April 2024 arXiv papers — page 155

Juncheng Yang, Zuchao Li, Shuai Xie, Wei Yu

The chain-of-thought technique has been received well in multi-modal tasks. It is a step-by-step linear reasoning process that adjusts the length of the chain to improve the performance of generated prompts. However, human thought processes are predominantly non-linear, as they encompass multiple aspects simultaneously and employ dynamic adjustment and updat

Stefano Longhi

Anderson localization, i.e. the suppression of diffusion in lattices with random or incommensurate disorder, is a fragile interference phenomenon which is spoiled out in the presence of dephasing effects or fluctuating disorder. As a consequence, Anderson localization-delocalization phase transitions observed in Hermitian systems, such as in one-dimensional

Stefano Longhi

The non-Hermitian skin effect describes the concentration of an extensive number of eigenstates near the boundaries of certain dissipative systems. This phenomenon has raised a huge interest in different areas of physics, including photonics, deeply expanding our understanding of non-Hermitian systems and opening up new avenues in both fundamental and applie

J. Mark Keil, Fraser McLeod, Debajyoti Mondal

The classical 3SUM conjecture states that the class of 3SUM-hard problems does not admit a truly subquadratic $O(n^{2-\delta})$-time algorithm, where $\delta >0$, in classical computing. The geometric 3SUM-hard problems have widely been studied in computational geometry and recently, these problems have been examined under the quantum computing model. For ex

Hamidreza Montaseri, Amin Gohari

The proliferation of algorithmic systems has fueled discussions surrounding the regulation and control of their social impact. Herein, we consider a system whose primary objective is to maximize utility by selecting the most qualified individuals. To promote demographic parity in the selection algorithm, we consider penalizing discrimination across social gr

Hal Tasaki

In the present note, we discuss a simple example of a macroscopic quantum many-body system in which the approach to thermal equilibrium from an arbitrary initial state in the microcanonical energy shell is proved without relying on any unproven assumptions. The model, which is equivalent to a free fermion chain, is designed to be a toy model for a weakly hea

Seokwoo Yeo, HyungJoo Kim, Su Houng Lee

Observing the mass shifts of mesons immersed in nuclear matter is interesting, as the changes are expected to shed light on the effects of chiral symmetry breaking on the origin of hadron masses. At the same time, it is important to understand the momentum dependence of the masses for spin-1 mesons, as the changes manifest differently across the two polariza

Xianping Ma, Xiaokang Zhang, Xingchen Ding, Man-On Pun

Unsupervised domain adaptation (UDA) techniques are vital for semantic segmentation in geosciences, effectively utilizing remote sensing imagery across diverse domains. However, most existing UDA methods, which focus on domain alignment at the high-level feature space, struggle to simultaneously retain local spatial details and global contextual semantics. T

Poulami Ghosh, Shikhar Vashishth, Raj Dabre, Pushpak Bhattacharyya

Contemporary deep learning models effectively handle languages with diverse morphology despite not being directly integrated into them. Morphology and word order are closely linked, with the latter incorporated into transformer-based models through positional encodings. This prompts a fundamental inquiry: Is there a correlation between the morphological comp

Gianluca Paolini

In [21] it was asked if equality on the reals is sharp as a lower bound for the complexity of topological isomorphism between oligomorphic groups. We prove that under the assumption of weak elimination of imaginaries this is indeed the case. Our methods are model theoretic and they also have applications on the classical problem of reconstruction of isomorph

Arvish Dabra, Rattan Lal, N. Shravan Kumar

Let $G$ be a locally compact group and $(\Phi,\Psi)$ a complementary pair of Young functions satisfying the $\Delta_2$-condition. Let $A_\Phi(G)$ be the Orlicz analogue of the Fig\`{a}-Talamanca Herz algebra $A_p(G).$ The dual of the algebra $A_\Phi(G)$ is the space of $\Psi$-pseudomeasures, denoted by $PM_\Psi(G).$ For certain topologically introverted subs

Sachini Wickramasinghe, Dhruv Parikh, Bingyi Zhang, Rajgopal Kannan

Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) is a key technique used in military applications like remote-sensing image recognition. Vision Transformers (ViTs) are the current state-of-the-art in various computer vision applications, outperforming their CNN counterparts. However, using ViTs for SAR ATR applications is challenging due to

