March 2024 arXiv papers — page 5

Vivek Khetan

This position paper proposes a systematic approach towards developing a framework to help select the most effective embedding models for natural language processing (NLP) tasks, addressing the challenge posed by the proliferation of both proprietary and open-source encoder models.

Letian Peng, Zilong Wang, Feng Yao, Zihan Wang

Information extraction (IE) is a fundamental area in natural language processing where prompting large language models (LLMs), even with in-context examples, cannot defeat small LMs tuned on very small IE datasets. We observe that IE tasks, such as named entity recognition and relation extraction, all focus on extracting important information, which can be f

Gamaliel Cerda-Morales

In this paper, a new generalization of third-order Jacobsthal bihyperbolic polynomials is introduced. Some of the properties of presented polynomials are given. A Vadja formula for the generalized bihyperbolic third-order Jacobsthal polynomials is obtained. This result implies the Catalan, Cassini and d'Ocagne identities. Moreover, generating function and ma

Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li

We introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits. QuaRot rotates LLMs in a way that removes outliers from the hidden state without changing the output, making quantization easier. This computational invariance is applied to the hidden state

Angelo Bella, Santi Spadaro

We define a topological space to be an "SDL space" if the closure of each one of its strongly discrete subsets is Lindel\"of. After distinguishing this property from the Lindel\"of property we make various remarks about cardinal invariants of SDL spaces. For example we prove that $|X| \leq 2^{\chi(X)}$ for every SDL Urysohn space and that every SDL $P$-space

Theodoros Depastas, Shuting Sun, Hongbin Heb, Hua Zheng

Helium burning is one of the most fundamental steps of stellar nucleosynthesis, as it describes the formation of life-determining element of carbon, while it plays a key role in the evolution of Red Giant, accreting White Dwarfs and Neutron Stars. In this work we develop a generalized statistical theory for the 3{\alpha} reaction, which is based on the use o

I. I. Mokhov

The predictability of climate anomalies in the regions of Northern Eurasia in connection with El Nino phenomena is analyzed. Particular attention is paid to the most likely transition in 2024 from an El Nino phase at the beginning of the year to a La Nina phase at the end of the year, with the greatest probability of high temperatures and dry conditions in E

Alireza Khalili Golmankhaneh, Claude Depollier, Diana Pham

This paper provides a summary of the fractal calculus framework. It presents higher-order homogeneous and nonhomogeneous linear fractal differential equations with $\alpha$-order. Solutions for these equations with constant coefficients are obtained through the method of variation of parameters and the method of undetermined coefficients. The solution space

Yian Wang, Juntian Zheng, Zhehuan Chen, Zhou Xian

In this work, we aim to teach robots to manipulate various thin-shell materials. Prior works studying thin-shell object manipulation mostly rely on heuristic policies or learn policies from real-world video demonstrations, and only focus on limited material types and tasks (e.g., cloth unfolding). However, these approaches face significant challenges when ex

Tenghao Huang, Dongwon Jung, Muhao Chen

Recent advancements in integrating external tools with Large Language Models (LLMs) have opened new frontiers, with applications in mathematical reasoning, code generators, and smart assistants. However, existing methods, relying on simple one-time retrieval strategies, fall short on effectively and accurately shortlisting relevant tools. This paper introduc

Arkady A. Popov, Sergey G. Rubin, Alexander S. Sakharov

The origin and evolution of supermassive black holes (SMBHs) in our universe have sparked controversy. In this study, we explore the hypothesis that some of these black holes may have seeded from the direct collapse of dark energy domains with density significantly higher than the surrounding regions. The mechanism of the origin of such domains relies on the

M. Malekhosseini, S. Rostami, A. R. Olamaei, R. Ostovar

It is fascinating to predict the mass and width of the ordinary and exotic mesons solely based on their quark content and quantum numbers. Such prediction goes beyond conventional methodologies traditionally employed in hadron physics for calculating or estimating these quantities. The relation between the quantum numbers and the properties of the mesons, su

Alireza Barekatain, Hamed Rahimi Nohooji, Holger Voos

The aim of this study is to investigate an automated industrial manipulation pipeline, where assembly tasks can be flexibly adapted to production without the need for a robotic expert, both for the vision system and the robot program. The objective of this study is first, to develop a synthetic-dataset-generation pipeline with a special focus on industrial p

Ilaria Castellani, Paola Giannini

We address the question of characterising the well-formedness properties of multiparty session types semantically, i.e., as properties of the semantic model used to interpret types. Choosing Prime Event Structures (PESs) as our semantic model, we present semantic counterparts for the two properties that underpin global type well-formedness, namely projectabi

Alireza Khalili Golmankhaneh, Donatella Bongiorno

In this paper, a homogeneous system of n $\alpha$-order linear fractal differential equation is defined and the set of its fundamental solutions through the corresponding Wronskian matrix is described. Finally, the solutions of some assigned autonomous homogeneous system are plotted to show the details previously proved.

