July 2023 arXiv papers — page 119

Feiyi Chen, Naijin Liu, Zhen Qin, Hailiang Zhao

Cloud providers can greatly benefit from accurate workload prediction. However, the workload of cloud servers is highly variable, with occasional workload bursts, which makes workload prediction challenging. The time series forecasting methods relying on periodicity information, often assume fixed and known periodicity length, which does not align with the p

Chuanbo Tang, Xihua Sheng, Zhuoyuan Li, Haotian Zhang

Video compression relies heavily on exploiting the temporal redundancy between video frames, which is usually achieved by estimating and using the motion information. The motion information is represented as optical flows in most of the existing deep video compression networks. Indeed, these networks often adopt pre-trained optical flow estimation networks f

Yue Tian, Guanjun Liu, Jiacun Wang, Mengchu Zhou

Many machine learning methods have been proposed to achieve accurate transaction fraud detection, which is essential to the financial security of individuals and banks. However, most existing methods leverage original features only or require manual feature engineering. They lack the ability to learn discriminative representations from transaction data. More

M. S. Tacca, M. B. Plenio

We present a group theoretical and ab-initio analysis of lattice point defects in fluorographene, with a focus on neutral and negative $\text{V}_{\text{CF}}$ vacancies. By using a combination of density functional theory calculations and group theory analysis, we investigate the many-body configurations of the defects and calculate the vertical absorption an

Jie Lu, Guo-Liang Yu, Zhi-Gang Wang, Bin Wu

In this article, the strong coupling constants of vertices $BB\Upsilon$, $BB^{*}\Upsilon$, $B^{*}B^{*}\Upsilon$, $BB^{*}\eta_{b}$ and $B^{*}B^{*}\eta_{b}$ are analyzed in the framework of QCD sum rules. In this work, all possible off-shell cases and the contributions of vacuum condensate terms including $\langle\overline{q}q\rangle$, $\langle\overline{q}g_{s

Francesco C. De Vecchi, Paola Morando, Stefania Ugolini

A strong quasi-invariance principle and a finite-dimensional integration by parts formula as in the Bismut approach to Malliavin calculus are obtained through a suitable application of Lie's symmetry theory to autonomous stochastic differential equations. The main stochastic, geometrical and analytical aspects of the theory are discussed and applications to

Luciano Mari, Jose Danuso Rocha de Oliveira, Andreas Savas-Halilaj, Renivaldo Sodre de Sena

In this paper we study conformal solitons for the mean curvature flow in hyperbolic space $\mathbb{H}^{n+1}$. Working in the upper half-space model, we focus on horo-expanders, which relate to the conformal field $-\partial_0$. We classify cylindrical and rotationally symmetric examples, finding appropriate analogues of grim-reaper cylinders, bowl and wingli

Zhengxin Lei, Feng Xu, Jiangtao Wei, Feng Cai

SAR images are highly sensitive to observation configurations, and they exhibit significant variations across different viewing angles, making it challenging to represent and learn their anisotropic features. As a result, deep learning methods often generalize poorly across different view angles. Inspired by the concept of neural radiance fields (NeRF), this

Constança Providência, Tuhin Malik, Milena Bastos Albino, Márcio Ferreira

The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a relativistic mean field description of nuclear matter. Different formulations, both with density dependent couplings and with non-linear mesonic terms, are considered and their predictions compared and discussed. A special atte

Hai D. Huynh, S. Natarajan, H. Nguyen-Xuan, Xiaoying Zhuang

The paper presents an assumed strain formulation over polygonal meshes to accurately evaluate the strain fields in nonlocal damage models. An assume strained technique based on the Hu-Washizu variational principle is employed to generate a new strain approximation instead of direct derivation from the basis functions and the displacement fields. The underlyi

M. Chak, T. Lelièvre, G. Stoltz, U. Vaes

Calculating averages with respect to multimodal probability distributions is often necessary in applications. Markov chain Monte Carlo (MCMC) methods to this end, which are based on time averages along a realization of a Markov process ergodic with respect to the target probability distribution, are usually plagued by a large variance due to the metastabilit

W. H. Lin, J. Garcia, J. Q. Li, S. Mazzi

The formation of Internal Transport Barrier (ITB) is studied in HL-2A plasmas by means of nonlinear gyrokinetic simulations. A new paradigm for the ITB formation is proposed in which different physics mechanisms play a different role depending on the ITB formation stage. In the early stage, fast ions, introduced by Neutral Beam Injection (NBI) ion system, ar

