Centre, Kolkata using the reaction, 114Cd({\alpha},2n) 116Sn at 34 MeV energy. Three new {\gamma}-transitions relevant to the present investigation are reported a

Tom Bachmann, Robert Burklund

We show that for any separably closed field $k$ of characteristic $p>0$, the canonical functor from nilpotent $p$-adic spaces to $\mathbb{E}_{\infty}$-coalgebras over $k$ (given by singular chains with coefficients in $k$) is fully faithful. We also identify the essential image of simply connected spaces inside coalgebras. This dualizes and removes finitenes

Pedro Braga, Georgios Chionas, Piotr Krysta, Stefanos Leonardos

Maximal Extractable Value (MEV) has emerged as a new frontier in the design of blockchain systems. In this paper, we propose making the MEV extraction rate as part of the protocol design space. Our aim is to leverage this parameter to maintain a healthy balance between block producers (who need to be compensated) and users (who need to feel encouraged to tra

Maxim Arnold, Lael Costa, Serge Tabachnikov

We study, theoretically and experimentally, a 1-parameter family of transformations and their limiting vector field on the space of plane polygons. These transformations are discrete analogs of completely integrable transformation on closed plane curves, known as the bicycle correspondence, that is a geometric realization of the B\"acklund transformation of

Junjie Cao, Xinglong Jia, Jingwei Lian

We investigate three intriguing anomalies within the framework of the General Next-to-Minimal Supersymmetric Standard Model. These anomalies include a significant deviation of the experimental results for the muon anomalous magnetic moment from its Standard Model prediction, with a confidence level of $5.1\sigma$; a joint observation by the CMS and ATLAS col

Hamed Fayyaz, Abigail Strang, Niharika S. D'Souza, Rahmatollah Beheshti

Polysomnography (PSG) is a type of sleep study that records multimodal physiological signals and is widely used for purposes such as sleep staging and respiratory event detection. Conventional machine learning methods assume that each sleep study is associated with a fixed set of observed modalities and that all modalities are available for each sample. Howe

Krishnendu De, Uday Chand De, Aydin Gezer

This article carries out the investigation of a three-dimensional Riemannian manifold $N^3$ endowed with a semi-symmetric type non-metric connection. Firstly, we construct a non-trivial example to prove the existence of a semi-symmetric type non-metric connection on $N^{3}$. It is established that a $N^3$ with the semi-symmetric type non-metric connection, w

Monica Marra

The foundation of two very early Usenet newsgroups in astrophysics, still existent today, and some milestones in their history have been tracked from the origins at Princeton University in 1983 to 1994. They result to be pioneering experiences in this discipline, and among the earliest ones of this kind in academic disciplines at large. To the best of our kn

Deven R. Desai, Mark Riedl

Copyright and computer science continue to intersect and clash, but they can coexist. The advent of new technologies such as digitization of visual and aural creations, sharing technologies, search engines, social media offerings, and more challenge copyright-based industries and reopen questions about the reach of copyright law. Breakthroughs in artificial

Murali Gunti, Roberto Rojas-Cessa

In Named Data Networking (NDN), data is identified by unique names instead of IP addresses, and routers use the names of the content to forward Interest packets towards the producers of the requested content. However, the current content search mechanism in NDN is complex and slow. This mechanism not only creates congestion but also hinders practical deploym

Qingyuan Wang, Silin Ren, Ruoyu Yin, Klaus Ziegler

We investigate a quantum walk on a ring represented by a directed triangle graph with complex edge weights and monitored at a constant rate until the quantum walker is detected. To this end, the first hitting time statistics is recorded using unitary dynamics interspersed stroboscopically by measurements, which is implemented on IBM quantum computers with a

Francisco Mota

In this note we explore the relationship between the operation of convolution of functions and the Eulerian integrals. This approach allow us to obtain some expressions for the convolution of a certain class of functions in terms of the Gamma Function as well as to derive some well known properties of the Gamma Function by using the concept and properties of

Dayong Liu, Huanyin Chen

In this paper, we present new presentations of group inverse for the sum of two group invertible elements in a Banach algebra. We then apply these results to block complex matrices. The group invertibility of certain block complex matrices is thereby obtained.

Demao Kong, Daneng Yang, Hai-Bo Yu

van Dokkum et al. (arXiv:2309.07969) reported the discovery of JWST-ER1, a strong lensing object at redshift $z\approx2$, using data from the James Webb Space Telescope. The lens mass within the Einstein ring is $5.9$ times higher than the expected stellar mass from a Chabrier initial mass function, indicating a high dark matter density. In this work, we sho

Daniel A. Serino, Allen Alvarez Loya, Joshua W. Burby, Ioannis G. Kevrekidis

Singularly perturbed dynamical systems play a crucial role in climate dynamics and plasma physics. A powerful and well-known tool to address these systems is the Fenichel normal form, which significantly simplifies fast dynamics near slow manifolds through a transformation. However, this normal form is difficult to realize in conventional numerical algorithm