E. M. Tursunov, Sh. G. Norbutaev, B. A. Fayzullaev

A new theoretical method is developed to solve the two-body bound-state Dirac equation for positronium. Only Coulomb potential was included in the Dirac Hamiltonian. It is shown that the two-body Dirac Hamiltonian can be written in the Hermitian matrix form of the 4$\times$4 size and diagonalized in the momentum-state representation. Numerical results for th

Songqun Gao, Wendi Ding, Maotong Cheng, Qinyuan Ren

Mobile manipulators are known for their superior mobility over manipulators on fixed bases, offering promising applications in smart industry and housekeeping scenarios. The dynamic coupling nature between the mobile base and the manipulator presents challenges for force interactive tasks of the mobile manipulator. However, current strategies often fail to a

Catie Cuan, Kyle Jeffrey, Kim Kleiven, Adrian Li

For decades, robotics researchers have pursued various tasks for multi-robot systems, from cooperative manipulation to search and rescue. These tasks are multi-robot extensions of classical robotic tasks and often optimized on dimensions such as speed or efficiency. As robots transition from commercial and research settings into everyday environments, social

Mojtaba Bavandsavadkoohi, Erwan Gloaguen, Behzad Tokhmechi, Alireza Arab-Amiri

Over the last couple of decades, there has been a surge in various approaches to multiple-point statistics simulation, commonly referred to as MPS. These methods have aimed to improve several critical aspects of realism in the results, including spatial continuity, conditioning, stochasticity, and computational efficiency. Nevertheless, achieving a simultane

Daniele Amato, Paolo Facchi

We prove sharp universal upper bounds on the number of steady and asymptotic states of discrete- and continuous-time Markovian evolutions of open quantum systems. We show that the bounds depend only on the dimension of the system and not on the details of the dynamics. A comparison with similar bounds deriving from a recent spectral conjecture for Markovian

Alex Nguyen, Zilong Wang, Jingbo Shang, Dheeraj Mekala

The application of natural language processing models to PDF documents is pivotal for various business applications yet the challenge of training models for this purpose persists in businesses due to specific hurdles. These include the complexity of working with PDF formats that necessitate parsing text and layout information for curating training data and t

Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang

The Lion optimizer has been a promising competitor with the AdamW for training large AI models, with advantages on memory, computation, and sample efficiency. In this paper, we introduce Distributed Lion, an innovative adaptation of Lion for distributed training environments. Leveraging the sign operator in Lion, our Distributed Lion only requires communicat

Jaime González-González, Francisco de Arriba-Pérez, Silvia García-Méndez, Andrea Busto-Castiñeira

Automatic legal text classification systems have been proposed in the literature to address knowledge extraction from judgments and detect their aspects. However, most of these systems are black boxes even when their models are interpretable. This may raise concerns about their trustworthiness. Accordingly, this work contributes with a system combining Natur

Tumpa Mahato, Rama Mishra, Sahil Joshi

In this paper we study welded knots and their invariants. We focus on generating examples of non-trivial knotted ribbon tori as the tube of welded knots that are obtained from classical knot diagrams by welding some of the crossings. Non-triviality is shown by determining the fundamental group of the concerned welded knot. Sample examples under consideration

T. B. Lysetskyi, Ya. I. Yeleiko

We consider a multi-type Galton-Watson branching processes, where the largest in magnitude positive eigenvalue $\rho$ of the first moments matrix is close to unity. Specifically, we examine the random vector representing the number of individuals preceding the generation $n$, often referred to as the total progeny. By conditioning on non-extinction or extinc

Mauro Salazar, Sara Betancur Giraldo, Fabio Paparella, Leonardo Pedroso

Research on the operation of mobility systems so far has mostly focused on minimizing cost-centered metrics such as average travel time, distance driven, and operational costs. Whilst capturing economic indicators, such metrics do not account for transportation justice aspects. In this paper, we present an optimization model to plan the operation of Intermod