Lei Qiao, Jan Sladek, Vladimir Sladek, Alexey S. Kaminskiy

The bilayer of CrI3 is a prototypical van der Waals 2D antiferromagnetic material with magnetoelectric effect. It is not generally known, however, that for symmetry reasons the flexomagnetic effect, i.e., the strain gradient-induced magnetization, is also possible in this material. In the present paper, based on the first principle calculations, we estimate

Pramit Bhattacharyya, Joydeep Mondal, Subhadip Maji, Arnab Bhattacharya

Bangla (or Bengali) is the fifth most spoken language globally; yet, the state-of-the-art NLP in Bangla is lagging for even simple tasks such as lemmatization, POS tagging, etc. This is partly due to lack of a varied quality corpus. To alleviate this need, we build Vacaspati, a diverse corpus of Bangla literature. The literary works are collected from variou

Oleksandr Palagin, Vladislav Kaverinskiy, Anna Litvin, Kyrylo Malakhov

This research presents a comprehensive methodology for utilizing an ontology-driven structured prompts system in interplay with ChatGPT, a widely used large language model (LLM). The study develops formal models, both information and functional, and establishes the methodological foundations for integrating ontology-driven prompts with ChatGPT's meta-learnin

Huihui Xu, Kevin Ashley

We use the combination of argumentative zoning [1] and a legal argumentative scheme to create legal argumentative segments. Based on the argumentative segmentation, we propose a novel task of classifying argumentative segments of legal case decisions. GPT-3.5 is used to generate summaries based on argumentative segments. In terms of automatic evaluation metr

Vedang Lad, Jonas Mueller

The labor-intensive annotation process of semantic segmentation datasets is often prone to errors, since humans struggle to label every pixel correctly. We study algorithms to automatically detect such annotation errors, in particular methods to score label quality, such that the images with the lowest scores are least likely to be correctly labeled. This he

J. Gibelin, D. Beaumel, T. Motobayashi, Y. Blumenfeld

Coulomb excitation of the exotic neutron-rich nucleus Ne26 on a Pb208 target was measured at 58 MeV/u in order to search for low-lying E1 strength above the neutron emission threshold. This radioactive beam experiment was carried out at the RIKEN Accelerator Research Facility. Using the invariant mass method in the Ne25+n channel, we observe a sizable amount

Ronen Gradwohl, Moshe Tennenholtz

We study the costs and benefits of selling data to a competitor. Although selling all consumers' data may decrease total firm profits, there exist other selling mechanisms -- in which only some consumers' data is sold -- that render both firms better off. We identify the profit-maximizing mechanism, and show that the benefit to firms comes at a cost to consu

Yoshihiro Fujiwara, Motoya Shinozaki, Kazuma Matsumura, Kosuke Noro

Semiconductor quantum dots are useful for controlling and observing quantum states and can also be used as sensors for reading out quantum bits and exploring local electronic states in nanostructures. However, challenges remain for the sensor applications, such as the trade-off between sensitivity and dynamic range and the issue of instability due to externa

David Hyland, Julian Gutierrez, Michael Wooldridge

We consider the problem of incentivising desirable behaviours in multi-agent systems by way of taxation schemes. Our study employs the concurrent games model: in this model, each agent is primarily motivated to seek the satisfaction of a goal, expressed as a Linear Temporal Logic (LTL) formula; secondarily, agents seek to minimise costs, where costs are impo

Yongheng Zhang, Danfeng Yan, Yuanqiang Cai

Removing multiple degradations, such as haze, rain, and blur, from real-world images poses a challenging and illposed problem. Recently, unified models that can handle different degradations have been proposed and yield promising results. However, these approaches focus on synthetic images and experience a significant performance drop when applied to realwor

Chunxi Guo, Zhiliang Tian, Jintao Tang, Shasha Li

Text-to-SQL aims at generating SQL queries for the given natural language questions and thus helping users to query databases. Prompt learning with large language models (LLMs) has emerged as a recent approach, which designs prompts to lead LLMs to understand the input question and generate the corresponding SQL. However, it faces challenges with strict SQL

Yuanzhe Yang

In epistemic logic, a way to deal with knowledge-wh is to interpret them as a kind of mention-some knowledge (MS-knowledge). But philosophers and linguists have challenged both the sufficiency and necessity of such an account: some argue that knowledge-wh has, in addition to MS-knowledge, also a sensitivity to false belief (FS); others argue that knowledge-w