Sara Rojas, Julien Philip, Kai Zhang, Sai Bi

Recent advancements in diffusion models have shown remarkable proficiency in editing 2D images based on text prompts. However, extending these techniques to edit scenes in Neural Radiance Fields (NeRF) is complex, as editing individual 2D frames can result in inconsistencies across multiple views. Our crucial insight is that a NeRF scene's geometry can serve

Shubham Patel, Divyaksh Shukla, Ashutosh Modi

This paper presents our approach for the SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversations. For the Emotion Recognition in Conversations (ERC) task, we utilize a masked-memory network along with speaker participation. We propose a transformer-based speaker-centric model for the Emotion Flip Reasoning (EFR) task. We also introduc

Roukaya Dekhil, Alexander F. Jercher, Daniele Oriti, Andreas G. A. Pithis

We continue the series of articles on the application of Landau-Ginzburg mean-field theory to unveil the basic phase structure of tensorial field theories which are characterized by combinatorially non-local interactions. Among others, this class covers tensor field theories (TFT) which lead to a new class of conformal field theories highly relevant for inve

Evgeniy Lokharu, Miles H. Wheeler

One of the most striking features of two-dimensional steady water waves with adverse vorticity is the emergence of stagnation points in the flow, even along branches of solutions that are initially unidirectional. In this paper we show that, for constant adverse vorticity above a certain explicit threshold, the first stagnation point must appear on the bed d

Zhiyuan Peng, Xuyang Wu, Qifan Wang, Sravanthi Rajanala

Parameter Efficient Fine-Tuning (PEFT) methods have been extensively utilized in Large Language Models (LLMs) to improve the down-streaming tasks without the cost of fine-tuing the whole LLMs. Recent studies have shown how to effectively use PEFT for fine-tuning LLMs in ranking tasks with convincing performance; there are some limitations, including the lear

Bama Srinivasan, Mala Nehru, Ranjani Parthasarathi, Saswati Mukherjee

This paper provides a few approaches to automating computer programming and project submission tasks, that we have been following for the last six years and have found to be successful. The approaches include using CodeRunner with Learning Management System (LMS) integration for programming practice and evaluation, and Git (GitHub) for project submissions an

Shreenaga Chikoti, Shrey Mehta, Ashutosh Modi

Memes are one of the most popular types of content used in an online disinformation campaign. They are primarily effective on social media platforms since they can easily reach many users. Memes in a disinformation campaign achieve their goal of influencing the users through several rhetorical and psychological techniques, such as causal oversimplification,

Yuhong Mo, Hao Qin, Yushan Dong, Ziyi Zhu

In this paper, a tool for detecting LLM AI text generation is developed based on the Transformer model, aiming to improve the accuracy of AI text generation detection and provide reference for subsequent research. Firstly the text is Unicode normalised, converted to lowercase form, characters other than non-alphabetic characters and punctuation marks are rem

Andronikos Paliathanasis

Inspired by the generalization of scalar field gravitational models with a minimum length we study the equivalent theory in modified theories of gravity. The quadratic Generalized Uncertainty Principle (GUP) gives rise to a deformed Heisenberg algebra in the application, resulting in the emergence of additional degrees of freedom described by higher-order de

Yu Cai, Weiwen Zhang, Hao Chen, Kwang-Ting Cheng

Anomaly detection (AD) aims at detecting abnormal samples that deviate from the expected normal patterns. Generally, it can be trained merely on normal data, without a requirement for abnormal samples, and thereby plays an important role in rare disease recognition and health screening in the medical domain. Despite the emergence of numerous methods for medi

Chong Zhang, Mingyu Jin, Qinkai Yu, Chengzhi Liu

Current large language models (LLMs) provide a strong foundation for large-scale user-oriented natural language tasks. A large number of users can easily inject adversarial text or instructions through the user interface, thus causing LLMs model security challenges. Although there is currently a large amount of research on prompt injection attacks, most of t

Pengxiao Han, Changkun Ye, Jieming Zhou, Jing Zhang

Long-tailed imbalance distribution is a common issue in practical computer vision applications. Previous works proposed methods to address this problem, which can be categorized into several classes: re-sampling, re-weighting, transfer learning, and feature augmentation. In recent years, diffusion models have shown an impressive generation ability in many su