Ignacio Vergara

We show that Property $\mathrm{(TTT)}$ is an obstruction to weak amenability with Cowling--Haagerup constant $1$. More precisely, if $G$ is a countable group and $H$ is an infinite subgroup of $G$ such that the pair $(G,H)$ has relative Property $\mathrm{(TTT)}$, then the weak Haagerup constant $\boldsymbol\Lambda_{\mathrm{WH}}(G)$ is strictly greater than $

Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila, Francisco J. González-Castaño

Financial news items are unstructured sources of information that can be mined to extract knowledge for market screening applications. Manual extraction of relevant information from the continuous stream of finance-related news is cumbersome and beyond the skills of many investors, who, at most, can follow a few sources and authors. Accordingly, we focus on

Md Adnan Faisal Hossain, Zhihao Duan, Yuning Huang, Fengqing Zhu

Feature compression is a promising direction for coding for machines. Existing methods have made substantial progress, but they require designing and training separate neural network models to meet different specifications of compression rate, performance accuracy and computational complexity. In this paper, a flexible variable-rate feature compression metho

Tsung Heng Wu, Md Amiruzzaman, Ye Zhao, Deepshikha Bhati

Street-level visual appearances play an important role in studying social systems, such as understanding the built environment, driving routes, and associated social and economic factors. It has not been integrated into a typical geographical visualization interface (e.g., map services) for planning driving routes. In this paper, we study this new visualizat

Wenjuan Li, Dongyong Yang, Feng Zhang

In this paper, we establish the $L^{p}(\mathbb{R}^{d})$-boundedness of the variation operator and the $\delta$-jump operator for generalized spherical means, and we also show the necessary conditions for the $L^{p}(\mathbb{R}^{d})$-boundedness of these operators. These results are almost optimal when $d=2$.

Marcel Ausloos, Giulia Rotundo, Roy Cerqueti

In this paper, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow to rank "agents", "opinions", ..., all defined in a very broad sense. We aim toward any process which should a priori demand or lead to some consensus in order to attain the pres

Shengze Jin, Iro Armeni, Marc Pollefeys, Daniel Barath

We introduce a novel framework for multiway point cloud mosaicking (named Wednesday), designed to co-align sets of partially overlapping point clouds -- typically obtained from 3D scanners or moving RGB-D cameras -- into a unified coordinate system. At the core of our approach is ODIN, a learned pairwise registration algorithm that iteratively identifies ove

Alireza Khalili Golmankhaneh, Donatella Bongiorno

In this research paper, we provide a concise overview of fractal calculus applied to fractal sets. We introduce and solve a second $\alpha$-order fractal differential equation with constant coefficients across different scenarios. We propose a uniqueness theorem for second $\alpha$-order fractal linear differential equations. We define the solution space as

Patrick Guidotti

A kernel based method is proposed for the construction of signature (defining) functions of subsets of $\mathbb{R}^d$. The subsets can range from full dimensional manifolds (open subsets) to point clouds (a finite number of points) and include bounded (closed) smooth manifolds of any codimension. The interpolation and analysis of point clouds are the main ap

Francisco Javier González-Castaño, Felipe Gil-Castiñeira, David Rodríguez-Pereira, José Ángel Regueiro-Janeiro

Drones may be more advantageous than fixed cameras for quality control applications in industrial facilities, since they can be redeployed dynamically and adjusted to production planning. The practical scenario that has motivated this paper, image acquisition with drones in a car manufacturing plant, requires drone positioning accuracy in the order of 5 cm.

Taesoo Song, Ilia Grishmanovskii, Olga Soloveva, Elena Bratkovskaya

We investigate the thermal production of charm quarks in the strongly interacting quark-gluon plasma (sQGP) created in heavy-ion collisions at relativistic energies. Our study is based on the off-shell parton-hadron-string dynamics (PHSD) transport approach describing the full time evolution of heavy-ion collisions on a microscopic basis with hadronic and pa

Zhaofeng Zhang, Banghao Chen, Shengxin Zhu, Nicolas Langrené

In traditional quantitative trading practice, navigating the complicated and dynamic financial market presents a persistent challenge. Fully capturing various market variables, including long-term information, as well as essential signals that may lead to profit remains a difficult task for learning algorithms. In order to tackle this challenge, this paper i