Minkyung Wang, Chisu Kim

Binarizing belief aggregation addresses how to rationally aggregate individual probabilistic beliefs into collective binary beliefs. Similar to the development of judgment aggregation theory, formulating axiomatic requirements, proving impossibility theorems, and identifying exact agenda conditions of impossibility theorems are natural and important research

Bernard Sinclair-Desgagné

Unknown unknowns are future relevant contingencies that lack an ex ante description. While there are numerous retrospective accounts showing that significant gains or losses might have been achieved or avoided had such contingencies been previously uncovered, getting hold of unknown unknowns still remains elusive, both in practice and conceptually. Using For

Aldo Ivńn Ramírez Abarca

This paper presents a logic-based framework to analyze responsibility, which I refer to as intentional epistemic act-utilitarian stit theory (IEAUST). To be precise, IEAUST is used to model and syntactically characterize various modes of responsibility, where by 'modes of responsibility' I mean instances of Broersen's three categories of responsibility (caus

Panagiotis Papadamos, Nina Gierasimczuk

In this paper we formalise three types of cognitive bias within the framework of belief revision: confirmation bias, framing bias, and anchoring bias. We interpret them generally, as restrictions on the process of iterated revision, and we apply them to three well-known belief revision methods: conditioning, lexicographic revision, and minimal revision. We i

Caspar Oesterheld, Abram Demski, Vincent Conitzer

The dominant theories of rational choice assume logical omniscience. That is, they assume that when facing a decision problem, an agent can perform all relevant computations and determine the truth value of all relevant logical/mathematical claims. This assumption is unrealistic when, for example, we offer bets on remote digits of pi or when an agent faces a

Daniel Miedema, Malvin Gattinger

Binary decision diagrams (BDDs) are widely used to mitigate the state-explosion problem in model checking. A variation of BDDs are Zero-suppressed Decision Diagrams (ZDDs) which omit variables that must be false, instead of omitting variables that do not matter. We use ZDDs to symbolically encode Kripke models used in Dynamic Epistemic Logic, a framework to

Yanjun Li

The logic of goal-directed knowing-how extends the standard epistemic logic with an operator of knowing-how. The knowing-how operator is interpreted as that there exists a strategy such that the agent knows that the strategy can make sure that p. This paper presents a tableau procedure for the multi-agent version of the logic of strategically knowing-how and

Saira Khan

The prescriptions of our two most prominent strands of decision theory, evidential and causal, differ in a general class of problems known as Newcomb problems. In these, evidential decision theory prescribes choosing a dominated act. Attempts have been made at reconciling the two theories by relying on additional requirements such as ratification (Jeffrey 19

Peter Hawke

We observe some puzzling linguistic data concerning ordinary knowledge ascriptions that embed an epistemic (im)possibility claim. We conclude that it is untenable to jointly endorse both classical logic and a pair of intuitively attractive theses: the thesis that knowledge ascriptions are always veridical and a `negative transparency' thesis that reduces kno

Jeremy Goodman, Bernhard Salow

In previous work ("Knowledge from Probability", TARK 2021) we develop a question-relative, probabilistic account of belief. On this account, what someone believes relative to a given question is (i) closed under entailment, (ii) sufficiently probable given their evidence, and (iii) sensitive to the relative probabilities of the answers to the question. Here

Emmanuel J. Genot

We argue that behavioral science models of online content-sharing overlook the role of strategic interactions between users. Borrowing from accuracy-nudges studies decision-theoretic models, we propose a basic game model and explore special cases with idealized parameter settings to identify refinements necessary to capture real-world online social network b

Marco Garapa, Eduardo Ferme, Maurício D. L. Reis

Two level credibility-limited revision is a non-prioritized revision operation. When revising by a two level credibility-limited revision, two levels of credibility and one level of incredibility are considered. When revising by a sentence at the highest level of credibility, the operator behaves as a standard revision, if the sentence is at the second level

Robert Ganian, Thekla Hamm, Dušan Knop, Sanjukta Roy

Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each coalition were captured using a utility function u that took into account distances in a given social network. In this paper, we consider a non-normalized score-based definition of social distance games where the utility function u_v depen

Rustam Galimullin, Louwe B. Kuijer

Arbitrary Public Announcement Logic with Common Knowledge (APALC) is an extension of Public Announcement Logic with common knowledge modality and quantifiers over announcements. We show that the satisfiability problem of APALC on S5-models, as well as that of two other related logics with quantification and common knowledge, is $\Sigma^1_1$-hard. This implie