Piyali Bhar

The physical properties of a (3+1)-D gravastar in the context of massive gravity are discussed in this work. In present investigation, the field equations have been solved for a static, uncharged sphere in order to achieve the gravastar model as proposed by Mazur and Mottola [Mazur and Mottola in Report No. LA-UR-01-5067,(2001); Mazur and Mottola, {\em Proc

Andre Ye, Jared Moore, Rose Novick, Amy X. Zhang

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 pr

Adithya Murali, Cody Rivera, P. Madhusudan

We propose a novel mechanism of defining data structures using intrinsic definitions that avoids recursion and instead utilizes monadic maps satisfying local conditions. We show that intrinsic definitions are a powerful mechanism that can capture a variety of data structures naturally. We show that they also enable a predictable verification methodology that

Songtao Jiang, Yan Zhang, Chenyi Zhou, Yeying Jin

Multimodal Large Language Models (MLLMs) such as GPT-4V and Gemini Pro face challenges in achieving human-level perception in Visual Question Answering (VQA), particularly in object-oriented perception tasks which demand fine-grained understanding of object identities, locations or attributes, as indicated by empirical findings. This is mainly due to their l

Udvas Basak, Rajarshi Dutta, Shivam Pandey, Ashutosh Modi

This paper describes our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness. The challenge is focused on automatically detecting the degree of relatedness between pairs of sentences for 14 languages including both high and low-resource Asian and African languages. Our team participated in two subtasks consisting of Track A: supervised

Rosa Orellana, Franco Saliola, Anne Schilling, Mike Zabrocki

It is an important problem in algebraic combinatorics to deduce the Schur function expansion of a symmetric function whose expansion in terms of the fundamental quasisymmetric function is known. For example, formulas are known for the fundamental expansion of a Macdonald symmetric function and for the plethysm of two Schur functions, while the Schur expansio

Hai-Dang Huynh-Lam, Ngoc-Phuong Ho-Thi, Minh-Triet Tran, Trung-Nghia Le

In this paper, we present TAC-SUM, a novel and efficient training-free approach for video summarization that addresses the limitations of existing cluster-based models by incorporating temporal context. Our method partitions the input video into temporally consecutive segments with clustering information, enabling the injection of temporal awareness into the

Shreyasi Mandal, Ashutosh Modi

Large Language models (LLMs) have demonstrated state-of-the-art performance in various natural language processing (NLP) tasks across multiple domains, yet they are prone to shortcut learning and factual inconsistencies. This research investigates LLMs' robustness, consistency, and faithful reasoning when performing Natural Language Inference (NLI) on breast

I-Hong Hou

This paper studies multi-stage systems with end-to-end bandit feedback. In such systems, each job needs to go through multiple stages, each managed by a different agent, before generating an outcome. Each agent can only control its own action and learn the final outcome of the job. It has neither knowledge nor control on actions taken by agents in the next s

Qiancheng Yang, Qiong Liu, Grant M. Kennedy, Mark C. Wyatt

Most debris discs consist of a gas-poor, cold dust belt located tens to hundreds of astronomical units away from the host star. Many cold dust belts exhibit distinct structures attributed to the dynamic interaction of planetary systems. Moreover, in a few systems, additional warm components can be found closer to the central star, resembling the asteroid bel

Kai Jiang, Xueyang Li, Yao Ma, Juan Zhang

In this paper, we propose a new algorithm, the irrational-window-filter projection method (IWFPM), for quasiperiodic systems with concentrated spectral point distribution. Based on the projection method (PM), IWFPM filters out dominant spectral points by defining an irrational window and uses a corresponding index-shift transform to make the FFT available. T

Simonetta Vezzoso

The Digital Markets Act (DMA) aims to ensure contestability and fairness in digital markets, particularly focusing on regulating Big Tech companies. The paper explores the DMA's capacity to address both current and future challenges in digital market contestability and fairness, spotlighting the trend towards platform integration and the potential rise of "s

Zhengying Lou, Ruibo Wang, Baha Eddine Youcef Belmekki, Mustafa A. Kishk

Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics

Chao Yang, Zhujun Zhang

To study the fixed parameter undecidability of tiling problem for a set of Wang tiles, Jeandel and Rolin show that the tiling problem for a set of 44 Wang bars is undecidable. In this paper, we improve their result by proving that whether a set of 29 Wang bars can tile the plane is undecidable. As a consequence, the tiling problem for a set of Wang tiles wit