N. O. Okeke, M. E. Egwe

The $L^p$-spaces, with $p \not = \infty$, form a partial algebra $(L^p(\Omega), \Gamma, \cdot)$ with pointwise multiplication of functions. The Sobolev spaces $W^{k,p}(\Omega)$, delineated by weak derivatives as subspaces of $L^p$-spaces is shown to contain the partial algebra $(L^p(\Omega), \Gamma, \cdot)$ generalized by the partial action of the smooth alg

Efstratios Chatzoglou, Vyron Kampourakis, Zisis Tsiatsikas, Georgios Karopoulos

Password management has long been a persistently challenging task. This led to the introduction of password management software, which has been around for at least 25 years in various forms, including desktop and browser-based applications. This work assesses the ability of two dozen password managers, 12 desktop applications, and 12 browser-plugins, to effe

Jean-Charles Delvenne, Léopold Van Brandt

We characterize the possible moments of entropy production for general overdamped Markovian systems. We find a general formulation of the problem, and derive a new necessary condition between the second and third moment. We determine all possible first, second and third moments of entropy production for a white noise process. As a consequence, we obtain a lo

Francesco Bascone, Franco Pezzella, Patrizia Vitale

Jacobi sigma models are two-dimensional topological non-linear field theories which are associated with Jacobi structures. The latter can be considered as a generalization of Poisson structures. After reviewing the main properties and peculiarities of these models, we focus on the twisted version in which a Wess-Zumino term is included. This modification all

Xihao Xie, Jia Zhang, Rahul Ramachandran, Tsengdar J. Lee

Increasingly, more software services have been published onto the Internet, making it a big challenge to recommend services in the process of a scientific workflow composition. In this paper, a novel context-aware approach is proposed to recommending next services in a workflow development process, through learning service representation and service selectio

Sonal Kumar, Sreyan Ghosh, S Sakshi, Utkarsh Tyagi

Open-vocabulary vision-language models (VLMs) like CLIP, trained using contrastive loss, have emerged as a promising new paradigm for text-to-image retrieval. However, do VLMs understand compound nouns (CNs) (e.g., lab coat) as well as they understand nouns (e.g., lab)? We curate Compun, a novel benchmark with 400 unique and commonly used CNs, to evaluate th

Elvin Hajizada, Balachandran Swaminathan, Yulia Sandamirskaya

Humans and animals learn throughout their lives from limited amounts of sensed data, both with and without supervision. Autonomous, intelligent robots of the future are often expected to do the same. The existing continual learning (CL) methods are usually not directly applicable to robotic settings: they typically require buffering and a balanced replay of

HongWei Yan, Liyuan Wang, Kaisheng Ma, Yi Zhong

To accommodate real-world dynamics, artificial intelligence systems need to cope with sequentially arriving content in an online manner. Beyond regular Continual Learning (CL) attempting to address catastrophic forgetting with offline training of each task, Online Continual Learning (OCL) is a more challenging yet realistic setting that performs CL in a one-

Jan Derbisz, Tomasz Krawczyk

In this paper we investigate some problems related to the Helly properties of circular-arc graphs, which are defined as intersection graphs of arcs of a fixed circle. As such, circular-arc graphs are among the simplest classes of intersection graphs whose models might not satisfy the Helly property. In particular, some cliques of a circular-arc graph might b

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

We present CoDa (Constrained Generation based Data Augmentation), a controllable, effective, and training-free data augmentation technique for low-resource (data-scarce) NLP. Our approach is based on prompting off-the-shelf instruction-following Large Language Models (LLMs) for generating text that satisfies a set of constraints. Precisely, we extract a set

Ishmael N. Amartey

Approximation theorem is one of the most important aspects of numerical analysis that has evolved over the years with many different approaches. Some of the most popular approximation methods include the Lebesgue approximation theorem, the Weierstrass approximation, and the Fourier approximation theorem. The limitations associated with various approximation

Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila, Francisco J. González-Castaño

Microblogging platforms, of which Twitter is a representative example, are valuable information sources for market screening and financial models. In them, users voluntarily provide relevant information, including educated knowledge on investments, reacting to the state of the stock markets in real-time and, often, influencing this state. We are interested i

Victor Rodriguez-Fernandez, Alejandro Carrasco, Jason Cheng, Eli Scharf

Recent trends are emerging in the use of Large Language Models (LLMs) as autonomous agents that take actions based on the content of the user text prompts. We intend to apply these concepts to the field of Guidance, Navigation, and Control in space, enabling LLMs to have a significant role in the decision-making process for autonomous satellite operations. A