James Fox, Matt MacDermott, Lewis Hammond, Paul Harrenstein

Multi-agent influence diagrams (MAIDs) are a popular game-theoretic model based on Bayesian networks. In some settings, MAIDs offer significant advantages over extensive-form game representations. Previous work on MAIDs has assumed that agents employ behavioural policies, which set independent conditional probability distributions over actions for each of th

Hung Le, Steven Senger, Minh-Quan Vo

We prove some novel multi-parameter point-line incidence estimates in vector spaces over finite fields. While these could be seen as special cases of higher-dimensional incidence results, they outperform their more general counterparts in those contexts. We go on to present a number of applications to illustrate their use in combinatorial problems from geome

Yiwen Ding, Krishna Manoorkar, Apostolos Tzimoulis, Ruoding Wang

This work extends Halpern and Pearl's causal models for actual causality to a possible world semantics environment. Using this framework we introduce a logic of actual causality with modal operators, which allows for reasoning about causality in scenarios involving multiple possibilities, temporality, knowledge and uncertainty. We illustrate this with a numb

Nicodemo De Vito

Hierarchies of conditional beliefs (Battigalli and Siniscalchi 1999) play a central role for the epistemic analysis of solution concepts in sequential games. They are practically modelled by type structures, which allow the analyst to represent the players' hierarchies without specifying an infinite sequence of conditional beliefs. Here, we study type struct

Armando Castañeda, Hans van Ditmarsch, David A. Rosenblueth, Diego A. Velázquez

Any kind of dynamics in dynamic epistemic logic can be represented as an action model. Right? Wrong! In this contribution we prove that the update expressivity of communication patterns is incomparable to that of action models. Action models, as update mechanisms, were proposed by Baltag, Moss, and Solecki in 1998 and have remained the nearly universally acc

Giacomo Bonanno

We provide a semantic characterization of AGM belief contraction based on frames consisting of a Kripke belief relation and a Stalnaker-Lewis selection function. The central idea is as follows. Let K be the initial belief set and K-A be the contraction of K by the formula A; then B belongs to the set K-A if and only if, at the actual state, the agent believe

Marta Bílková, Igor Sedlár

Epistemic logics of intensional groups lift the assumption that membership in a group of agents is common knowledge. Instead of being represented directly as a set of agents, intensional groups are represented by a property that may change its extension from world to world. Several authors have considered versions of the intensional group framework where gro

Edoardo Baccini, Zoé Christoff

Numerous logics have been developed to reason either about threshold-induced opinion diffusion in a network, or about similarity-driven network structure evolution, or about both. In this paper, we first introduce a logic containing different dynamic operators to capture changes that are 'asynchronous' (opinion change only, network-link change only) and chan

Itai Arieli, Ivan Geffner, Moshe Tennenholtz

In an information aggregation game, a set of senders interact with a receiver through a mediator. Each sender observes the state of the world and communicates a message to the mediator, who recommends an action to the receiver based on the messages received. The payoff of the senders and of the receiver depend on both the state of the world and the action se

Krzysztof R. Apt, Sunil Simon

Recently, in [K.R. Apt and S. Simon: Well-founded extensive games with perfect information, TARK21], we studied well-founded games, a natural extension of finite extensive games with perfect information in which all plays are finite. We extend here, to this class of games, two results concerned with iterated elimination of weakly dominated strategies, origin

Samuel Allen Alexander, Arthur Paul Pedersen

A fundamental question asked in modal logic is whether a given theory is consistent. But consistent with what? A typical way to address this question identifies a choice of background knowledge axioms (say, S4, D, etc.) and then shows the assumptions codified by the theory in question to be consistent with those background axioms. But determining the specifi

Fuxiao Liu, Paiheng Xu, Zongxia Li, Yue Feng

We investigate the role of various demonstration components in the in-context learning (ICL) performance of large language models (LLMs). Specifically, we explore the impacts of ground-truth labels, input distribution, and complementary explanations, particularly when these are altered or perturbed. We build on previous work, which offers mixed findings on h

Leonie Gomell, Imants Dirba, Hanna Bishara, Zhongji Sun

The influence of microstructure on thermoelectricity is increasingly recognized. Approaches for microstructural engineering can hence be exploited to enhance thermoelectric performance, particularly through manipulating crystalline defects, their structure, and composition. Here, we focus on a full-Heusler Fe2VAl-based compound that is one of the most promis