Soyoung Yoon, Eunbi Choi, Jiyeon Kim, Hyeongu Yun

We propose ListT5, a novel reranking approach based on Fusion-in-Decoder (FiD) that handles multiple candidate passages at both train and inference time. We also introduce an efficient inference framework for listwise ranking based on m-ary tournament sort with output caching. We evaluate and compare our model on the BEIR benchmark for zero-shot retrieval ta

Sayan Bandyapadhyay, Jie Xue

Geometric matching is an important topic in computational geometry and has been extensively studied over decades. In this paper, we study a geometric-matching problem, known as geometric many-to-many matching. In this problem, the input is a set $S$ of $n$ colored points in $\mathbb{R}^d$, which implicitly defines a graph $G = (S,E(S))$ where $E(S) = \{(p,q)

Ashish Chandra, Zhengjiang Li, Qiang Wen

Recently it was proposed that, the AdS/BCFT correspondence can be simulated by a holographic Weyl transformed CFT$_2$, where the cut-off brane plays the role of the Karch-Randall (KR) brane \cite{Basu:2022crn}. In this paper, we focus on the Weyl transformation that optimizes the path integral computation of the reduced density matrix for a single interval i

Vinay Malvimat, Somnath Porey, Baishali Roy

In this study, we analyze Krylov Complexity in two-dimensional conformal field theories subjected to deformed SL$(2,\mathbb{R})$ Hamiltonians. In the vacuum state, we find that the K-complexity exhibits a universal phase structure. The phase structure involves the K-complexity exhibiting an oscillatory behaviour in the non-heating phase, which contrasts with

Paloma T. Lima, Martin Milanič, Peter Muršič, Karolina Okrasa

For a tree decomposition $\mathcal{T}$ of a graph $G$, by $\mu(\mathcal{T})$ we denote the size of a largest induced matching in $G$ all of whose edges intersect one bag of $\mathcal{T}$. Induced matching treewidth of a graph $G$ is the minimum value of $\mu(\mathcal{T})$ over all tree decompositions $\mathcal{T}$ of $G$. Yolov [SODA 2018] proved that Max We

Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg

Large language models (LLMs) have demonstrated impressive performance on a number of natural language processing tasks, such as question answering and text summarization. However, their performance on sequence labeling tasks such as intent classification and slot filling (IC-SF), which is a central component in personal assistant systems, lags significantly

Ekansh Chauhan, Amit Sharma, Megha S Uppin, C. V. Jawahar

The effective management of brain tumors relies on precise typing, subtyping, and grading. This study advances patient care with findings from rigorous multiple instance learning experimentations across various feature extractors and aggregators in brain tumor histopathology. It establishes new performance benchmarks in glioma subtype classification across m

Sabri Koraltan, Katrin Schultheiss, Florian Bruckner, Markus Weigand

The efficient excitation of spin waves is a key challenge in the realization of magnonic devices. We demonstrate the current-driven generation of spin waves in antiferromagnetically coupled magnetic vortices. We employ time-resolved scanning transmission X-ray microscopy (TR-STXM) to directly image the emission of spin waves upon the application of an altern

Arindam Majee, Rahul Saha, Snehasish Roy, Srilekha Mandal

The advancement in cyber-physical systems has opened a new way in disaster management and rescue operations. The usage of UAVs is very promising in this context. UAVs, mainly quadcopters, are small in size and their payload capacity is limited. A single UAV can not traverse the whole area. Hence multiple UAVs or swarms of UAVs come into the picture managing

Sosuke Ichihashi, So Kuroki, Mai Nishimura, Kazumi Kasaura

The human brain's plasticity allows for the integration of artificial body parts into the human body. Leveraging this, embodied systems realize intuitive interactions with the environment. We introduce a novel concept: embodied swarm robots. Swarm robots constitute a collective of robots working in harmony to achieve a common objective, in our case, serving

Shaolong Han, Yuanfeng Jin, Seok-Jin Kang, Duncan Laurie

In this paper we construct Young wall models for the level $1$ highest weight and Fock space crystals of quantum affine algebras in types $E_6^{(2)}$ and $F_4^{(1)}$. Our starting point in each case is a combinatorial realization for a certain level $1$ perfect crystal in terms of Young columns. Then using energy functions and affine energy functions we defi

Shivam Choubey, Birupaksha Pal, Manish Agrawal

Operator-based neural network architectures such as DeepONets have emerged as a promising tool for the surrogate modeling of physical systems. In general, towards operator surrogate modeling, the training data is generated by solving the PDEs using techniques such as Finite Element Method (FEM). The computationally intensive nature of data generation is one

Florian Aichinger, Sascha Desmettre

Geometric Asian options are a type of options where the payoff depends on the geometric mean of the underlying asset over a certain period of time. This paper is concerned with the pricing of such options for the class of Volterra-Heston models, covering the rough Heston model. We are able to derive semi-closed formulas for the prices of geometric Asian opti

Jianling Fu, Hui Jiang, Ming Xu, Yuxin Deng

We consider the two categories of termination problems of quantum programs with nondeterminism: 1) Is an input of a program terminating with probability one under all schedulers? If not, how can a scheduler be synthesized to evidence the nontermination? 2) Are all inputs terminating with probability one under their respective schedulers? If yes, a further qu