Yuya Koda, Makoto Ozawa, Yi-Sheng Wang

We classify all potential configurations of essential annuli in a genus two atoroidal handlebody exterior in the $3$-sphere, building on two recent classifications: the classification of the JSJ-graph of the exterior and the classification of essential annuli in the exterior. In contrast to knots, genus two handlebody exteriors may contain infinitely many no

Arkabrata Ghosh, Sayan Goswami, Sourav Kanti Patra

The study of symmetric structures is a new trend in Ramsey theory. Recently in [7], Di Nasso initiated a systematic study of symmetrization of classical Ramsey theoretical results, and proved a symmetric version of several Ramsey theoretic results. In this paper Di Nasso asked if his method could be adapted to find new non-linear Diophantine equations that a

Ondřej Kopáček, Vladimír Karas

According to General Relativity, astrophysical black holes are described by a small number of parameters. Apart from the mass of the black hole (M), among the most interesting characteristics is the spin (a), which determines the degree of rotation, i.e., the angular momentum of the black hole. The latter is observationally constrained by the spectral and ti

Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto

There is an increasing conflict between business incentives to hide models and data as trade secrets, and the societal need for algorithmic transparency. For example, a rightsholder wishing to know whether their copyrighted works have been used during training must convince the model provider to allow a third party to audit the model and data. Finding a mutu

Fei Cao, Xiaoqian Gong

In this manuscript we investigate the equivalence of Fourier-based metrics on discrete state spaces with the well-known Wasserstein distances. While the use of Fourier-based metrics in continuous state spaces is ubiquitous since its introduction by Giuseppe Toscani and his colleagues [9, 14, 16] in the study of kinetic-type partial differential equations, th

Tomoya Wakayama

The remarkable generalization performance of large-scale models has been challenging the conventional wisdom of the statistical learning theory. Although recent theoretical studies have shed light on this behavior in linear models and nonlinear classifiers, a comprehensive understanding of overparameterization in nonlinear regression models is still lacking.

Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao

This paper introduces an approach to address the target enclosing problem using non-holonomic multiagent systems, where agents self-organize on the enclosing shape around a fixed target. In our approach, agents independently move toward the desired enclosing geometry when apart and activate the collision avoidance mechanism when a collision is imminent, ther

Md Nakhla Rafi, Dong Jae Kim, An Ran Chen, Tse-Hsun Chen

Automatic software fault localization plays an important role in software quality assurance by pinpointing faulty locations for easier debugging. Coverage-based fault localization, a widely used technique, employs statistics on coverage spectra to rank code based on suspiciousness scores. However, the rigidity of statistical approaches calls for learning-bas

Rosen, Yu, Cyril Picard, Faez Ahmed

Bayesian Optimization (BO) is a foundational strategy in the field of engineering design optimization for efficiently handling black-box functions with many constraints and expensive evaluations. This paper introduces a fast and accurate BO framework that leverages Pre-trained Transformers for Bayesian Optimization (PFN4sBO) to address constrained optimizati

Takeshi Fukasawa

This study investigates computationally efficient inner-loop algorithms for estimating static/dynamic BLP models. It provides the following ideas for reducing the number of inner-loop iterations: (1). Add a term relating to the outside option share in the BLP contraction mapping; (2). Analytically represent the mean product utilities as a function of value f

N. Nakhonthong, P. Chainakun, W. Luangtip, A. J. Young

We present the Granger causality (GC) test for the X-ray reverberation analysis of Active Galactic Nuclei (AGN). If the light curves in the continuum-dominated band help predict (Granger cause) those dominated by reflection, the Granger lags that associate to the intrinsic reverberation lags can be inferred. We focus on six AGN observed by XMM-Newton, includ

Han Lei, Baoming Wang, Zuwei Shui, Peiyuan Yang

In addition to environmental perception sensors such as cameras, radars, etc. in the automatic driving system, the external environment of the vehicle is perceived, in fact, there is also a perception sensor that has been silently dedicated in the system, that is, the positioning module. This paper explores the application of SLAM (Simultaneous Localization

Suk Yee Yong, K. E. Harborne, Caroline Foster, Robert Bassett

Since the turn of the century, astronomers have been exploiting the rich information afforded by combining stellar kinematic maps and imaging in an attempt to recover the intrinsic, three-dimensional (3D) shape of a galaxy. A common intrinsic shape recovery method relies on an expected monotonic relationship between the intrinsic misalignment of the kinemati