Jie Chen, Xiaoyun, Li, Chengxing

There has been an increasing use of master protocols in oncology clinical trials because of its efficiency and flexibility to accelerate cancer drug development. Depending on the study objective and design, a master protocol trial can be a basket trial, an umbrella trial, a platform trial, or any other form of trials in which multiple investigational product

Farid Arthaud, Martin Rinard

Epistemic logics model how agents reason about their beliefs and the beliefs of other agents. Existing logics typically assume the ability of agents to reason perfectly about propositions of unbounded modal depth. We present DBEL, an extension of S5 that models agents that can reason about epistemic formulas only up to a specific modal depth. To support expl

Carlo Proietti, Fernando R. Velázquez-Quesada, Antonio Yuste-Ginel

This work builds upon a well-established research tradition on modal logics of awareness. One of its aims is to export tools and techniques to other areas within modal logic. To this end, we illustrate a number of significant bridges with abstract argumentation, justification logics, the epistemic logic of knowing-what and deontic logic, where basic notions

Jaydip Sen, Subhasis Dasgupta

Portfolio optimization has been an area that has attracted considerable attention from the financial research community. Designing a profitable portfolio is a challenging task involving precise forecasting of future stock returns and risks. This chapter presents a comparative study of three portfolio design approaches, the mean-variance portfolio (MVP), hier

Vasilis Papaspirou, Leandros Maglaras, Ioanna Kantzavelou, Naghmeh Moradpoor

This paper extends and advances our recently introduced two-factor Honeytoken authentication method by incorporating blockchain technology. This novel approach strengthens the authentication method to prevent many attacks including tampering attacks. Evaluation results show that integrating blockchain into the Honeytoken method could improve performance and

Yoshiki Nakamura

We introduce the $k$-variable-occurrence fragment, which is the set of terms having at most $k$ occurrences of variables. We give a sufficient condition for the decidability of the equational theory of the $k$-variable-occurrence fragment using the finiteness of a monoid. As a case study, we prove that for Tarski's calculus of relations with bounded dot-dagg

Y. Bliokh, Y. Cao, V. Maksimov, A. Haim

It was observed experimentally that after crossing a waveguide filled with a neutral gas, a short powerful microwave pulse leaves a periodic glow of plasma along the waveguide, persisting several tens of nanoseconds. A theoretical model is presented which in combination with numerical simulations proposes a possible explanation of this phenomenon.

Anna Daniel Fome, Wolfgang Bock, Axel Klar

In the world of epidemics, the mathematical modeling of disease co-infection is gaining importance due to its contributions to mathematics and public health. Because the co-infection may have a double burden on families, countries, and the universe, understanding its dynamics is paramount. We study a SEIQR (susceptible-exposed-infectious-quarantined-recovere

Yipu Li, Yanjing Wang

Aristotle's discussions on modal syllogistic have often been viewed as error-prone and have garnered significant attention in the literature due to historical and philosophical interests. However, from a contemporary standpoint, they also introduced natural fragments of first-order modal logic, warranting a comprehensive technical analysis. In this paper, dr

Wesley Pegden, Anish Sevekari

In this paper, we provide a family of dynamic programming based algorithms to sample nearly-shortest self avoiding walks between two points of the integer lattice $\mathbb{Z}^2$. We show that if the shortest path of between two points has length $n$, then we can sample paths (self-avoiding-walks) of length $n+O(n^{1-\delta})$ in polynomial time. As an exampl

Adam Bjorndahl, Joseph Y. Halpern

In earlier work, we introduced the framework of language-based decisions, the core idea of which was to modify Savage's classical decision-theoretic framework by taking actions to be descriptions in some language, rather than functions from states to outcomes, as they are defined classically. Actions had the form "if psi then do(phi)", where psi and phi were

Gaia Belardinelli, Burkhard C. Schipper

Awareness structures by Fagin and Halpern (1988) (FH) feature a syntactic awareness correspondence and accessibility relations modeling implicit knowledge. They are a flexible model of unawareness, and best interpreted from a outside modeler's perspective. Unawareness structures by Heifetz, Meier, and Schipper (2006, 2008) (HMS) model awareness by a lattice