Aleksa Sukovic, Goran Radanovic

Equipping agents with the capacity to justify made decisions using supporting evidence represents a cornerstone of accountable decision-making. Furthermore, ensuring that justifications are in line with human expectations and societal norms is vital, especially in high-stakes situations such as healthcare. In this work, we propose the use of a debate-based r

Ricardo E. da Silva, Jonas H. Osório, Gabriel L. Rodrigues, David J. Webb

The modulation efficiency of a tubular-lattice hollow-core fiber (HCF) by means of flexural acoustic waves is investigated in detail for the first time. The main acousto-optic properties of the HCF are evaluated employing 2D and 3D models based on the finite element method. The induced coupling of the fundamental and first higher-order modes is simulated in

Haoran Geng, Yuezhi Che, Dazhao Chen, Michael Niemier

The rise of cloud computing demands secure memory systems that ensure data confidentiality, integrity, and freshness against replay attacks. Existing schemes such as AES-XTS, AES-GCM, and AES-CTR each trade performance for security, with only AES-CTR plus Message Authentication Codes (MAC) and Merkle Trees (MT) providing full protection - at the cost of subs

Hongyu Sun, Yongcai Wang, Wang Chen, Haoran Deng

This paper presents a parameter-efficient prompt tuning method, named PPT, to adapt a large multi-modal model for 3D point cloud understanding. Existing strategies are quite expensive in computation and storage, and depend on time-consuming prompt engineering. We address the problems from three aspects. Firstly, a PromptLearner module is devised to replace h

Ismail Sk, Joydeep Chatterjee, A. Taraphder, Nandan Pakhira

The recent observation of magnetization plateaus in rare-earth metallic tetraborides has drawn a lot of attention to this class of materials. In this work, we investigate the electronic structure of one such canonical system $\textrm{LuB}_{4}$, using first-principle density functional theory, together with strong Coulomb correlation and spin-orbit coupling (

Jianli Zhao, Changhao Xu, Bin Jiang

Relational triple extraction is a fundamental task in the field of information extraction, and a promising framework based on table filling has recently gained attention as a potential baseline for entity relation extraction. However, inherent shortcomings such as redundant information and incomplete triple recognition remain problematic. To address these ch

Oliver Sourbut, Lewis Hammond, Harriet Wood

Many settings of interest involving humans and machines -- from virtual personal assistants to autonomous vehicles -- can naturally be modelled as principals (humans) delegating to agents (machines), which then interact with each other on their principals' behalf. We refer to these multi-principal, multi-agent scenarios as delegation games. In such games, th

Hanxi Li, Guofeng Li, Bo Li, Lin Wu

Matting with a static background, often referred to as ``Background Matting" (BGM), has garnered significant attention within the computer vision community due to its pivotal role in various practical applications like webcasting and photo editing. Nevertheless, achieving highly accurate background matting remains a formidable challenge, primarily owing to t

Zijian Li, Ruichu Cai, Haiqin Huang, Sili Zhang

Existing model-based interactive recommendation systems are trained by querying a world model to capture the user preference, but learning the world model from historical logged data will easily suffer from bias issues such as popularity bias and sampling bias. This is why some debiased methods have been proposed recently. However, two essential drawbacks st

Tasnim Ahmed, Nicola Piovesan, Antonio De Domenico, Salimur Choudhury

Large Language Models (LLMs) have emerged as a significant advancement in the field of Natural Language Processing (NLP), demonstrating remarkable capabilities in language generation and other language-centric tasks. Despite their evaluation across a multitude of analytical and reasoning tasks in various scientific domains, a comprehensive exploration of the

Sana Hafeez, Mahmoud A. Shawky, Mohammad Al-Quraan, Lina Mohjazi

Unmanned aerial vehicles (UAV), an emerging architecture that embodies flying ad-hoc networks, face critical privacy and security challenges, mainly when engaged in data-sensitive missions. Therefore, message authentication is a crucial security feature in drone communications. This paper presents a Blockchain-based Efficient, and Trusted Authentication sche

Vladimir V. Basov

A first-order ordinary differential equation, solved with respect to derivative, is considered. It's right-hand side is defined and continuous on the set, consisting of a connected open subset of a two-dimensional Euclidean space and a part of its boundary. In the papers, dated by 2020, problems related to the existence or absence of the solution to the BIVP

Yilin Zheng, Zhigong Song

The reconstruction of 3D microstructures from 2D slices is considered to hold significant value in predicting the spatial structure and physical properties of materials.The dimensional extension from 2D to 3D is viewed as a highly challenging inverse problem from the current technological perspective.Recently,methods based on generative adversarial networks

Anej Svete, Robin Shing Moon Chan, Ryan Cotterell

Recent work by Hewitt et al. (2020) provides an interpretation of the empirical success of recurrent neural networks (RNNs) as language models (LMs). It shows that RNNs can efficiently represent bounded hierarchical structures that are prevalent in human language. This suggests that RNNs' success might be linked to their ability to model hierarchy. However,