Ayan Banerjee, Nityanand Mathur, Josep Llados, Umapada Pal

Generating VectorArt from text prompts is a challenging vision task, requiring diverse yet realistic depictions of the seen as well as unseen entities. However, existing research has been mostly limited to the generation of single objects, rather than comprehensive scenes comprising multiple elements. In response, this work introduces SVGCraft, a novel end-t

Anna Vaughan, Stratis Markou, Will Tebbutt, James Requeima

Weather forecasting is critical for a range of human activities including transportation, agriculture, industry, as well as the safety of the general public. Machine learning models have the potential to transform the complex weather prediction pipeline, but current approaches still rely on numerical weather prediction (NWP) systems, limiting forecast speed

Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila, Francisco J. González-Castaño

Finance-related news such as Bloomberg News, CNN Business and Forbes are valuable sources of real data for market screening systems. In news, an expert shares opinions beyond plain technical analyses that include context such as political, sociological and cultural factors. In the same text, the expert often discusses the performance of different assets. Som

Artem Kravchuk

A Transposition graph $T_n$ is defined as a Cayley graph over the symmetric group $Sym_n$ generated by all transpositions. It is known that the spectrum of $T_n$ consists of integers, but it is not known exactly how these numbers are distributed. In this paper we prove that integers from the segment $[-n, n]$ lie in the spectrum of $T_n$ for any $n\geqslant

Xiaoyang Lyu, Yang-Tian Sun, Yi-Hua Huang, Xiuzhe Wu

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering quality of 3DGS. The key insight is incorporating an implicit signed distance field (SDF) within 3D Gaussians to enable them t

Geoffrey S. H. Cruttwell, Bruno Gavranovic, Neil Ghani, Paul Wilson

We propose a categorical semantics for machine learning algorithms in terms of lenses, parametric maps, and reverse derivative categories. This foundation provides a powerful explanatory and unifying framework: it encompasses a variety of gradient descent algorithms such as ADAM, AdaGrad, and Nesterov momentum, as well as a variety of loss functions such as

Adnan Malik, Yonghui Xia, Ayesha Almas, M. Farasat Shamir

In this manuscript, we investigate the behavior of stellar structure through embedding approach in $f(R, \phi, X)$ modified theory of gravity, where $R$ denotes the Ricci scalar, $\phi$ represents the scalar potential and $X$ indicates the kinetic potential. For this purpose, we consider the spherically symmetric space-time with anisotropic fluid. We further

Marc Feger, Stefan Dietze

Twitter has emerged as a global hub for engaging in online conversations and as a research corpus for various disciplines that have recognized the significance of its user-generated content. Argument mining is an important analytical task for processing and understanding online discourse. Specifically, it aims to identify the structural elements of arguments

Jie Gao, Simret Araya Gebreegziabher, Kenny Tsu Wei Choo, Toby Jia-Jun Li

With ChatGPT's release, conversational prompting has become the most popular form of human-LLM interaction. However, its effectiveness is limited for more complex tasks involving reasoning, creativity, and iteration. Through a systematic analysis of HCI papers published since 2021, we identified four key phases in the human-LLM interaction flow - planning, f

Xiangjun Peng

A new analytic framework is first formalized via the usage of the Monadology (Leibniz 1898), to expand the understanding of Zermelo-Fraenkel-choice set theory (ZFC) and Von Neumann-Bernays-Godel set theory (NBG). Implicitly, the framework levels value, representation and information separately. Given the fact that there exists a coincidental equivalence betw

Ege Aktemur, Ege Zorlutuna, Kaan Bilgili, Tacettin Emre Bok

We introduce a new approach in distributed deep learning, utilizing Geoffrey Hinton's Forward-Forward (FF) algorithm to speed up the training of neural networks in distributed computing environments. Unlike traditional methods that rely on forward and backward passes, the FF algorithm employs a dual forward pass strategy, significantly diverging from the con

Guimin Hu, Zhihong Zhu, Daniel Hershcovich, Lijie Hu

Multimodal emotion recognition in conversation (MERC) and multimodal emotion-cause pair extraction (MECPE) have recently garnered significant attention. Emotions are the expression of affect or feelings; responses to specific events, or situations -- known as emotion causes. Both collectively explain the causality between human emotion and intents. However,