Philippe Balbiani, Wiebe van der Hoek, Louwe B. Kuijer

Correspondence theory allows us to create sound and complete axiomatizations for modal logic on frames with certain properties. For example, if we restrict ourselves to transitive frames we should add the axiom $\square \phi \rightarrow \square\square\phi$ which, among other things, can be interpreted as positive introspection. One limitation of this techniq

Wei Liu, Yudong Wang

The strong convergence of numerical methods for stochastic differential equations (SDEs) for $t\in[0,\infty)$ is proved. The result is applicable to any one-step numerical methods with Markov property that have the finite time strong convergence and the uniformly bounded moment. In addition, the convergence of the numerical stationary distribution to the und

Guanzhou Lan, Bin Zhao, Xuelong Li

Nighttime surveillance suffers from degradation due to poor illumination and arduous human annotations. It is challengable and remains a security risk at night. Existing methods rely on multi-spectral images to perceive objects in the dark, which are troubled by low resolution and color absence. We argue that the ultimate solution for nighttime surveillance

Aroonima Sahoo, Tofan Kumar Khuntia, Kishor Chandra Pati

This paper primarily deals with the study of G-derivations associated with Lie-Yamaguti algebras. Taking G as an automorphism group, the concept of G-derivations, which is a derivation under both the bilinear and trilinear operations is defined for Lie-Yamaguti algebras. Then some important properties of G-derivations are studied along with their relationshi

Daoan Zhang, Weitong Zhang, Yu Zhao, Jianguo Zhang

Pre-trained large language models demonstrate potential in extracting information from DNA sequences, yet adapting to a variety of tasks and data modalities remains a challenge. To address this, we propose DNAGPT, a generalized DNA pre-training model trained on over 200 billion base pairs from all mammals. By enhancing the classic GPT model with a binary cla

Bang Chen, Wei Peng, Maonian Wu, Bo Zheng

The recommendation system is not only a problem of inductive statistics from data but also a cognitive task that requires reasoning ability. The most advanced graph neural networks have been widely used in recommendation systems because they can capture implicit structured information from graph-structured data. However, like most neural network algorithms,

Chen Chen, Yufei Wang, Yang Zhang, Quan Z. Sheng

Knowledge graph completion (KGC) is the task of inferencing missing facts from any given knowledge graphs (KG). Previous KGC methods typically represent knowledge graph entities and relations as trainable continuous embeddings and fuse the embeddings of the entity $h$ (or $t$) and relation $r$ into hidden representations of query $(h, r, ?)$ (or $(?, r, t$))

Arvind Shankar Kumar

This is an introductory review of Musical Excellence of Mridangam by Dr. Umayalpuram K Sivaraman, Dr. T Ramasami and Dr. Naresh, which is a scientific treatise exploring the unique tonal properties of the ancient Indian classical percussive instrument -- the Mridangam. This review aims to bridge the gap between the primary intended audience of Musical Excell

Hojin Lee, Kanghoon Lee, Sangmin Lee

We verify the global Poincar\'e invariance of the Hamiltonian mechanics of gravitating binary dynamics at the second post Minkowskian (2PM) order. For spinless point particles, based on the known 2PM Hamiltonian in the center of momentum frame, we compute the general 2PM Hamiltonian valid in an arbitrary reference frame. An off-shell extension of the 1PM Ham

Ghada Alsuhli, Vasileios Sakellariou, Hani Saleh, Mahmoud Al-Qutayri

Deep neural networks (DNNs) have become an enabling component for a myriad of artificial intelligence applications. DNNs have shown sometimes superior performance, even compared to humans, in cases such as self-driving, health applications, etc. Because of their computational complexity, deploying DNNs in resource-constrained devices still faces many challen

Sushma Anand Akoju, Robert Vacareanu, Haris Riaz, Eduardo Blanco

We introduce a synthetic dataset called Sentences Involving Complex Compositional Knowledge (SICCK) and a novel analysis that investigates the performance of Natural Language Inference (NLI) models to understand compositionality in logic. We produce 1,304 sentence pairs by modifying 15 examples from the SICK dataset (Marelli et al., 2014). To this end, we mo

Yaozu Ye, Hao Shi, Kailun Yang, Ze Wang

Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for optical flow estimation. However, existing datasets from event cameras provide only low frame rate ground truth for optical flow, limiting the research potential of event-driven optical flow. To address this challenge, we introduce a low-latency event represent