Yan Kang, Ziyao Ren, Lixin Fan, Linghua Yang

SecureBoost is a tree-boosting algorithm that leverages homomorphic encryption (HE) to protect data privacy in vertical federated learning. SecureBoost and its variants have been widely adopted in fields such as finance and healthcare. However, the hyperparameters of SecureBoost are typically configured heuristically for optimizing model performance (i.e., u

Carlos G. Torres-Castanedo, Dominic P. Goronzy, Thang Pham, Anthony McFadden

Superconducting Nb thin films have recently attracted significant attention due to their utility for quantum information technologies. In the processing of Nb thin films, fluoride-based chemical etchants are commonly used to remove surface oxides that are known to affect superconducting quantum devices adversely. However, these same etchants can also introdu

Yinbin Deng, Longge Shi

In this paper, we consider the existence and nonexistence of positive solution for a Neumann problem with double critical exponents and fast increasing weighted in half-space. This problem is closely related to the study of self-similar solutions for nonlinear heat equation. By applying the Mountain Pass Theorem without (PS) condition and the delicate estima

Rustem Yeshpanov, Pavel Efimov, Leonid Boytsov, Ardak Shalkarbayuli

We introduce KazQAD -- a Kazakh open-domain question answering (ODQA) dataset -- that can be used in both reading comprehension and full ODQA settings, as well as for information retrieval experiments. KazQAD contains just under 6,000 unique questions with extracted short answers and nearly 12,000 passage-level relevance judgements. We use a combination of m

Lars Becker, Paata Ivanisvili, Dmitry Krachun, Jóse Madrid

We show that for all $A, B \subseteq \{0,1,2\}^{d}$ we have $$ |A+B|\geq (|A||B|)^{\log(5)/(2\log(3))}. $$ We also show that for all finite $A,B \subset \mathbb{Z}^{d}$, and any $V \subseteq\{0,1\}^{d}$ the inequality $$ |A+B+V|\geq |A|^{1/p}|B|^{1/q}|V|^{\log_{2}(p^{1/p}q^{1/q})} $$ holds for all $p \in (1, \infty)$, where $q=\frac{p}{p-1}$ is the conjugate

Hongyan Gu, Chunxu Yang, Shino Magaki, Neda Zarrin-Khameh

As Artificial Intelligence (AI) making advancements in medical decision-making, there is a growing need to ensure doctors develop appropriate reliance on AI to avoid adverse outcomes. However, existing methods in enabling appropriate AI reliance might encounter challenges while being applied in the medical domain. With this regard, this work employs and prov

Linn Abraham, Sheelu Abraham, Ajit K. Kembhavi, N. S. Philip

Morphological features in galaxies, like spiral arms, bars, rings, tidal tails etc. carry information about their structure, origin and evolution. It is therefore important to catalog and study such features and to correlate them with other basic galaxy properties, the environment in which the galaxies are located and their interactions with other galaxies.

Siyuan Tian, Hao Wang, Yiren Rong, Junhao Wang

Modern displays nowadays possess the capability to render video content with a high dynamic range (HDR) and an extensive color gamut .However, the majority of available resources are still in standard dynamic range (SDR). Therefore, we need to identify an effective methodology for this objective.The existing deep neural networks (DNN) based SDR to HDR conver

Liqun Fu, Jingwen Tong, Tongtong Lin, Jun Zhang

As the cloud is pushed to the edge of the network, resource allocation for user experience improvement in mobile edge clouds (MEC) is increasingly important and faces multiple challenges. This paper studies quality of experience (QoE)-oriented resource allocation in MEC while considering user diversity, limited resources, and the complex relationship between

Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu

Cross-Domain Recommendation (CDR) seeks to enable effective knowledge transfer across domains. Existing works rely on either representation alignment or transformation bridges, but they struggle on identifying domain-shared from domain-specific latent factors. Specifically, while CDR describes user representations as a joint distribution over two domains, th

Guangdong Nie, Guanghui Han, Erfa S. Z., Kangxi Liu

Binary compound FeGe hosts multiple structures, from cubic and hexagonal to monoclinic. Compared to the well-known skyrmion lattice in the cubic phase and the antiferromagnetic charge-density wave in the hexagonal phase, the monoclinic FeGe is less explored. Here, we synthesized the monoclinic FeGe films on Al2O3 (001) and studied their structural, magnetic,

Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie

Image-to-image translation is a vital component in medical imaging processing, with many uses in a wide range of imaging modalities and clinical scenarios. Previous methods include Generative Adversarial Networks (GANs) and Diffusion Models (DMs), which offer realism but suffer from instability and lack uncertainty estimation. Even though both GAN and DM met

Dong-Yu Hong, Zhuo-Hui Wang, Shuang-Yong Zhou

The Wilson coefficients of the Standard Model Effective Field Theory are subject to a series of positivity bounds. It has been shown that, while the positivity part of the UV partial wave unitarity leads to the Wilson coefficients living in a convex cone, further including the non-positivity part caps the cone from above. For the Higgs scattering, a capped p

Tian Chen, Guanxu Li, Zhen Wu

In this paper, we consider the mean field optimal switching problem with a Markov chain under viscosity solution notion. Based on the conditional distribution of the Markov chain, the value function and corresponding dynamic programming principle (DPP) are established. The switching problem is characterized by an obstacle equation on the Wasserstein space, a

Zhengcong Fei, Mingyuan Fan, Changqian Yu, Debang Li

Transformers have catalyzed advancements in computer vision and natural language processing (NLP) fields. However, substantial computational complexity poses limitations for their application in long-context tasks, such as high-resolution image generation. This paper introduces a series of architectures adapted from the RWKV model used in the NLP, with requi

Xin Zhang, Dongfang Xu, Shenghui Song, Mérouane Debbah

The multiple-input and multiple-output (MIMO) technique is regarded as a promising approach to boost the throughput and reliability of optical fiber communications. However, the fundamental limits of optical fiber MIMO systems with finite block-length (FBL) are not available in the literature. This paper studies the fundamental limits of optical fiber multic

Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of models to rapidly learn new information in real-world scenarios where data follows long-tailed distributions, all while avoiding forgetting previously acquired knowledge. In this work, we study the under-explored problem of Long-Tailed Online Continual Learning

Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B. Hashimoto

LLM-based auto-annotators have become a key component of the LLM development process due to their cost-effectiveness and scalability compared to human-based evaluation. However, these auto-annotators can introduce biases that are hard to remove. Even simple, known confounders such as preference for longer outputs remain in existing automated evaluation metri

Yi Li, Xin Xie, Lina Lei, Haiyan Fu

The generation of smooth and continuous images between domains has recently drawn much attention in image-to-image (I2I) translation. Linear relationship acts as the basic assumption in most existing approaches, while applied to different aspects including features, models or labels. However, the linear assumption is hard to conform with the element dimensio

Yunrui Qiu, Inhyuk Jang, Xuhui Huang, Arun Yethiraj

Unraveling the relation between structural information and the dynamic properties of supercooled liquids is one of the grand challenges of physics. Dynamic heterogeneity, characterized by the propensity of particles, is often used as a proxy for the dynamic slowing down. In this work, we introduce an unsupervised machine learning approach based on a time-lag

Pengyuan Lu, Lin Zhang, Mengyu Liu, Kaustubh Sridhar

Cyber-physical systems (CPS) have experienced rapid growth in recent decades. However, like any other computer-based systems, malicious attacks evolve mutually, driving CPS to undesirable physical states and potentially causing catastrophes. Although the current state-of-the-art is well aware of this issue, the majority of researchers have not focused on CPS

Shijie Cui, Xu Guo, Zhe Zhang

This paper is concerned with estimation and inference for ultrahigh dimensional partially linear single-index models. The presence of high dimensional nuisance parameter and nuisance unknown function makes the estimation and inference problem very challenging. In this paper, we first propose a profile partial penalized least squares estimator and establish t

Cesar A. Ipanaque Zapata, Daciberg L. Gonçalves

In this paper, for fibrations $p:E\to B$, $p':E'\to B$ over $B$ and a free involution $\tau:E\to E$ which satisfy the equality $p\circ\tau=p$, we discover a connection between the sectional category of the double covers $q:E\to E/\tau$ and $q^Y:F_{p'}(E',2)\to F_{p'}(E',2)/\mathbb{Z}_2$ from the $2$-ordered fibre-wise configuration space $F_{p'}(E',2)$ to it