Johannes Stowasser, Felix Hitzelhammer, Michael A. Schreiber, Ulrich Hohenester

Focusing on two-level atoms, we apply the positive $P$ representation to a full-wave mixed bosonic and fermionic system of Jaynes-Cummings type and identify an advantageous degree of freedom in the choice of the involved nonorthogonal fermionic basis states. On this basis, we propose a stochastic correction to the Maxwell-Bloch equations by relating them to

Akash Ghosh, B Venkata Sahith, Niloy Ganguly, Pawan Goyal

Question-answering (QA) on hybrid scientific tabular and textual data deals with scientific information, and relies on complex numerical reasoning. In recent years, while tabular QA has seen rapid progress, understanding their robustness on scientific information is lacking due to absence of any benchmark dataset. To investigate the robustness of the existin

Thomas Hillen, Maria R. D'Orsogna, Jacob C. Mantooth, Alan E. Lindsay

Many transport processes in ecology, physics and biochemistry can be described by the average time to first find a site or exit a region, starting from an initial position. Typical mathematical treatments are based on formulations that allow for various diffusive forms and geometries but where only initial and final positions are taken into account. Here, we

Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai

Pretrained language models are an integral part of AI applications, but their high computational cost for training limits accessibility. Initiatives such as Bloom and StarCoder aim to democratize access to pretrained models for collaborative community development. Despite these efforts, such models encounter challenges such as limited multilingual capabiliti

Marco Tschimpke, Manuela Schreyer, Wolfgang Trutschnig

Kokol and Stopar ($2023$) recently studied the exact region $\Omega_{\phi,\rho}$ determined by Spearman's footrule $\phi$ and Spearman's $\rho$ and derived a sharp lower, as well as a non-sharp upper bound for $\rho$ given $\phi$. Considering that the proofs for establishing these inequalities are novel and interesting, but technically quite involved we here

Marco Cognetta, Tatsuya Hiraoka, Naoaki Okazaki, Rico Sennrich

We explore threshold vocabulary trimming in Byte-Pair Encoding subword tokenization, a postprocessing step that replaces rare subwords with their component subwords. The technique is available in popular tokenization libraries but has not been subjected to rigorous scientific scrutiny. While the removal of rare subwords is suggested as best practice in machi

Yitong Wang

Let $p$ be a prime number, $K$ a finite unramified extension of $\mathbb{Q}_p$ and $\mathbb{F}$ a finite extension of $\mathbb{F}_p$. For $\overline{\rho}$ any reducible two-dimensional representation of $\operatorname{Gal}(\overline{K}/K)$ over $\mathbb{F}$, we compute explicitly the associated \'etale $(\varphi,\mathcal{O}_K^{\times})$-module $D_A^{\otimes

Manuele Veggi

This dissertation presents the first version of a project at the Fondazione Federico Zeri, aimed at modelling the art market starting from the recognition of the peculiarities of this sector and relying on the data collected by this institute during its research activities on its documentary collection. Specifically, this study describes the development of a

Rahul K. Gupta, Daniel K. Molzahn

Active power curtailment of photovoltaic (PV) generation is commonly exercised to mitigate over-voltage issues in power distribution networks. However, fairness concerns arise as certain PV plants may experience more significant curtailments than others depending on their locations within the network. Existing literature tackles this issue through fairness-p

Cyrille Armel Sayou Ngomsi, Tamanna Joshi, Pratibha Dev

Spin-active defects in silicon carbide (SiC) are promising quantum light sources for realizing scalable quantum technologies. In different applications, these photoluminescent defects are often placed in a nanostructured host or close to surfaces in order to enhance the signal from the defects. However, proximity to the surface not only modifies frequencies

Tahiya Chowdhury, Ilan Mandel, Jorge Ortiz, Wendy Ju

Street view imagery (SVI), largely captured via outfitted fleets or mounted dashcams in consumer vehicles is a rapidly growing source of geospatial data used in urban sensing and development. These datasets are often collected opportunistically, are massive in size, and vary in quality which limits the scope and extent of their use in urban planning. Thus fa

R. K. H. Smeets, K. Mitra, I. S. Pop, S. Sonner

We propose and analyse numerical schemes for a system of quasilinear, degenerate evolution equations modelling biofilm growth as well as other processes such as flow through porous media and the spreading of wildfires. The first equation in the system is parabolic and exhibits degenerate and singular diffusion, while the second is either uniformly parabolic