Robert de Mello Koch

We study the holographic duality between the free $O(N)$ vector model and higher spin gravity. Conserved spinning primary currents of the conformal field theory (CFT) are dual to spinning gauge fields in the gravity. Reducing to independent components of the conserved CFT currents one finds two components at each spin. After gauge fixing the gravity and then

Aveek Chandra, Shuin Jian Wu, Angelina Frank, James A. Grieve

Quantum photonic devices operating in the single photon regime require the detection and characterization of quantum states of light. Chip-scale, waveguide-based devices are a key enabling technology for increasing the scale and complexity of such systems. Collecting single photons from multiple outputs at the end-face of such a chip is a core task that is f

Yu Ohno

We determine all the homogeneous structure tensors on $\mathbb{S}^2\times\mathbb{R}$ and $\mathbb{H}^2\times\mathbb{R}$. This work together with previous articles yields a complete classification of all the homogeneous structure tensors on three-dimensional homogeneous Riemannian manifolds.

Normen Yu, Gang Tan, Saeid Tizpaz-Niari

This thesis explores open-sourced machine learning (ML) model explanation tools to understand whether these tools can allow a layman to visualize, understand, and suggest intuitive remedies to unfairness in ML-based decision-support systems. Machine learning models trained on datasets biased against minority groups are increasingly used to guide life-alterin

U. Özdem

The magnetic and quadrupole moments of the $Z_{c}(4020)^+$, $Z_{c}(4050)^+$ and $Z_{c}(4600)^{+}$ states are calculated within the QCD light-cone sum rules. The compact diquark-antidiquark interpolating currents and the distribution amplitudes of the on-shell photon are used to extract the magnetic and quadrupole moments of these states. The magnetic moments

Yifan Sun, Stefan Wabnitz, Pedro Parra-Rivas

We study the dynamics of Kerr cavity solitons in the normal dispersion regime, in the presence of an intracavity phase modulation. The associated parabolic potential introduces multimode resonances, which promote the formation of high-order bright solitons. By gradually reducing the potential strength, bright solitons undergo a transition into dark solitons.

Kh. M. Shadimetov, R. S. Karimov

In this paper, we consider the problem of constructing new optimal explicit and implicit Adams-type difference formulas for finding an approximate solution to the Cauchy problem for an ordinary differential equation in a Hilbert space. In this work, I minimize the norm of the error functional of the difference formula with respect to the coefficients, we obt

Hui Kang, Sheng Liu, Huaxi Huang, Jun Yu

In recent years, research on learning with noisy labels has focused on devising novel algorithms that can achieve robustness to noisy training labels while generalizing to clean data. These algorithms often incorporate sophisticated techniques, such as noise modeling, label correction, and co-training. In this study, we demonstrate that a simple baseline usi

Run Lv, Wenqian Tu, Dingfu Shao, Yuping Sun

Recently, near-ambient superconductivity was claimed in nitrogen-doped lutetium hydride (LuH$_{3-\delta}$N$_{\epsilon}$) . Unfortunately, all follow-up research still cannot find superconductivity signs in successfully synthesized lutetium dihydride (LuH$_2$) and N-doped LuH$_{2\pm x}$N$_y$. However, a similar intriguing observation was the pressure-induced

Gourab Ghatak

We study the initial beam acquisition problem in millimeter wave (mm-wave) networks from the perspective of best arm identification in multi-armed bandits (MABs). For the stationary environment, we propose a novel algorithm called concurrent beam exploration, CBE, in which multiple beams are grouped based on the beam indices and are simultaneously activated

Sho Ejiri, Osamu Fujino, Masataka Iwai

In this paper, we study when positivity conditions of vector bundles are preserved by extension. We prove that an extension of a big (resp. pseudo-effective) line bundle by an ample (resp. a nef) vector bundle is big (resp. pseudo-effective). We also show that an extension of an ample line bundle by a big line bundle is not necessarily pseudo-effective. In p

Vlad Smolin

A topological space is called a submetrizable if it can be mapped onto a metrizable topological space by a continuous one-to-one map. In this paper we answer two questions concerning sequence-covering maps on submetrizable spaces.