Pei Wang, Zhaowei Cai, Hao Yang, Ashwin Swaminathan

Existing unified image segmentation models either employ a unified architecture across multiple tasks but use separate weights tailored to each dataset, or apply a single set of weights to multiple datasets but are limited to a single task. In this paper, we introduce the Mixed-Query Transformer (MQ-Former), a unified architecture for multi-task and multi-da

Jasmina Veta Buralieva, Diana T. Stoeva, Katerina Hadzi-Velkova Saneva, Sanja Atanasova

This paper is a short overview of the main Abelian- and Tauberian-type results from [4, 14, 26] regarding the asymptotic analysis of different classes of generalized functions in terms of appropriate frames. The Tauberian-type results provide a comprehensive characterization of the quasiasymptotic and S-asymptotic properties of distributions.

Sentao Miao, Yining Wang

This paper proposes a practically efficient algorithm with optimal theoretical regret which solves the classical network revenue management (NRM) problem with unknown, nonparametric demand. Over a time horizon of length $T$, in each time period the retailer needs to decide prices of $N$ types of products which are produced based on $M$ types of resources wit

Ke Lan

The lack of key experimental data leads us to the conclusion that, the published experimental confirmation of driving pressure boosting and smoothing for hybrid-drive inertial fusion is not credible.

Daisuke Mashima, Yao Chen, Muhammad M. Roomi, Subhash Lakshminarayana

Smart Grid is a power grid system that uses digital communication technologies. By deploying intelligent devices throughout the power grid infrastructure,from power generation to consumption, and enabling communication among them, it revolutionizes the modern power grid industry with increased efficiency, reliability, and availability. However, reliance on i

Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato

We present Diffusion-KTO, a novel approach for aligning text-to-image diffusion models by formulating the alignment objective as the maximization of expected human utility. Since this objective applies to each generation independently, Diffusion-KTO does not require collecting costly pairwise preference data nor training a complex reward model. Instead, our

Ljiljana Arambašić, Diana T. Stoeva

Let $I\subseteq \Bbb N$ be a finite or infinite set and let ${(x_n)_{n\in I}}$ be a frame for a separable Hilbert space $\mathcal{H}$. Consider transmission of a signal $h\in\mathcal{H}$ where a finite subset $(\langle h,x_n\rangle)_{n\in E}$ of the frame coefficients $(\langle h,x_n\rangle)_{n\in I}$ is lost. There are several approaches in the literature a

Roberto Paroni, Brian Seguin

In this work we address the following question: is it possible for a one-dimensional, linearly elastic beam to only bend on the Cantor set and, if so, what would the bending energy of such a beam look like? We answer this question by considering a sequence of beams, indexed by $n$, each one only able to bend on the set associated with the $n$-th step in the

Caelan Atamanchuk, Luc Devroye, Gabor Lugosi

A \emph{random temporal graph} is an Erd\H{o}s-R\'enyi random graph $G(n,p)$, together with a random ordering of its edges. A path in the graph is called \emph{increasing} if the edges on the path appear in increasing order. A set $S$ of vertices forms a \emph{temporal clique} if for all $u,v \in S$, there is an increasing path from $u$ to $v$. \cite{Becker2

Swagat Ranjit

Foreign currency exchange plays a vital role for trading of currency in the financial market. Due to its volatile nature, prediction of foreign currency exchange is a challenging task. This paper presents different machine learning techniques like Artificial Neural Network (ANN), Recurrent Neural Network (RNN) to develop prediction model between Nepalese Rup

Hui Tong, Nir Guttman, Teagan A. Clarke, Paul D. Lasky

It has become increasingly useful to answer questions in gravitational-wave astronomy using transdimensional models where the number of free parameters can be varied depending on the complexity required to fit the data. Given the growing interest in transdimensional inference, we introduce a new package for the Bayesian inference Library (Bilby) called tBilb

Xiaokun Teng, David W. Tam, Lebing Chen, Hengxin Tan

Understanding spin and lattice excitations in a metallic magnetic ordered system form the basis to unveil the magnetic and lattice exchange couplings and their interactions with itinerant electrons. Kagome lattice antiferromagnet FeGe is interesting because it displays rare charge density wave (CDW) deep inside the antiferromagnetic ordered phase that intera

Simindokht Jahangard, Zhixi Cai, Shiki Wen, Hamid Rezatofighi

Understanding human social behaviour is crucial in computer vision and robotics. Micro-level observations like individual actions fall short, necessitating a comprehensive approach that considers individual behaviour, intra-group dynamics, and social group levels for a thorough understanding. To address dataset limitations, this paper introduces JRDB-Social,

Tim Dalby

Another proof that uniformly nonsquare Banach spaces have the fixed point property is presented.