Younes Belkouchi, Jean-Christophe Pesquet, Audrey Repetti, Hugues Talbot

This article introduces a novel approach to learning monotone neural networks through a newly defined penalization loss. The proposed method is particularly effective in solving classes of variational problems, specifically monotone inclusion problems, commonly encountered in image processing tasks. The Forward-Backward-Forward (FBF) algorithm is employed to

Yitong Wang

Let $p$ be a prime number, $K$ a finite unramified extension of $\mathbb{Q}_p$ and $\mathbb{F}$ a finite extension of $\mathbb{F}_p$. For $\pi$ an admissible smooth representation of $\operatorname{GL}_2(K)$ over $\mathbb{F}$ satisfying certain multiplicity-one properties, we compute the rank of the associated \'etale $(\varphi,\mathcal{O}_K^{\times})$-modul

G. S. Denisov, R. E. Asfin

This article continues the series of works by the authors on the approximation of the electronic terms of diatomic molecules by the Morse formula, which is the simplest anharmonic approximation of the real term U(r). Depending on the choice of parameters, the approximation has two alternative solutions M1(r) and M2(r), with different patterns of deviations f

Lucas M. Dutton, Christopher Kumar Anand, Robert Enenkel, Silvia Melitta Müller

Floating-point arithmetic performance determines the overall performance of important applications, from graphics to AI. Meeting the IEEE-754 specification for floating-point requires that final results of addition, subtraction, multiplication, division, and square root are correctly rounded based on the user-selected rounding mode. A frustrating fact for im

Parag Pravin Dakle, Alolika Gon, Sihan Zha, Liang Wang

In this paper, we describe the different approaches explored by the Jetsons team for the Multi-Lingual ESG Impact Duration Inference (ML-ESG-3) shared task. The shared task focuses on predicting the duration and type of the ESG impact of a news article. The shared task dataset consists of 2,059 news titles and articles in English, French, Korean, and Japanes

Mohammed Haroon Dupty, Yanfei Dong, Sicong Leng, Guoji Fu

This paper addresses the challenge of object-centric layout generation under spatial constraints, seen in multiple domains including floorplan design process. The design process typically involves specifying a set of spatial constraints that include object attributes like size and inter-object relations such as relative positioning. Existing works, which typ

Sanghyun Jo, Soohyun Ryu, Sungyub Kim, Eunho Yang

We identify a critical bias in contemporary CLIP-based models, which we denote as single tag bias. This bias manifests as a disproportionate focus on a singular tag (word) while neglecting other pertinent tags, stemming from CLIP's text embeddings that prioritize one specific tag in image-text relationships. When deconstructing text into individual tags, onl

Anil Bayram Gogebakan, Enrico Magliano, Alessio Carpegna, Annachiara Ruospo

As artificial neural networks become increasingly integrated into safety-critical systems such as autonomous vehicles, devices for medical diagnosis, and industrial automation, ensuring their reliability in the face of random hardware faults becomes paramount. This paper introduces SpikingJET, a novel fault injector designed specifically for fully connected

Yuyang Chen, Peng Luo

In this paper, we study non-homogeneous stochastic linear-quadratic (LQ) optimal control problems with multi-dimensional state and regime switching. We focus on the corresponding stochastic Riccati equation, which is the same as that one in homogeneous stochastic LQ optimal control problem, and the adjoint backward stochastic differential equation (BSDE), wh

Svyatoslav Dedikov, Evgenii Vasiliev

The destruction of clouds by strong shocks and hot winds is the key process responsible for the transp orting of metals and dust from the ISM to the ICM/IGM, and establishing the multiphase structure in and around galaxies. In this work, we perform a detailed analysis of this process using two different approaches for tracking the cloud material (gas and dus

Ziyi Zhou, Xiaoming Zhang, Litian Zhang, Jiacheng Liu

Existing benchmarks for fake news detection have significantly contributed to the advancement of models in assessing the authenticity of news content. However, these benchmarks typically focus solely on news pertaining to a single semantic topic or originating from a single platform, thereby failing to capture the diversity of multi-domain news in real scena

Sanghyun Jo, Fei Pan, In-Jae Yu, Kyungsu Kim

Weakly-supervised semantic segmentation (WSS) ensures high-quality segmentation with limited data and excels when employed as input seed masks for large-scale vision models such as Segment Anything. However, WSS faces challenges related to minor classes since those are overlooked in images with adjacent multiple classes, a limitation originating from the ove

Antonio Cesar do Prado Rosa Junior, Elias Brito Alves Junior, Wanisson Silva Santana, Clebson Cruz