Aidos Issadykov, Sayabek K. Sakhiyev

In this work we tried to predict the parameters of $B^{*}_c$ meson. Simple assumptions gave us following parametres $m_{B_{c}^{*}}=6329\pm 10$ MeV and $f_{B_{c}^{*}}= 535.5\pm57.8$ MeV (for $\Lambda_{B_{c}^{*}}=2.26\pm 0.14$ GeV in covariant confined quark model). We calculated widths of radiative decays of $B^*_{q}$ mesons, where $q=u/d,s,c$ and compared th

Sheng-Qi Zhang, Cong-Feng Qiao

Motivated by the recent experimental progress in the $ \Lambda_c $ decay that contains a neutron in the final state, we analyze the semileptonic decay $ \Lambda_c \rightarrow n \ell \nu_\ell $ in the framework of QCD sum rules. The transition form factors are analytically computed using three-point correlation functions and the Cutkosky cutting rules, which

Seonghyun Kim, Dukjae Jang, Soonchul Choi, Tsuyoshi Miyatsu

We explore the impact of neutron-rich nuclei masses on the symmetry energy properties using the mass table evaluated by the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) model. First, using the semi-empirical mass formula with the DRHBc mass table, we investigate the symmetry energy at saturation density $\rho_0$, denoted as $S_0$, and

Yi Liao, Yongsheng Gao, Weichuan Zhang

Decisions made by convolutional neural networks(CNN) can be understood and explained by visualizing discriminative regions on images. To this end, Class Activation Map (CAM) based methods were proposed as powerful interpretation tools, making the prediction of deep learning models more explainable, transparent, and trustworthy. However, all the CAM-based met

Jeongyun Kim, Myung-Hwan Jeon, Sangwoo Jung, Wooseong Yang

Transparent objects are encountered frequently in our daily lives, yet recognizing them poses challenges for conventional vision sensors due to their unique material properties, not being well perceived from RGB or depth cameras. Overcoming this limitation, thermal infrared cameras have emerged as a solution, offering improved visibility and shape informatio

Asmita Kumari

Entanglement is necessary but not sufficient to demonstrate nonlocality as there exist local entangled states which do not violate any Bell inequality. In recent years, the activation of nonlocality (known as hidden nonlocality) by using local filtering operations has gained considerable interest. In the original proposal of Popescu [Phys. Rev. Lett. 74, 261

Shengyi Li, Qifan Xue, Yezhuo Zhang, Xuanpeng Li

Trajectory prediction is critical for autonomous driving vehicles. Most existing methods tend to model the correlation between history trajectory (input) and future trajectory (output). Since correlation is just a superficial description of reality, these methods rely heavily on the i.i.d. assumption and evince a heightened susceptibility to out-of-distribut

Renhao Wang, Yu Sun, Arnuv Tandon, Yossi Gandelsman

Prior work has established Test-Time Training (TTT) as a general framework to further improve a trained model at test time. Before making a prediction on each test instance, the model is first trained on the same instance using a self-supervised task such as reconstruction. We extend TTT to the streaming setting, where multiple test instances - video frames

Aidos Issadykov, Mikhail A. Ivanov

A brief review of the current state of observed deviations of theoretical predictions from experimental data in semileptonic decays of $B$ and $B_c$ mesons is given. A theoretical analysis of these decays is carried out, taking into account the effects of new physics, which appear due to the introduction of new four-fermion operators, which are absent in the

Silvia Bertoluzza, Erik Burman, Cuiyu He

In this paper, we provide a theoretical analysis of the recently introduced weakly adversarial networks (WAN) method, used to approximate partial differential equations in high dimensions. We address the existence and stability of the solution, as well as approximation bounds. More precisely, we prove the existence of discrete solutions, intended in a suitab

Shin'ichi Nojiri, Sergei D. Odintsov, Tanmoy Paul, Soumitra SenGupta

The question that continues to hinge the interrelation between cosmology and thermodynamics is broadly described as -- what is the form of horizon entropy that links the Friedmann equations for a "$general$" gravity theory with the underlying thermodynamics of the apparent horizon? The answer to this question was known only for Einstein's gravity and for $(n

San-Dong Guo

The antiferromagnetic (AFM) materials are robust to external magnetic perturbation due to missing any net magnetic moment. In general, the spin splitting in the band structures disappears in these antiferromagnets. However, the altermagnetism can achieve spin-split bands in collinear symmetry-compensated antiferromagnet with special magnetic space group. Her

Meng Sun, Tilen Čadež, Igor Yurkevich, Alexei Andreanov

We study the interplay between quasi-periodic disorder and superconductivity in a 1D tight-binding model with the quasi-periodic modulation of on-site energies that follow the Fibonacci rule and all the eigenstates are multifractal. As a signature of multifractality, we observe the power-law dependence of the correlation between different single-particle eig