Matthew H. Hamil, Daniel K. Nakano

Balmer recently showed that there is a general notion of a nilpotence theorem for tensor triangulated categories through the use of homological residue fields and the connection with the homological spectrum. The homological spectrum (like the theory of $\pi$-points) can be viewed as a topological space that provides an important realization of the Balmer sp

Muhammad Asad, Ihsan Ullah, Ganesh Sistu, Michael G. Madden

In novelty detection, the goal is to decide if a new data point should be categorized as an inlier or an outlier, given a training dataset that primarily captures the inlier distribution. Recent approaches typically use deep encoder and decoder network frameworks to derive a reconstruction error, and employ this error either to determine a novelty score, or

Eric Kubischta, Ian Teixeira

In a recent paper, we defined twisted unitary $1$-groups and showed that they automatically induced error-detecting quantum codes. We also showed that twisted unitary $1$-groups correspond to irreducible products of characters thereby reducing the problem of code-finding to a computation in the character theory of finite groups. Using a combination of GAP co

Jairo Diaz-Rodriguez, Juan Pablo Gomez, Jeremy P. Orange, Nathan D. Burkett-Cadena

Identifying areas in a landscape where individuals have a higher likelihood of disease infection is key to managing diseases. Unlike conventional methods relying on ecological assumptions, we perform a novel epidemiological tomography for the estimation of landscape propensity to disease infection, using GPS animal tracks in a manner analogous to tomographic

Shuo Xie, Zhiyuan Li

Adam with decoupled weight decay, also known as AdamW, is widely acclaimed for its superior performance in language modeling tasks, surpassing Adam with $\ell_2$ regularization in terms of generalization and optimization. However, this advantage is not theoretically well-understood. One challenge here is that though intuitively Adam with $\ell_2$ regularizat

CUORE Collaboration, D. Q. Adams, C. Alduino, K. Alfonso

Matter-antimatter asymmetry underlines the incompleteness of the current understanding of particle physics. Neutrinoless double-beta decay ($0\nu \beta\beta$) may help explain this asymmetry, while unveiling the Majorana nature of the neutrino. The CUORE experiment searches for $0\nu \beta\beta$ of $^{130}$Te using a tonne-scale cryogenic calorimeter operate

Shadi Alijani, Jamil Fayyad, Homayoun Najjaran

Deep learning models are often evaluated in scenarios where the data distribution is different from those used in the training and validation phases. The discrepancy presents a challenge for accurately predicting the performance of models once deployed on the target distribution. Domain adaptation and generalization are widely recognized as effective strateg

Yan Brodskyi, Vitaliy Gyrya, Anatoly Zlotnik

We develop an explicit second order staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their pla

Spencer R. Klein

Quantum mechanics is central to coherent photoproduction in ultra-peripheral collisions (UPCs). This writeup will discuss some surprising aspects of UPCs that stem from these quantum mechanical roots. The Good-Walker (GW) paradigm, which connects coherent photoproduction with the target nucleus remaining in its ground state. This contrasts with a semi-classi

Tanuj Kumar, Demeng Feng, Shenwei Yin, Merlin Mah

Laser-light sails are a spacecraft concept wherein lightweight "sails" are propelled by high-intensity lasers. We investigated the near-infrared absorption of free-standing membranes of stoichiometric silicon nitride (Si$_3$N$_4$), a candidate sail material. To resolve the small but non-zero optical loss, we used photothermal common-path interferometry (PCI)

Mónica Clapp, Alberto Saldaña, Mayra Soares, Víctor A. Vicente-Benítez

We establish the existence of a solution to a nonlinear competitive Schr\"odinger system whose scalar potential tends to a positive constant at infinity with an appropriate rate. This solution has the property that all components are invariant under the action of a group of linear isometries and each component is obtained from the previous one by composing i

Douglas M. Gingrich

We calculate the quasinormal modes of a nonsingular spherically symmetric black hole effective model with holonomy corrections. The model is based on quantum corrections inspired by loop quantum gravity. It is covariant and results in a spacetime that is regular everywhere with a parameter-dependent black bounce. Perturbations of these black holes due to mas