We present a review of the Non-additive Stochastic Model for supercooled liquids (NSM), an efficient approach for diffusive processes that provides a suitable interpretation for the non-Arrhenius dynamics in these materials. Based on a class of non-homogeneous continuity equations, the NSM provides functions able to model the thermal behavior of the viscosit

Evgemii O. Vasiliev, Yuri A. Shchekinov

For understanding the nature of gaseous flows in star-forming regions of nearby galaxies it is usually utilized the relation between surface brightness in H$\alpha$ line and velocity dispersion of ionized gas known as ''surface brightness -- velocity dispersion diagram''. Using the three-dimensional gasdynamic simulations we consider the evolution of the syn

Zetao Xie, Zeling Chen, Hao Li, Qinghui Yan

The emerging field of free-electron quantum optics enables electron-photon entanglement and holds the potential for generating nontrivial photon states for quantum information processing. Although recent experimental studies have entered the quantum regime, rapid theoretical developments predict that qualitatively unique phenomena only emerge beyond a certai

Hyunjae Kim, Hyeon Hwang, Jiwoo Lee, Sihyeon Park

While recent advancements in commercial large language models (LM) have shown promising results in medical tasks, their closed-source nature poses significant privacy and security concerns, hindering their widespread use in the medical field. Despite efforts to create open-source models, their limited parameters often result in insufficient multi-step reason

Weiwei Chen, Yedi Shen, Tianle Zhan, W. Zhu

We explore the dynamic shear viscosity of the undoped ABC-stacked multilayer graphene based on the chiral-$N$ effective Hamiltonian, where the chirality $N$ is equivalent to the layer number. We investigate the dependence of the dynamic shear viscosity on the frequency in the collisionless regime and calculate Coulomb interaction corrections by three leading

Suvrat Raju

An examination of the constraints of quantum gravity leads to a clear physical picture for how information about the initial state is transferred to the Hawking radiation that emerges from a black hole.

Pengzhi Li, Yikang Ding, Haohan Wang, Chengshuai Tang

This paper presents a novel monocular depth estimation method, named ECFNet, for estimating high-quality monocular depth with clear edges and valid overall structure from a single RGB image. We make a thorough inquiry about the key factor that affects the edge depth estimation of the MDE networks, and come to a ratiocination that the edge information itself

Fayssal Saadi

We describe the dynamics of a group $\Gamma$ generated by Dehn twists along two filling multi-curves or a family of filling curves on the SU(2)-representation variety of closed surfaces. Consequently, we provide explicit $\Gamma$-invariant rational functions on the representation variety of the genus two closed surface $S_2$ for some pair of multi-curves. We

Jingwen Tong, Zhenzhen Chen, Liqun Fu, Jun Zhang

Federated learning (FL) is an appealing paradigm for learning a global model among distributed clients while preserving data privacy. Driven by the demand for high-quality user experiences, evaluating the well-trained global model after the FL process is crucial. In this paper, we propose a closed-loop model analytics framework that allows for effective eval

Mohamed Camil Belhadjoudja, Miroslav Krstic, Mohamed Maghenem, Emmanuel Witrant

We consider the problem of inverse optimal control design for systems that are not affine in the control. In particular, we consider some classes of partial differential equations (PDEs) with quadratic convection and counter-convection, for which the L2 norm is a control Lyapunov function (CLF) whose derivative has either a depressed cubic or a quadratic dep

Ahmed R. Sadik, Bodo Urban, Omar Adel

Worker-Robot Cooperation is a new industrial trend, which aims to sum the advantages of both the human and the industrial robot to afford a new intelligent manufacturing techniques. The cooperative manufacturing between the worker and the robot contains other elements such as the product parts and the manufacturing tools. All these production elements must c

Yifei Liu, Qiong Cao, Yandong Wen, Huaiguang Jiang

This paper addresses the problem of generating lifelike holistic co-speech motions for 3D avatars, focusing on two key aspects: variability and coordination. Variability allows the avatar to exhibit a wide range of motions even with similar speech content, while coordination ensures a harmonious alignment among facial expressions, hand gestures, and body pos

Bin Wang, Yan Zhang, Yan Ma, Yaohui Jin

The next Point of Interest (POI) recommendation aims to recommend the next POI for users at a specific time. As users' check-in records can be viewed as a long sequence, methods based on Recurrent Neural Networks (RNNs) have recently shown good applicability to this task. However, existing methods often struggle to fully explore the spatio-temporal correlati